## What changes were proposed in this pull request?
To implement the method `buildReader` in `FileFormat`, it is required to serialize the hadoop configuration for executors.
Previous spark-avro uses its own class `SerializableConfiguration` for the serialization. As now it is part of Spark, we can use SerializableConfiguration in Spark util to deduplicate the code.
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21846 from gengliangwang/removeSerializableConfiguration.
## What changes were proposed in this pull request?
As per Reynold's comment: https://github.com/apache/spark/pull/21742#discussion_r203496489
It makes sense to remove the implicit class AvroDataFrameWriter/AvroDataFrameReader, since the Avro package is external module.
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21841 from gengliangwang/removeImplicit.
## What changes were proposed in this pull request?
1. Add a new function from_avro for parsing a binary column of avro format and converting it into its corresponding catalyst value.
2. Add a new function to_avro for converting a column into binary of avro format with the specified schema.
I created #21774 for this, but it failed the build https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Compile/job/spark-master-compile-maven-hadoop-2.6/7902/
Additional changes In this PR:
1. Add `scalacheck` dependency in pom.xml to resolve the failure.
2. Update the `log4j.properties` to make it consistent with other modules.
## How was this patch tested?
Unit test
Compile with different commands:
```
./build/mvn --force -DzincPort=3643 -DskipTests -Phadoop-2.6 -Phive-thriftserver -Pkinesis-asl -Pspark-ganglia-lgpl -Pmesos -Pyarn compile test-compile
./build/mvn --force -DzincPort=3643 -DskipTests -Phadoop-2.7 -Phive-thriftserver -Pkinesis-asl -Pspark-ganglia-lgpl -Pmesos -Pyarn compile test-compile
./build/mvn --force -DzincPort=3643 -DskipTests -Phadoop-3.1 -Phive-thriftserver -Pkinesis-asl -Pspark-ganglia-lgpl -Pmesos -Pyarn compile test-compile
```
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21838 from gengliangwang/from_and_to_avro.
## What changes were proposed in this pull request?
I propose to add new option for AVRO datasource which should control ignoring of files without `.avro` extension in read. The option has name `ignoreExtension` with default value `true`. If both options `ignoreExtension` and `avro.mapred.ignore.inputs.without.extension` are set, `ignoreExtension` overrides the former one. Here is an example of usage:
```
spark
.read
.option("ignoreExtension", false)
.avro("path to avro files")
```
## How was this patch tested?
I added a test which checks the option directly and a test for checking that new option overrides hadoop's config.
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#21798 from MaxGekk/avro-ignore-extension.
## What changes were proposed in this pull request?
Previously in the refactoring of Avro Serializer and Deserializer, a new class SerializableSchema is created for serializing the Avro schema:
https://github.com/apache/spark/pull/21762/files#diff-01fea32e6ec6bcf6f34d06282e08705aR37
On second thought, we can use `toString` method for serialization. After that, parse the JSON format schema on executor. This makes the code much simpler.
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21829 from gengliangwang/removeSerializableSchema.
## What changes were proposed in this pull request?
Add a new function from_avro for parsing a binary column of avro format and converting it into its corresponding catalyst value.
Add a new function to_avro for converting a column into binary of avro format with the specified schema.
This PR is in progress. Will add test cases.
## How was this patch tested?
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21774 from gengliangwang/from_and_to_avro.
## What changes were proposed in this pull request?
As stated in https://github.com/apache/spark/pull/21321, in the error messages we should use `catalogString`. This is not the case, as SPARK-22893 used `simpleString` in order to have the same representation everywhere and it missed some places.
The PR unifies the messages using alway the `catalogString` representation of the dataTypes in the messages.
## How was this patch tested?
existing/modified UTs
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#21804 from mgaido91/SPARK-24268_catalog.
## What changes were proposed in this pull request?
In the PR, I propose to put all `Avro` options in new class `AvroOptions` in the same way as for other datasources `JSON` and `CSV`.
## How was this patch tested?
It was tested by `AvroSuite`
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#21810 from MaxGekk/avro-options.
## What changes were proposed in this pull request?
This pr fixes lint-java and Scala 2.12 build.
lint-java:
```
[ERROR] src/test/resources/log4j.properties:[0] (misc) NewlineAtEndOfFile: File does not end with a newline.
```
Scala 2.12 build:
```
[error] /.../sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousCoalesceRDD.scala:121: overloaded method value addTaskCompletionListener with alternatives:
[error] (f: org.apache.spark.TaskContext => Unit)org.apache.spark.TaskContext <and>
[error] (listener: org.apache.spark.util.TaskCompletionListener)org.apache.spark.TaskContext
[error] cannot be applied to (org.apache.spark.TaskContext => java.util.List[Runnable])
[error] context.addTaskCompletionListener { ctx =>
[error] ^
```
## How was this patch tested?
Manually executed lint-java and Scala 2.12 build in my local environment.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#21801 from ueshin/issues/SPARK-24386_24768/fix_build.
## What changes were proposed in this pull request?
In the PR, I propose to change default behaviour of AVRO datasource which currently ignores files without `.avro` extension in read by default. This PR sets the default value for `avro.mapred.ignore.inputs.without.extension` to `false` in the case if the parameter is not set by an user.
## How was this patch tested?
Added a test file without extension in AVRO format, and new test for reading the file with and wihout specified schema.
Author: Maxim Gekk <maxim.gekk@databricks.com>
Author: Maxim Gekk <max.gekk@gmail.com>
Closes#21769 from MaxGekk/avro-without-extension.
## What changes were proposed in this pull request?
In the PR, I propose to move `testFile()` to the common trait `SQLTestUtilsBase` and wrap test files in `AvroSuite` by the method `testFile()` which returns full paths to test files in the resource folder.
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#21773 from MaxGekk/test-file.
## What changes were proposed in this pull request?
Currently the Avro Deserializer converts input Avro format data to `Row`, and then convert the `Row` to `InternalRow`.
While the Avro Serializer converts `InternalRow` to `Row`, and then output Avro format data.
This PR allows direct conversion between `InternalRow` and Avro format data.
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21762 from gengliangwang/avro_io.
## What changes were proposed in this pull request?
Improve Avro unit test:
1. use QueryTest/SharedSQLContext/SQLTestUtils, instead of the duplicated test utils.
2. replace deprecated methods
This is a follow up PR for #21760, the PR passes pull request tests but failed in: https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Compile/job/spark-master-compile-maven-hadoop-2.6/7842/
This PR is to fix it.
## How was this patch tested?
Unit test.
Compile with different commands:
```
./build/mvn --force -DzincPort=3643 -DskipTests -Phadoop-2.6 -Phive-thriftserver -Pkinesis-asl -Pspark-ganglia-lgpl -Pmesos -Pyarn compile test-compile
./build/mvn --force -DzincPort=3643 -DskipTests -Phadoop-2.7 -Phive-thriftserver -Pkinesis-asl -Pspark-ganglia-lgpl -Pmesos -Pyarn compile test-compile
./build/mvn --force -DzincPort=3643 -DskipTests -Phadoop-3.1 -Phive-thriftserver -Pkinesis-asl -Pspark-ganglia-lgpl -Pmesos -Pyarn compile test-compile
```
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21768 from gengliangwang/improve_avro_test.
## What changes were proposed in this pull request?
Improve Avro unit test:
1. use QueryTest/SharedSQLContext/SQLTestUtils, instead of the duplicated test utils.
2. replace deprecated methods
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21760 from gengliangwang/improve_avro_test.
We have hundreds of kafka topics need to be consumed in one application. The application master will throw OOM exception after hanging for nearly half of an hour.
OOM happens in the env with a lot of topics, and it's not convenient to set up such kind of env in the unit test. So I didn't change/add test case.
Author: Yuanbo Liu <yuanbo@Yuanbos-MacBook-Air.local>
Author: yuanbo <yuanbo@apache.org>
Closes#21690 from yuanboliu/master.
## What changes were proposed in this pull request?
Apache Avro (https://avro.apache.org) is a popular data serialization format. It is widely used in the Spark and Hadoop ecosystem, especially for Kafka-based data pipelines. Using the external package https://github.com/databricks/spark-avro, Spark SQL can read and write the avro data. Making spark-Avro built-in can provide a better experience for first-time users of Spark SQL and structured streaming. We expect the built-in Avro data source can further improve the adoption of structured streaming.
The proposal is to inline code from spark-avro package (https://github.com/databricks/spark-avro). The target release is Spark 2.4.
[Built-in AVRO Data Source In Spark 2.4.pdf](https://github.com/apache/spark/files/2181511/Built-in.AVRO.Data.Source.In.Spark.2.4.pdf)
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21742 from gengliangwang/export_avro.
Setting the timestamp directly would cause exception on reading stream, it can be set directly only if the mode is not AT_TIMESTAMP
## What changes were proposed in this pull request?
The last patch in the kinesis streaming receiver sets the timestamp for the mode AT_TIMESTAMP, but this mode can only be set via the
`baseClientLibConfiguration.withTimestampAtInitialPositionInStream()
`
and can't be set directly using
`.withInitialPositionInStream()`
This patch fixes the issue.
## How was this patch tested?
Kinesis Receiver doesn't expose the internal state outside, so couldn't find the right way to test this change. Seeking for tips from other contributors here.
Author: Yash Sharma <ysharma@atlassian.com>
Closes#21541 from yashs360/ysharma/fix_kinesis_bug.
## What changes were proposed in this pull request?
SPARK-22893 tried to unify error messages about dataTypes. Unfortunately, still many places were missing the `simpleString` method in other to have the same representation everywhere.
The PR unified the messages using alway the simpleString representation of the dataTypes in the messages.
## How was this patch tested?
existing/modified UTs
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#21321 from mgaido91/SPARK-24268.
This passes the unique task attempt id instead of attempt number to v2 data sources because attempt number is reused when stages are retried. When attempt numbers are reused, sources that track data by partition id and attempt number may incorrectly clean up data because the same attempt number can be both committed and aborted.
For v1 / Hadoop writes, generate a unique ID based on available attempt numbers to avoid a similar problem.
Closes#21558
Author: Marcelo Vanzin <vanzin@cloudera.com>
Author: Ryan Blue <blue@apache.org>
Closes#21606 from vanzin/SPARK-24552.2.
## What changes were proposed in this pull request?
This PR replaces `getTimeAsMs` with `getTimeAsSeconds` to fix the issue that reading "spark.network.timeout" using a wrong time unit when the user doesn't specify a time out.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <zsxwing@gmail.com>
Closes#21382 from zsxwing/fix-network-timeout-conf.
## What changes were proposed in this pull request?
`CachedKafkaConsumer` in the project streaming-kafka-0-10 is designed to maintain a pool of KafkaConsumers that can be reused. However, it was built with the assumption there will be only one thread trying to read the same Kafka TopicPartition at the same time. This assumption is not true all the time and this can inadvertently lead to ConcurrentModificationException.
Here is a better way to design this. The consumer pool should be smart enough to avoid concurrent use of a cached consumer. If there is another request for the same TopicPartition as a currently in-use consumer, the pool should automatically return a fresh consumer.
- There are effectively two kinds of consumer that may be generated
- Cached consumer - this should be returned to the pool at task end
- Non-cached consumer - this should be closed at task end
- A trait called `KafkaDataConsumer` is introduced to hide this difference from the users of the consumer so that the client code does not have to reason about whether to stop and release. They simply call `val consumer = KafkaDataConsumer.acquire` and then `consumer.release`.
- If there is request for a consumer that is in-use, then a new consumer is generated.
- If there is request for a consumer which is a task reattempt, then already existing cached consumer will be invalidated and a new consumer is generated. This could fix potential issues if the source of the reattempt is a malfunctioning consumer.
- In addition, I renamed the `CachedKafkaConsumer` class to `KafkaDataConsumer` because is a misnomer given that what it returns may or may not be cached.
## How was this patch tested?
A new stress test that verifies it is safe to concurrently get consumers for the same TopicPartition from the consumer pool.
Author: Gabor Somogyi <gabor.g.somogyi@gmail.com>
Closes#20997 from gaborgsomogyi/SPARK-19185.
## What changes were proposed in this pull request?
SPARK-24073 renames DataReaderFactory -> InputPartition and DataReader -> InputPartitionReader. Some classes still reflects the old name and causes confusion. This patch renames the left over classes to reflect the new interface and fixes a few comments.
## How was this patch tested?
Existing unit tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Arun Mahadevan <arunm@apache.org>
Closes#21355 from arunmahadevan/SPARK-24308.
## What changes were proposed in this pull request?
Renames:
* `DataReaderFactory` to `InputPartition`
* `DataReader` to `InputPartitionReader`
* `createDataReaderFactories` to `planInputPartitions`
* `createUnsafeDataReaderFactories` to `planUnsafeInputPartitions`
* `createBatchDataReaderFactories` to `planBatchInputPartitions`
This fixes the changes in SPARK-23219, which renamed ReadTask to
DataReaderFactory. The intent of that change was to make the read and
write API match (write side uses DataWriterFactory), but the underlying
problem is that the two classes are not equivalent.
ReadTask/DataReader function as Iterable/Iterator. One InputPartition is
a specific partition of the data to be read, in contrast to
DataWriterFactory where the same factory instance is used in all write
tasks. InputPartition's purpose is to manage the lifecycle of the
associated reader, which is now called InputPartitionReader, with an
explicit create operation to mirror the close operation. This was no
longer clear from the API because DataReaderFactory appeared to be more
generic than it is and it isn't clear why a set of them is produced for
a read.
## How was this patch tested?
Existing tests, which have been updated to use the new name.
Author: Ryan Blue <blue@apache.org>
Closes#21145 from rdblue/SPARK-24073-revert-data-reader-factory-rename.
## What changes were proposed in this pull request?
This makes it easy to understand at runtime which version is running. Great for debugging production issues.
## How was this patch tested?
Not necessary.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#21160 from tdas/SPARK-24094.
## What changes were proposed in this pull request?
In some streaming queries, the input and processing rates are not calculated at all (shows up as zero) because MicroBatchExecution fails to associated metrics from the executed plan of a trigger with the sources in the logical plan of the trigger. The way this executed-plan-leaf-to-logical-source attribution works is as follows. With V1 sources, there was no way to identify which execution plan leaves were generated by a streaming source. So did a best-effort attempt to match logical and execution plan leaves when the number of leaves were same. In cases where the number of leaves is different, we just give up and report zero rates. An example where this may happen is as follows.
```
val cachedStaticDF = someStaticDF.union(anotherStaticDF).cache()
val streamingInputDF = ...
val query = streamingInputDF.join(cachedStaticDF).writeStream....
```
In this case, the `cachedStaticDF` has multiple logical leaves, but in the trigger's execution plan it only has leaf because a cached subplan is represented as a single InMemoryTableScanExec leaf. This leads to a mismatch in the number of leaves causing the input rates to be computed as zero.
With DataSourceV2, all inputs are represented in the executed plan using `DataSourceV2ScanExec`, each of which has a reference to the associated logical `DataSource` and `DataSourceReader`. So its easy to associate the metrics to the original streaming sources.
In this PR, the solution is as follows. If all the streaming sources in a streaming query as v2 sources, then use a new code path where the execution-metrics-to-source mapping is done directly. Otherwise we fall back to existing mapping logic.
## How was this patch tested?
- New unit tests using V2 memory source
- Existing unit tests using V1 source
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#21126 from tdas/SPARK-24050.
## What changes were proposed in this pull request?
Currently, the driver side of the Kafka source (i.e. KafkaMicroBatchReader) eagerly creates a consumer as soon as the Kafk aMicroBatchReader is created. However, we create dummy KafkaMicroBatchReader to get the schema and immediately stop it. Its better to make the consumer creation lazy, it will be created on the first attempt to fetch offsets using the KafkaOffsetReader.
## How was this patch tested?
Existing unit tests
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#21134 from tdas/SPARK-24056.
## What changes were proposed in this pull request?
Kafka partitions can be revoked when new consumers joined in the consumer group to rebalance the partitions. But current Spark Kafka connector code makes sure there's no partition revoking scenarios, so trying to get latest offset from revoked partitions will throw exceptions as JIRA mentioned.
Partition revoking happens when new consumer joined the consumer group, which means different streaming apps are trying to use same group id. This is fundamentally not correct, different apps should use different consumer group. So instead of throwing an confused exception from Kafka, improve the exception message by identifying revoked partition and directly throw an meaningful exception when partition is revoked.
Besides, this PR also fixes bugs in `DirectKafkaWordCount`, this example simply cannot be worked without the fix.
```
8/01/05 09:48:27 INFO internals.ConsumerCoordinator: Revoking previously assigned partitions [kssh-7, kssh-4, kssh-3, kssh-6, kssh-5, kssh-0, kssh-2, kssh-1] for group use_a_separate_group_id_for_each_stream
18/01/05 09:48:27 INFO internals.AbstractCoordinator: (Re-)joining group use_a_separate_group_id_for_each_stream
18/01/05 09:48:27 INFO internals.AbstractCoordinator: Successfully joined group use_a_separate_group_id_for_each_stream with generation 4
18/01/05 09:48:27 INFO internals.ConsumerCoordinator: Setting newly assigned partitions [kssh-7, kssh-4, kssh-6, kssh-5] for group use_a_separate_group_id_for_each_stream
```
## How was this patch tested?
This is manually verified in local cluster, unfortunately I'm not sure how to simulate it in UT, so propose the PR without UT added.
Author: jerryshao <sshao@hortonworks.com>
Closes#21038 from jerryshao/SPARK-22968.
## What changes were proposed in this pull request?
There was no check on nullability for arguments of `Tuple`s. This could lead to have weird behavior when a null value had to be deserialized into a non-nullable Scala object: in those cases, the `null` got silently transformed in a valid value (like `-1` for `Int`), corresponding to the default value we are using in the SQL codebase. This situation was very likely to happen when deserializing to a Tuple of primitive Scala types (like Double, Int, ...).
The PR adds the `AssertNotNull` to arguments of tuples which have been asked to be converted to non-nullable types.
## How was this patch tested?
added UT
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#20976 from mgaido91/SPARK-23835.
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Nolan Emirot <nolan@turo.com>
Closes#20990 from emirot/kinesis_stream_example_typo.
## What changes were proposed in this pull request?
This PR implemented the following cleanups related to `UnsafeWriter` class:
- Remove code duplication between `UnsafeRowWriter` and `UnsafeArrayWriter`
- Make `BufferHolder` class internal by delegating its accessor methods to `UnsafeWriter`
- Replace `UnsafeRow.setTotalSize(...)` with `UnsafeRowWriter.setTotalSize()`
## How was this patch tested?
Tested by existing UTs
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#20850 from kiszk/SPARK-23713.
## What changes were proposed in this pull request?
Add `spark.streaming.backpressure.initialRate` to direct Kafka Streams for Kafka 0.8 and 0.10
This is required in order to be able to use backpressure with huge lags, which cannot be processed at once. Without this parameter `DirectKafkaInputDStream` with backpressure enabled would try to get all the possible data from Kafka before adjusting consumption rate
## How was this patch tested?
- Tests added to `org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala` and `org/apache/spark/streaming/kafka/DirectKafkaStreamSuite.scala`
- Manual tests on YARN cluster
Author: akonopko <alex.konopko@teamaol.com>
Author: Alexander Konopko <alexander.konopko@gmail.com>
Closes#19431 from akonopko/SPARK-18580-initialrate.
## What changes were proposed in this pull request?
CacheKafkaConsumer in the project `kafka-0-10-sql` is designed to maintain a pool of KafkaConsumers that can be reused. However, it was built with the assumption there will be only one task using trying to read the same Kafka TopicPartition at the same time. Hence, the cache was keyed by the TopicPartition a consumer is supposed to read. And any cases where this assumption may not be true, we have SparkPlan flag to disable the use of a cache. So it was up to the planner to correctly identify when it was not safe to use the cache and set the flag accordingly.
Fundamentally, this is the wrong way to approach the problem. It is HARD for a high-level planner to reason about the low-level execution model, whether there will be multiple tasks in the same query trying to read the same partition. Case in point, 2.3.0 introduced stream-stream joins, and you can build a streaming self-join query on Kafka. It's pretty non-trivial to figure out how this leads to two tasks reading the same partition twice, possibly concurrently. And due to the non-triviality, it is hard to figure this out in the planner and set the flag to avoid the cache / consumer pool. And this can inadvertently lead to ConcurrentModificationException ,or worse, silent reading of incorrect data.
Here is a better way to design this. The planner shouldnt have to understand these low-level optimizations. Rather the consumer pool should be smart enough avoid concurrent use of a cached consumer. Currently, it tries to do so but incorrectly (the flag inuse is not checked when returning a cached consumer, see [this](https://github.com/apache/spark/blob/master/external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/CachedKafkaConsumer.scala#L403)). If there is another request for the same partition as a currently in-use consumer, the pool should automatically return a fresh consumer that should be closed when the task is done. Then the planner does not have to have a flag to avoid reuses.
This PR is a step towards that goal. It does the following.
- There are effectively two kinds of consumer that may be generated
- Cached consumer - this should be returned to the pool at task end
- Non-cached consumer - this should be closed at task end
- A trait called KafkaConsumer is introduced to hide this difference from the users of the consumer so that the client code does not have to reason about whether to stop and release. They simply called `val consumer = KafkaConsumer.acquire` and then `consumer.release()`.
- If there is request for a consumer that is in-use, then a new consumer is generated.
- If there is a concurrent attempt of the same task, then a new consumer is generated, and the existing cached consumer is marked for close upon release.
- In addition, I renamed the classes because CachedKafkaConsumer is a misnomer given that what it returns may or may not be cached.
This PR does not remove the planner flag to avoid reuse to make this patch safe enough for merging in branch-2.3. This can be done later in master-only.
## How was this patch tested?
A new stress test that verifies it is safe to concurrently get consumers for the same partition from the consumer pool.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#20767 from tdas/SPARK-23623.
## What changes were proposed in this pull request?
Omit rounding of backpressure rate. Effects:
- no batch with large number of records is created when rate from PID estimator is one
- the number of records per batch and partition is more fine-grained improving backpressure accuracy
## How was this patch tested?
This was tested by running:
- `mvn test -pl external/kafka-0-8`
- `mvn test -pl external/kafka-0-10`
- a streaming application which was suffering from the issue
JasonMWhite
The contribution is my original work and I license the work to the project under the project’s open source license
Author: Sebastian Arzt <sebastian.arzt@plista.com>
Closes#17774 from arzt/kafka-back-pressure.
## What changes were proposed in this pull request?
As discussion in #20675, we need add a new interface `ContinuousDataReaderFactory` to support the requirements of setting start offset in Continuous Processing.
## How was this patch tested?
Existing UT.
Author: Yuanjian Li <xyliyuanjian@gmail.com>
Closes#20689 from xuanyuanking/SPARK-23533.
## What changes were proposed in this pull request?
Add an epoch ID argument to DataWriterFactory for use in streaming. As a side effect of passing in this value, DataWriter will now have a consistent lifecycle; commit() or abort() ends the lifecycle of a DataWriter instance in any execution mode.
I considered making a separate streaming interface and adding the epoch ID only to that one, but I think it requires a lot of extra work for no real gain. I think it makes sense to define epoch 0 as the one and only epoch of a non-streaming query.
## How was this patch tested?
existing unit tests
Author: Jose Torres <jose@databricks.com>
Closes#20710 from jose-torres/api2.
## What changes were proposed in this pull request?
Currently, when the Kafka source reads from Kafka, it generates as many tasks as the number of partitions in the topic(s) to be read. In some case, it may be beneficial to read the data with greater parallelism, that is, with more number partitions/tasks. That means, offset ranges must be divided up into smaller ranges such the number of records in partition ~= total records in batch / desired partitions. This would also balance out any data skews between topic-partitions.
In this patch, I have added a new option called `minPartitions`, which allows the user to specify the desired level of parallelism.
## How was this patch tested?
New tests in KafkaMicroBatchV2SourceSuite.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#20698 from tdas/SPARK-23541.
## What changes were proposed in this pull request?
Add a configuration spark.streaming.kafka.allowNonConsecutiveOffsets to allow streaming jobs to proceed on compacted topics (or other situations involving gaps between offsets in the log).
## How was this patch tested?
Added new unit test
justinrmiller has been testing this branch in production for a few weeks
Author: cody koeninger <cody@koeninger.org>
Closes#20572 from koeninger/SPARK-17147.
## What changes were proposed in this pull request?
var `KafkaContinuousReader.knownPartitions` should be threadsafe as it is accessed from multiple threads - the query thread at the time of reader factory creation, and the epoch tracking thread at the time of `needsReconfiguration`.
## How was this patch tested?
Existing tests.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#20655 from tdas/SPARK-23484.
## What changes were proposed in this pull request?
SPARK-23203: DataSourceV2 should use immutable catalyst trees instead of wrapping a mutable DataSourceV2Reader. This commit updates DataSourceV2Relation and consolidates much of the DataSourceV2 API requirements for the read path in it. Instead of wrapping a reader that changes, the relation lazily produces a reader from its configuration.
This commit also updates the predicate and projection push-down. Instead of the implementation from SPARK-22197, this reuses the rule matching from the Hive and DataSource read paths (using `PhysicalOperation`) and copies most of the implementation of `SparkPlanner.pruneFilterProject`, with updates for DataSourceV2. By reusing the implementation from other read paths, this should have fewer regressions from other read paths and is less code to maintain.
The new push-down rules also supports the following edge cases:
* The output of DataSourceV2Relation should be what is returned by the reader, in case the reader can only partially satisfy the requested schema projection
* The requested projection passed to the DataSourceV2Reader should include filter columns
* The push-down rule may be run more than once if filters are not pushed through projections
## How was this patch tested?
Existing push-down and read tests.
Author: Ryan Blue <blue@apache.org>
Closes#20387 from rdblue/SPARK-22386-push-down-immutable-trees.
## What changes were proposed in this pull request?
Migrating KafkaSource (with data source v1) to KafkaMicroBatchReader (with data source v2).
Performance comparison:
In a unit test with in-process Kafka broker, I tested the read throughput of V1 and V2 using 20M records in a single partition. They were comparable.
## How was this patch tested?
Existing tests, few modified to be better tests than the existing ones.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#20554 from tdas/SPARK-23362.
## What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/20435.
While reorganizing the packages for streaming data source v2, the top level stream read/write support interfaces should not be in the reader/writer package, but should be in the `sources.v2` package, to follow the `ReadSupport`, `WriteSupport`, etc.
## How was this patch tested?
N/A
Author: Wenchen Fan <wenchen@databricks.com>
Closes#20509 from cloud-fan/followup.
## What changes were proposed in this pull request?
In the document of `ContinuousReader.setOffset`, we say this method is used to specify the start offset. We also have a `ContinuousReader.getStartOffset` to get the value back. I think it makes more sense to rename `ContinuousReader.setOffset` to `setStartOffset`.
## How was this patch tested?
N/A
Author: Wenchen Fan <wenchen@databricks.com>
Closes#20486 from cloud-fan/rename.
## What changes were proposed in this pull request?
1. create a new package for partitioning/distribution related classes.
As Spark will add new concrete implementations of `Distribution` in new releases, it is good to
have a new package for partitioning/distribution related classes.
2. move streaming related class to package `org.apache.spark.sql.sources.v2.reader/writer.streaming`, instead of `org.apache.spark.sql.sources.v2.streaming.reader/writer`.
So that the there won't be package reader/writer inside package streaming, which is quite confusing.
Before change:
```
v2
├── reader
├── streaming
│ ├── reader
│ └── writer
└── writer
```
After change:
```
v2
├── reader
│ └── streaming
└── writer
└── streaming
```
## How was this patch tested?
Unit test.
Author: Wang Gengliang <ltnwgl@gmail.com>
Closes#20435 from gengliangwang/new_pkg.
## What changes were proposed in this pull request?
All other classes in the reader/writer package doesn't have `V2` in their names, and the streaming reader/writer don't have `V2` either. It's more consistent to remove `V2` from `DataSourceV2Reader` and `DataSourceVWriter`.
Also rename `DataSourceV2Option` to remote the `V2`, we should only have `V2` in the root interface: `DataSourceV2`.
This PR also fixes some places that the mix-in interface doesn't extend the interface it aimed to mix in.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#20427 from cloud-fan/ds-v2.
## What changes were proposed in this pull request?
Currently we have `ReadTask` in data source v2 reader, while in writer we have `DataWriterFactory`.
To make the naming consistent and better, renaming `ReadTask` to `DataReaderFactory`.
## How was this patch tested?
Unit test
Author: Wang Gengliang <ltnwgl@gmail.com>
Closes#20397 from gengliangwang/rename.
## What changes were proposed in this pull request?
Replace streaming V2 sinks with a unified StreamWriteSupport interface, with a shim to use it with microbatch execution.
Add a new SQL config to use for disabling V2 sinks, falling back to the V1 sink implementation.
## How was this patch tested?
Existing tests, which in the case of Kafka (the only existing continuous V2 sink) now use V2 for microbatch.
Author: Jose Torres <jose@databricks.com>
Closes#20369 from jose-torres/streaming-sink.
## What changes were proposed in this pull request?
KafkaSourceSuiteBase should be abstract class, otherwise KafkaSourceSuiteBase will also run.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <zsxwing@gmail.com>
Closes#20412 from zsxwing/SPARK-23242.
## What changes were proposed in this pull request?
Currently, `KafkaContinuousSourceStressForDontFailOnDataLossSuite` runs on `MicroBatchExecution`. It should test `ContinuousExecution`.
## How was this patch tested?
Pass the updated test suite.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#20374 from dongjoon-hyun/SPARK-23198.
## What changes were proposed in this pull request?
Typo fixes
## How was this patch tested?
Local build / Doc-only changes
Author: Jacek Laskowski <jacek@japila.pl>
Closes#20344 from jaceklaskowski/typo-fixes.
## What changes were proposed in this pull request?
Continuous processing tasks will fail on any attempt number greater than 0. ContinuousExecution will catch these failures and restart globally from the last recorded checkpoints.
## How was this patch tested?
unit test
Author: Jose Torres <jose@databricks.com>
Closes#20225 from jose-torres/no-retry.
## What changes were proposed in this pull request?
The first commit added a new test, and the second refactored the class the test was in. The automatic merge put the test in the wrong place.
## How was this patch tested?
-
Author: Jose Torres <jose@databricks.com>
Closes#20289 from jose-torres/fix.
## What changes were proposed in this pull request?
The Kafka reader is now interruptible and can close itself.
## How was this patch tested?
I locally ran one of the ContinuousKafkaSourceSuite tests in a tight loop. Before the fix, my machine ran out of open file descriptors a few iterations in; now it works fine.
Author: Jose Torres <jose@databricks.com>
Closes#20253 from jose-torres/fix-data-reader.
## What changes were proposed in this pull request?
This problem reported by yanlin-Lynn ivoson and LiangchangZ. Thanks!
When we union 2 streams from kafka or other sources, while one of them have no continues data coming and in the same time task restart, this will cause an `IllegalStateException`. This mainly cause because the code in [MicroBatchExecution](https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/MicroBatchExecution.scala#L190) , while one stream has no continues data, its comittedOffset same with availableOffset during `populateStartOffsets`, and `currentPartitionOffsets` not properly handled in KafkaSource. Also, maybe we should also consider this scenario in other Source.
## How was this patch tested?
Add a UT in KafkaSourceSuite.scala
Author: Yuanjian Li <xyliyuanjian@gmail.com>
Closes#20150 from xuanyuanking/SPARK-22956.
## What changes were proposed in this pull request?
This PR aims to update the followings in `docker/spark-test`.
- JDK7 -> JDK8
Spark 2.2+ supports JDK8 only.
- Ubuntu 12.04.5 LTS(precise) -> Ubuntu 16.04.3 LTS(xeniel)
The end of life of `precise` was April 28, 2017.
## How was this patch tested?
Manual.
* Master
```
$ cd external/docker
$ ./build
$ export SPARK_HOME=...
$ docker run -v $SPARK_HOME:/opt/spark spark-test-master
CONTAINER_IP=172.17.0.3
...
18/01/11 06:50:25 INFO MasterWebUI: Bound MasterWebUI to 172.17.0.3, and started at http://172.17.0.3:8080
18/01/11 06:50:25 INFO Utils: Successfully started service on port 6066.
18/01/11 06:50:25 INFO StandaloneRestServer: Started REST server for submitting applications on port 6066
18/01/11 06:50:25 INFO Master: I have been elected leader! New state: ALIVE
```
* Slave
```
$ docker run -v $SPARK_HOME:/opt/spark spark-test-worker spark://172.17.0.3:7077
CONTAINER_IP=172.17.0.4
...
18/01/11 06:51:54 INFO Worker: Successfully registered with master spark://172.17.0.3:7077
```
After slave starts, master will show
```
18/01/11 06:51:54 INFO Master: Registering worker 172.17.0.4:8888 with 4 cores, 1024.0 MB RAM
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#20230 from dongjoon-hyun/SPARK-23038.
## What changes were proposed in this pull request?
This patch bumps the master branch version to `2.4.0-SNAPSHOT`.
## How was this patch tested?
N/A
Author: gatorsmile <gatorsmile@gmail.com>
Closes#20222 from gatorsmile/bump24.
## What changes were proposed in this pull request?
Add kafka source and sink for continuous processing. This involves two small changes to the execution engine:
* Bring data reader close() into the normal data reader thread to avoid thread safety issues.
* Fix up the semantics of the RECONFIGURING StreamExecution state. State updates are now atomic, and we don't have to deal with swallowing an exception.
## How was this patch tested?
new unit tests
Author: Jose Torres <jose@databricks.com>
Closes#20096 from jose-torres/continuous-kafka.
## What changes were proposed in this pull request?
This PR cleans up a few Java linter errors for Apache Spark 2.3 release.
## How was this patch tested?
```bash
$ dev/lint-java
Using `mvn` from path: /usr/local/bin/mvn
Checkstyle checks passed.
```
We can see the result from [Travis CI](https://travis-ci.org/dongjoon-hyun/spark/builds/322470787), too.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#20101 from dongjoon-hyun/fix-java-lint.
## What changes were proposed in this pull request?
Kinesis client can resume from a specified timestamp while creating a stream. We should have option to pass a timestamp in config to allow kinesis to resume from the given timestamp.
The patch introduces a new `KinesisInitialPositionInStream` that takes the `InitialPositionInStream` with the `timestamp` information that can be used to resume kinesis fetches from the provided timestamp.
## How was this patch tested?
Unit Tests
cc : budde brkyvz
Author: Yash Sharma <ysharma@atlassian.com>
Closes#18029 from yssharma/ysharma/kcl_resume.
## What changes were proposed in this pull request?
Some users depend on source compatibility with the org.apache.spark.sql.execution.streaming.Offset class. Although this is not a stable interface, we can keep it in place for now to simplify upgrades to 2.3.
Author: Jose Torres <jose@databricks.com>
Closes#20012 from joseph-torres/binary-compat.
## What changes were proposed in this pull request?
This PR provides DataSourceV2 API support for structured streaming, including new pieces needed to support continuous processing [SPARK-20928]. High level summary:
- DataSourceV2 includes new mixins to support micro-batch and continuous reads and writes. For reads, we accept an optional user specified schema rather than using the ReadSupportWithSchema model, because doing so would severely complicate the interface.
- DataSourceV2Reader includes new interfaces to read a specific microbatch or read continuously from a given offset. These follow the same setter pattern as the existing Supports* mixins so that they can work with SupportsScanUnsafeRow.
- DataReader (the per-partition reader) has a new subinterface ContinuousDataReader only for continuous processing. This reader has a special method to check progress, and next() blocks for new input rather than returning false.
- Offset, an abstract representation of position in a streaming query, is ported to the public API. (Each type of reader will define its own Offset implementation.)
- DataSourceV2Writer has a new subinterface ContinuousWriter only for continuous processing. Commits to this interface come tagged with an epoch number, as the execution engine will continue to produce new epoch commits as the task continues indefinitely.
Note that this PR does not propose to change the existing DataSourceV2 batch API, or deprecate the existing streaming source/sink internal APIs in spark.sql.execution.streaming.
## How was this patch tested?
Toy implementations of the new interfaces with unit tests.
Author: Jose Torres <jose@databricks.com>
Closes#19925 from joseph-torres/continuous-api.
## What changes were proposed in this pull request?
In the previous PRs, https://github.com/apache/spark/pull/17832 and https://github.com/apache/spark/pull/17835 , we convert `TIMESTAMP WITH TIME ZONE` and `TIME WITH TIME ZONE` to `TIMESTAMP` for all the JDBC sources. However, this conversion could be risky since it does not respect our SQL configuration `spark.sql.session.timeZone`.
In addition, each vendor might have different semantics for these two types. For example, Postgres simply returns `TIMESTAMP` types for `TIMESTAMP WITH TIME ZONE`. For such supports, we should do it case by case. This PR reverts the general support of `TIMESTAMP WITH TIME ZONE` and `TIME WITH TIME ZONE` for JDBC sources, except ORACLE Dialect.
When supporting the ORACLE's `TIMESTAMP WITH TIME ZONE`, we only support it when the JVM default timezone is the same as the user-specified configuration `spark.sql.session.timeZone` (whose default is the JVM default timezone). Now, we still treat `TIMESTAMP WITH TIME ZONE` as `TIMESTAMP` when fetching the values via the Oracle JDBC connector, whose client converts the timestamp values with time zone to the timestamp values using the local JVM default timezone (a test case is added to `OracleIntegrationSuite.scala` in this PR for showing the behavior). Thus, to avoid any future behavior change, we will not support it if JVM default timezone is different from `spark.sql.session.timeZone`
No regression because the previous two PRs were just merged to be unreleased master branch.
## How was this patch tested?
Added the test cases
Author: gatorsmile <gatorsmile@gmail.com>
Closes#19939 from gatorsmile/timezoneUpdate.
…a-2.12 and JDK9
## What changes were proposed in this pull request?
Some compile error after upgrading to scala-2.12
```javascript
spark_source/core/src/main/scala/org/apache/spark/executor/Executor.scala:455: ambiguous reference to overloaded definition, method limit in class ByteBuffer of type (x$1: Int)java.nio.ByteBuffer
method limit in class Buffer of type ()Int
match expected type ?
val resultSize = serializedDirectResult.limit
error
```
The limit method was moved from ByteBuffer to the superclass Buffer and it can no longer be called without (). The same reason for position method.
```javascript
/home/zly/prj/oss/jdk9_HOS_SOURCE/spark_source/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformationExec.scala:427: ambiguous reference to overloaded definition, [error] both method putAll in class Properties of type (x$1: java.util.Map[_, _])Unit [error] and method putAll in class Hashtable of type (x$1: java.util.Map[_ <: Object, _ <: Object])Unit [error] match argument types (java.util.Map[String,String])
[error] props.putAll(outputSerdeProps.toMap.asJava)
[error] ^
```
This is because the key type is Object instead of String which is unsafe.
## How was this patch tested?
running tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: kellyzly <kellyzly@126.com>
Closes#19854 from kellyzly/SPARK-22660.
## What changes were proposed in this pull request?
This PR fixes the conversion error when reads data from a PostgreSQL table that contains columns of `uuid[]`, `inet[]` and `cidr[]` data types.
For example, create a table with the uuid[] data type, and insert the test data.
```SQL
CREATE TABLE users
(
id smallint NOT NULL,
name character varying(50),
user_ids uuid[],
PRIMARY KEY (id)
)
INSERT INTO users ("id", "name","user_ids")
VALUES (1, 'foo', ARRAY
['7be8aaf8-650e-4dbb-8186-0a749840ecf2'
,'205f9bfc-018c-4452-a605-609c0cfad228']::UUID[]
)
```
Then it will throw the following exceptions when trying to load the data.
```
java.lang.ClassCastException: [Ljava.util.UUID; cannot be cast to [Ljava.lang.String;
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$14.apply(JdbcUtils.scala:459)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$14.apply(JdbcUtils.scala:458)
...
```
## How was this patch tested?
Added test in `PostgresIntegrationSuite`.
Author: Jen-Ming Chung <jenmingisme@gmail.com>
Closes#19567 from jmchung/SPARK-22291.
TIMESTAMP (-101), BINARY_DOUBLE (101) and BINARY_FLOAT (100) are handled in OracleDialect
## What changes were proposed in this pull request?
When a oracle table contains columns whose type is BINARY_FLOAT or BINARY_DOUBLE, spark sql fails to load a table with SQLException
```
java.sql.SQLException: Unsupported type 101
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getCatalystType(JdbcUtils.scala:235)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$8.apply(JdbcUtils.scala:292)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$8.apply(JdbcUtils.scala:292)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.getSchema(JdbcUtils.scala:291)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD$.resolveTable(JDBCRDD.scala:64)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation.<init>(JDBCRelation.scala:113)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:47)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:306)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:146)
```
## How was this patch tested?
I updated a UT which covers type conversion test for types (-101, 100, 101), on top of that I tested this change against actual table with those columns and it was able to read and write to the table.
Author: Kohki Nishio <taroplus@me.com>
Closes#19548 from taroplus/oracle_sql_types_101.
## What changes were proposed in this pull request?
Move flume behind a profile, take 2. See https://github.com/apache/spark/pull/19365 for most of the back-story.
This change should fix the problem by removing the examples module dependency and moving Flume examples to the module itself. It also adds deprecation messages, per a discussion on dev about deprecating for 2.3.0.
## How was this patch tested?
Existing tests, which still enable flume integration.
Author: Sean Owen <sowen@cloudera.com>
Closes#19412 from srowen/SPARK-22142.2.
## What changes were proposed in this pull request?
Enable Scala 2.12 REPL. Fix most remaining issues with 2.12 compilation and warnings, including:
- Selecting Kafka 0.10.1+ for Scala 2.12 and patching over a minor API difference
- Fixing lots of "eta expansion of zero arg method deprecated" warnings
- Resolving the SparkContext.sequenceFile implicits compile problem
- Fixing an odd but valid jetty-server missing dependency in hive-thriftserver
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#19307 from srowen/Scala212.
## What changes were proposed in this pull request?
Auto generated Oracle schema some times not we expect:
- `number(1)` auto mapped to BooleanType, some times it's not we expect, per [SPARK-20921](https://issues.apache.org/jira/browse/SPARK-20921).
- `number` auto mapped to Decimal(38,10), It can't read big data, per [SPARK-20427](https://issues.apache.org/jira/browse/SPARK-20427).
This PR fix this issue by custom schema as follows:
```scala
val props = new Properties()
props.put("customSchema", "ID decimal(38, 0), N1 int, N2 boolean")
val dfRead = spark.read.schema(schema).jdbc(jdbcUrl, "tableWithCustomSchema", props)
dfRead.show()
```
or
```sql
CREATE TEMPORARY VIEW tableWithCustomSchema
USING org.apache.spark.sql.jdbc
OPTIONS (url '$jdbcUrl', dbTable 'tableWithCustomSchema', customSchema'ID decimal(38, 0), N1 int, N2 boolean')
```
## How was this patch tested?
unit tests
Author: Yuming Wang <wgyumg@gmail.com>
Closes#18266 from wangyum/SPARK-20427.
## What changes were proposed in this pull request?
Put Kafka 0.8 support behind a kafka-0-8 profile.
## How was this patch tested?
Existing tests, but, until PR builder and Jenkins configs are updated the effect here is to not build or test Kafka 0.8 support at all.
Author: Sean Owen <sowen@cloudera.com>
Closes#19134 from srowen/SPARK-21893.
## What changes were proposed in this pull request?
this PR describe remove the import class that are unused.
## How was this patch tested?
N/A
Author: caoxuewen <cao.xuewen@zte.com.cn>
Closes#19131 from heary-cao/unuse_import.
…build; fix some things that will be warnings or errors in 2.12; restore Scala 2.12 profile infrastructure
## What changes were proposed in this pull request?
This change adds back the infrastructure for a Scala 2.12 build, but does not enable it in the release or Python test scripts.
In order to make that meaningful, it also resolves compile errors that the code hits in 2.12 only, in a way that still works with 2.11.
It also updates dependencies to the earliest minor release of dependencies whose current version does not yet support Scala 2.12. This is in a sense covered by other JIRAs under the main umbrella, but implemented here. The versions below still work with 2.11, and are the _latest_ maintenance release in the _earliest_ viable minor release.
- Scalatest 2.x -> 3.0.3
- Chill 0.8.0 -> 0.8.4
- Clapper 1.0.x -> 1.1.2
- json4s 3.2.x -> 3.4.2
- Jackson 2.6.x -> 2.7.9 (required by json4s)
This change does _not_ fully enable a Scala 2.12 build:
- It will also require dropping support for Kafka before 0.10. Easy enough, just didn't do it yet here
- It will require recreating `SparkILoop` and `Main` for REPL 2.12, which is SPARK-14650. Possible to do here too.
What it does do is make changes that resolve much of the remaining gap without affecting the current 2.11 build.
## How was this patch tested?
Existing tests and build. Manually tested with `./dev/change-scala-version.sh 2.12` to verify it compiles, modulo the exceptions above.
Author: Sean Owen <sowen@cloudera.com>
Closes#18645 from srowen/SPARK-14280.
During profiling of a structured streaming application with Kafka as the source, I came across this exception:
This is a 1 minute sample, which caused 106K `NonLocalReturnControl` exceptions to be thrown.
This happens because `CachedKafkaConsumer.get` is ran inside:
`private def runUninterruptiblyIfPossible[T](body: => T): T`
Where `body: => T` is the `get` method. Turning the method into a function means that in order to escape the `while` loop defined in `get` the runtime has to do dirty tricks which involve throwing the above exception.
## What changes were proposed in this pull request?
Instead of using `return` (which is generally not recommended in Scala), we place the result of the `fetchData` method inside a local variable and use a boolean flag to indicate the status of fetching data, which we monitor as our predicate to the `while` loop.
## How was this patch tested?
I've ran the `KafkaSourceSuite` to make sure regression passes. Since the exception isn't visible from user code, there is no way (at least that I could think of) to add this as a test to the existing suite.
Author: Yuval Itzchakov <yuval.itzchakov@clicktale.com>
Closes#19059 from YuvalItzchakov/master.
## What changes were proposed in this pull request?
All streaming logical plans will now have isStreaming set. This involved adding isStreaming as a case class arg in a few cases, since a node might be logically streaming depending on where it came from.
## How was this patch tested?
Existing unit tests - no functional change is intended in this PR.
Author: Jose Torres <joseph-torres@databricks.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#18973 from joseph-torres/SPARK-21765.
## What changes were proposed in this pull request?
The previous PR(https://github.com/apache/spark/pull/19000) removed filter pushdown verification, This PR add them back.
## How was this patch tested?
manual tests
Author: Yuming Wang <wgyumg@gmail.com>
Closes#19002 from wangyum/SPARK-21790-follow-up.
## What changes were proposed in this pull request?
[SPARK-17701](https://github.com/apache/spark/pull/18600/files#diff-b9f96d092fb3fea76bcf75e016799678L77) removed `metadata` function, this PR removed the Docker-based Integration module that has been relevant to `SparkPlan.metadata`.
## How was this patch tested?
manual tests
Author: Yuming Wang <wgyumg@gmail.com>
Closes#19000 from wangyum/SPARK-21709.
This version fixes a few issues in the import order checker; it provides
better error messages, and detects more improper ordering (thus the need
to change a lot of files in this patch). The main fix is that it correctly
complains about the order of packages vs. classes.
As part of the above, I moved some "SparkSession" import in ML examples
inside the "$example on$" blocks; that didn't seem consistent across
different source files to start with, and avoids having to add more on/off blocks
around specific imports.
The new scalastyle also seems to have a better header detector, so a few
license headers had to be updated to match the expected indentation.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#18943 from vanzin/SPARK-21731.
## What changes were proposed in this pull request?
This pr updated `lz4-java` to the latest (v1.4.0) and removed custom `LZ4BlockInputStream`. We currently use custom `LZ4BlockInputStream` to read concatenated byte stream in shuffle. But, this functionality has been implemented in the latest lz4-java (https://github.com/lz4/lz4-java/pull/105). So, we might update the latest to remove the custom `LZ4BlockInputStream`.
Major diffs between the latest release and v1.3.0 in the master are as follows (62f7547abb...6d4693f562);
- fixed NPE in XXHashFactory similarly
- Don't place resources in default package to support shading
- Fixes ByteBuffer methods failing to apply arrayOffset() for array-backed
- Try to load lz4-java from java.library.path, then fallback to bundled
- Add ppc64le binary
- Add s390x JNI binding
- Add basic LZ4 Frame v1.5.0 support
- enable aarch64 support for lz4-java
- Allow unsafeInstance() for ppc64le archiecture
- Add unsafeInstance support for AArch64
- Support 64-bit JNI build on Solaris
- Avoid over-allocating a buffer
- Allow EndMark to be incompressible for LZ4FrameInputStream.
- Concat byte stream
## How was this patch tested?
Existing tests.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#18883 from maropu/SPARK-21276.
## What changes were proposed in this pull request?
The examples and docs for Spark-Kinesis integrations use the deprecated KinesisUtils. We should update the docs to use the KinesisInputDStream builder to create DStreams.
## How was this patch tested?
The patch primarily updates the documents. The patch will also need to make changes to the Spark-Kinesis examples. The examples need to be tested.
Author: Yash Sharma <ysharma@atlassian.com>
Closes#18071 from yssharma/ysharma/kinesis_docs.
## What changes were proposed in this pull request?
Currently spark-streaming-kafka-0-10 has a dependency on the full kafka distribution (but only uses and requires the kafka-clients library).
The PR fixes that (the library only depends on kafka-clients), and the tests depend on the full kafka.
## How was this patch tested?
All existing tests still pass.
Author: Tim Van Wassenhove <github@timvw.be>
Closes#18353 from timvw/master.
## What changes were proposed in this pull request?
Address scapegoat warnings for:
- BigDecimal double constructor
- Catching NPE
- Finalizer without super
- List.size is O(n)
- Prefer Seq.empty
- Prefer Set.empty
- reverse.map instead of reverseMap
- Type shadowing
- Unnecessary if condition.
- Use .log1p
- Var could be val
In some instances like Seq.empty, I avoided making the change even where valid in test code to keep the scope of the change smaller. Those issues are concerned with performance and it won't matter for tests.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#18635 from srowen/Scapegoat1.
## What changes were proposed in this pull request?
- Remove Scala 2.10 build profiles and support
- Replace some 2.10 support in scripts with commented placeholders for 2.12 later
- Remove deprecated API calls from 2.10 support
- Remove usages of deprecated context bounds where possible
- Remove Scala 2.10 workarounds like ScalaReflectionLock
- Other minor Scala warning fixes
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#17150 from srowen/SPARK-19810.
## What changes were proposed in this pull request?
Move `compileValue` method in JDBCRDD to JdbcDialect, and override the `compileValue` method in OracleDialect to rewrite the Oracle-specific timestamp and date literals in where clause.
## How was this patch tested?
An integration test has been added.
Author: Rui Zha <zrdt713@gmail.com>
Author: Zharui <zrdt713@gmail.com>
Closes#18451 from SharpRay/extend-compileValue-to-dialects.
## What changes were proposed in this pull request?
This PR is to revert some code changes in the read path of https://github.com/apache/spark/pull/14377. The original fix is https://github.com/apache/spark/pull/17830
When merging this PR, please give the credit to gaborfeher
## How was this patch tested?
Added a test case to OracleIntegrationSuite.scala
Author: Gabor Feher <gabor.feher@lynxanalytics.com>
Author: gatorsmile <gatorsmile@gmail.com>
Closes#18408 from gatorsmile/OracleType.
This patch adds DB2 specific data type mappings for decfloat, real, xml , and timestamp with time zone (DB2Z specific type) types on read and for byte, short data types on write to the to jdbc data source DB2 dialect. Default mapping does not work for these types when reading/writing from DB2 database.
Added docker test, and a JDBC unit test case.
Author: sureshthalamati <suresh.thalamati@gmail.com>
Closes#9162 from sureshthalamati/db2dialect_enhancements-spark-10655.
## What changes were proposed in this pull request?
Add a new property `spark.streaming.kafka.consumer.cache.enabled` that allows users to enable or disable the cache for Kafka consumers. This property can be especially handy in cases where issues like SPARK-19185 get hit, for which there isn't a solution committed yet. By default, the cache is still on, so this change doesn't change any out-of-box behavior.
## How was this patch tested?
Running unit tests
Author: Mark Grover <mark@apache.org>
Author: Mark Grover <grover.markgrover@gmail.com>
Closes#18234 from markgrover/spark-19185.
## What changes were proposed in this pull request?
Currently the `DataFrameWriter` operations have several problems:
1. non-file-format data source writing action doesn't show up in the SQL tab in Spark UI
2. file-format data source writing action shows a scan node in the SQL tab, without saying anything about writing. (streaming also have this issue, but not fixed in this PR)
3. Spark SQL CLI actions don't show up in the SQL tab.
This PR fixes all of them, by refactoring the `ExecuteCommandExec` to make it have children.
close https://github.com/apache/spark/pull/17540
## How was this patch tested?
existing tests.
Also test the UI manually. For a simple command: `Seq(1 -> "a").toDF("i", "j").write.parquet("/tmp/qwe")`
before this PR:
<img width="266" alt="qq20170523-035840 2x" src="https://cloud.githubusercontent.com/assets/3182036/26326050/24e18ba2-3f6c-11e7-8817-6dd275bf6ac5.png">
after this PR:
<img width="287" alt="qq20170523-035708 2x" src="https://cloud.githubusercontent.com/assets/3182036/26326054/2ad7f460-3f6c-11e7-8053-d68325beb28f.png">
Author: Wenchen Fan <wenchen@databricks.com>
Closes#18064 from cloud-fan/execution.
## What changes were proposed in this pull request?
In summary, cost of recreating a KafkaProducer for writing every batch is high as it starts a lot threads and make connections and then closes them. A KafkaProducer instance is promised to be thread safe in Kafka docs. Reuse of KafkaProducer instance while writing via multiple threads is encouraged.
Furthermore, I have performance improvement of 10x in latency, with this patch.
### These are times that addBatch took in ms. Without applying this patch
### These are times that addBatch took in ms. After applying this patch
## How was this patch tested?
Running distributed benchmarks comparing runs with this patch and without it.
Added relevant unit tests.
Author: Prashant Sharma <prashsh1@in.ibm.com>
Closes#17308 from ScrapCodes/cached-kafka-producer.
## What changes were proposed in this pull request?
Add `ThreadUtils.awaitReady` similar to `ThreadUtils.awaitResult` and disallow `Await.ready`.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#17763 from zsxwing/awaitready.
## What changes were proposed in this pull request?
The pull requests proposes to remove the hardcoded values for Amazon Kinesis - MIN_RETRY_WAIT_TIME_MS, MAX_RETRIES.
This change is critical for kinesis checkpoint recovery when the kinesis backed rdd is huge.
Following happens in a typical kinesis recovery :
- kinesis throttles large number of requests while recovering
- retries in case of throttling are not able to recover due to the small wait period
- kinesis throttles per second, the wait period should be configurable for recovery
The patch picks the spark kinesis configs from:
- spark.streaming.kinesis.retry.wait.time
- spark.streaming.kinesis.retry.max.attempts
Jira : https://issues.apache.org/jira/browse/SPARK-20140
## How was this patch tested?
Modified the KinesisBackedBlockRDDSuite.scala to run kinesis tests with the modified configurations. Wasn't able to test the patch with actual throttling.
Author: Yash Sharma <ysharma@atlassian.com>
Closes#17467 from yssharma/ysharma/spark-kinesis-retries.
## What changes were proposed in this pull request?
This PR proposes to fix the lint-breaks as below:
```
[ERROR] src/main/java/org/apache/spark/unsafe/Platform.java:[51] (regexp) RegexpSingleline: No trailing whitespace allowed.
[ERROR] src/main/scala/org/apache/spark/sql/streaming/Trigger.java:[45,25] (naming) MethodName: Method name 'ProcessingTime' must match pattern '^[a-z][a-z0-9][a-zA-Z0-9_]*$'.
[ERROR] src/main/scala/org/apache/spark/sql/streaming/Trigger.java:[62,25] (naming) MethodName: Method name 'ProcessingTime' must match pattern '^[a-z][a-z0-9][a-zA-Z0-9_]*$'.
[ERROR] src/main/scala/org/apache/spark/sql/streaming/Trigger.java:[78,25] (naming) MethodName: Method name 'ProcessingTime' must match pattern '^[a-z][a-z0-9][a-zA-Z0-9_]*$'.
[ERROR] src/main/scala/org/apache/spark/sql/streaming/Trigger.java:[92,25] (naming) MethodName: Method name 'ProcessingTime' must match pattern '^[a-z][a-z0-9][a-zA-Z0-9_]*$'.
[ERROR] src/main/scala/org/apache/spark/sql/streaming/Trigger.java:[102,25] (naming) MethodName: Method name 'Once' must match pattern '^[a-z][a-z0-9][a-zA-Z0-9_]*$'.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisInputDStreamBuilderSuite.java:[28,8] (imports) UnusedImports: Unused import - org.apache.spark.streaming.api.java.JavaDStream.
```
after:
```
dev/lint-java
Checkstyle checks passed.
```
[Test Result](https://travis-ci.org/ConeyLiu/spark/jobs/229666169)
## How was this patch tested?
Travis CI
Author: Xianyang Liu <xianyang.liu@intel.com>
Closes#17890 from ConeyLiu/codestyle.
### What changes were proposed in this pull request?
This PR is to support JDBC data type TIME WITH TIME ZONE. It can be converted to TIMESTAMP
In addition, before this PR, for unsupported data types, we simply output the type number instead of the type name.
```
java.sql.SQLException: Unsupported type 2014
```
After this PR, the message is like
```
java.sql.SQLException: Unsupported type TIMESTAMP_WITH_TIMEZONE
```
- Also upgrade the H2 version to `1.4.195` which has the type fix for "TIMESTAMP WITH TIMEZONE". However, it is not fully supported. Thus, we capture the exception, but we still need it to partially test the support of "TIMESTAMP WITH TIMEZONE", because Docker tests are not regularly run.
### How was this patch tested?
Added test cases.
Author: Xiao Li <gatorsmile@gmail.com>
Closes#17835 from gatorsmile/h2.
## What changes were proposed in this pull request?
SparkSQL can now read from a database table with column type [TIMESTAMP WITH TIME ZONE](https://docs.oracle.com/javase/8/docs/api/java/sql/Types.html#TIMESTAMP_WITH_TIMEZONE).
## How was this patch tested?
Tested against Oracle database.
JoshRosen, you seem to know the class, would you look at this? Thanks!
Author: Jannik Arndt <jannik@jannikarndt.de>
Closes#17832 from JannikArndt/spark-20557-timestamp-with-timezone.
## What changes were proposed in this pull request?
I checked the logs of https://amplab.cs.berkeley.edu/jenkins/job/spark-branch-2.2-test-maven-hadoop-2.7/47/ and found it took several seconds to create Kafka internal topic `__consumer_offsets`. As Kafka creates this topic lazily, the topic creation happens in the first test `deserialization of initial offset with Spark 2.1.0` and causes it timeout.
This PR changes `offsets.topic.num.partitions` from the default value 50 to 1 to make creating `__consumer_offsets` (50 partitions -> 1 partition) much faster.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#17863 from zsxwing/fix-kafka-flaky-test.
## What changes were proposed in this pull request?
We didn't enforce analyzed plans in Spark 2.1 when writing out to Kafka.
## How was this patch tested?
New unit test.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Bill Chambers <bill@databricks.com>
Closes#17804 from anabranch/SPARK-20496-2.
## What changes were proposed in this pull request?
Cancel a batch Kafka query but one of task cannot be cancelled, and rerun the same DataFrame may cause ConcurrentModificationException because it may launch two tasks sharing the same group id.
This PR always create a new consumer when `reuseKafkaConsumer = false` to avoid ConcurrentModificationException. It also contains other minor fixes.
## How was this patch tested?
Jenkins.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#17752 from zsxwing/kafka-fix.
## What changes were proposed in this pull request?
This PR changes Executor's threads to `UninterruptibleThread` so that we can use `runUninterruptibly` in `CachedKafkaConsumer`. However, this is just best effort to avoid hanging forever. If the user uses`CachedKafkaConsumer` in another thread (e.g., create a new thread or Future), the potential hang may still happen.
## How was this patch tested?
The new added test.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#17761 from zsxwing/int.
## What changes were proposed in this pull request?
The spark-kinesis testcases use the KinesisUtils.createStream which are deprecated now. Modify the testcases to use the recommended KinesisInputDStream.builder instead.
This change will also enable the testcases to automatically use the session tokens automatically.
## How was this patch tested?
All the existing testcases work fine as expected with the changes.
https://issues.apache.org/jira/browse/SPARK-20189
Author: Yash Sharma <ysharma@atlassian.com>
Closes#17506 from yssharma/ysharma/cleanup_kinesis_testcases.
## What changes were proposed in this pull request?
Add Locale.ROOT to internal calls to String `toLowerCase`, `toUpperCase`, to avoid inadvertent locale-sensitive variation in behavior (aka the "Turkish locale problem").
The change looks large but it is just adding `Locale.ROOT` (the locale with no country or language specified) to every call to these methods.
## How was this patch tested?
Existing tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#17527 from srowen/SPARK-20156.
## What changes were proposed in this pull request?
For large trigger intervals (e.g. 10 minutes), if a batch takes 11 minutes, then it will wait for 9 mins before starting the next batch. This does not make sense. The processing time based trigger policy should be to do process batches as fast as possible, but no faster than 1 in every trigger interval. If batches are taking longer than trigger interval anyways, then no point waiting extra trigger interval.
In this PR, I modified the ProcessingTimeExecutor to do so. Another minor change I did was to extract our StreamManualClock into a separate class so that it can be used outside subclasses of StreamTest. For example, ProcessingTimeExecutorSuite does not need to create any context for testing, just needs the StreamManualClock.
## How was this patch tested?
Added new unit tests to comprehensively test this behavior.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#17525 from tdas/SPARK-20209.
## What changes were proposed in this pull request?
- Add new KinesisDStream.scala containing KinesisDStream.Builder class
- Add KinesisDStreamBuilderSuite test suite
- Make KinesisInputDStream ctor args package private for testing
- Add JavaKinesisDStreamBuilderSuite test suite
- Add args to KinesisInputDStream and KinesisReceiver for optional
service-specific auth (Kinesis, DynamoDB and CloudWatch)
## How was this patch tested?
Added ```KinesisDStreamBuilderSuite``` to verify builder class works as expected
Author: Adam Budde <budde@amazon.com>
Closes#17250 from budde/KinesisStreamBuilder.
## What changes were proposed in this pull request?
An additional trigger and trigger executor that will execute a single trigger only. One can use this OneTime trigger to have more control over the scheduling of triggers.
In addition, this patch requires an optimization to StreamExecution that logs a commit record at the end of successfully processing a batch. This new commit log will be used to determine the next batch (offsets) to process after a restart, instead of using the offset log itself to determine what batch to process next after restart; using the offset log to determine this would process the previously logged batch, always, thus not permitting a OneTime trigger feature.
## How was this patch tested?
A number of existing tests have been revised. These tests all assumed that when restarting a stream, the last batch in the offset log is to be re-processed. Given that we now have a commit log that will tell us if that last batch was processed successfully, the results/assumptions of those tests needed to be revised accordingly.
In addition, a OneTime trigger test was added to StreamingQuerySuite, which tests:
- The semantics of OneTime trigger (i.e., on start, execute a single batch, then stop).
- The case when the commit log was not able to successfully log the completion of a batch before restart, which would mean that we should fall back to what's in the offset log.
- A OneTime trigger execution that results in an exception being thrown.
marmbrus tdas zsxwing
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Tyson Condie <tcondie@gmail.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#17219 from tcondie/stream-commit.
## Problem
There are several places where we write out version identifiers in various logs for structured streaming (usually `v1`). However, in the places where we check for this, we throw a confusing error message.
## What changes were proposed in this pull request?
This patch made two major changes:
1. added a `parseVersion(...)` method, and based on this method, fixed the following places the way they did version checking (no other place needed to do this checking):
```
HDFSMetadataLog
- CompactibleFileStreamLog ------------> fixed with this patch
- FileStreamSourceLog ---------------> inherited the fix of `CompactibleFileStreamLog`
- FileStreamSinkLog -----------------> inherited the fix of `CompactibleFileStreamLog`
- OffsetSeqLog ------------------------> fixed with this patch
- anonymous subclass in KafkaSource ---> fixed with this patch
```
2. changed the type of `FileStreamSinkLog.VERSION`, `FileStreamSourceLog.VERSION` etc. from `String` to `Int`, so that we can identify newer versions via `version > 1` instead of `version != "v1"`
- note this didn't break any backwards compatibility -- we are still writing out `"v1"` and reading back `"v1"`
## Exception message with this patch
```
java.lang.IllegalStateException: Failed to read log file /private/var/folders/nn/82rmvkk568sd8p3p8tb33trw0000gn/T/spark-86867b65-0069-4ef1-b0eb-d8bd258ff5b8/0. UnsupportedLogVersion: maximum supported log version is v1, but encountered v99. The log file was produced by a newer version of Spark and cannot be read by this version. Please upgrade.
at org.apache.spark.sql.execution.streaming.HDFSMetadataLog.get(HDFSMetadataLog.scala:202)
at org.apache.spark.sql.execution.streaming.OffsetSeqLogSuite$$anonfun$3$$anonfun$apply$mcV$sp$2.apply(OffsetSeqLogSuite.scala:78)
at org.apache.spark.sql.execution.streaming.OffsetSeqLogSuite$$anonfun$3$$anonfun$apply$mcV$sp$2.apply(OffsetSeqLogSuite.scala:75)
at org.apache.spark.sql.test.SQLTestUtils$class.withTempDir(SQLTestUtils.scala:133)
at org.apache.spark.sql.execution.streaming.OffsetSeqLogSuite.withTempDir(OffsetSeqLogSuite.scala:26)
at org.apache.spark.sql.execution.streaming.OffsetSeqLogSuite$$anonfun$3.apply$mcV$sp(OffsetSeqLogSuite.scala:75)
at org.apache.spark.sql.execution.streaming.OffsetSeqLogSuite$$anonfun$3.apply(OffsetSeqLogSuite.scala:75)
at org.apache.spark.sql.execution.streaming.OffsetSeqLogSuite$$anonfun$3.apply(OffsetSeqLogSuite.scala:75)
at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
```
## How was this patch tested?
unit tests
Author: Liwei Lin <lwlin7@gmail.com>
Closes#17070 from lw-lin/better-msg.
When using the KafkaSource with Structured Streaming, consumer assignments are not what the user expects if startingOffsets is set to an explicit set of topics/partitions in JSON where the topic(s) happen to have uppercase characters. When StartingOffsets is constructed, the original string value from options is transformed toLowerCase to make matching on "earliest" and "latest" case insensitive. However, the toLowerCase JSON is passed to SpecificOffsets for the terminal condition, so topic names may not be what the user intended by the time assignments are made with the underlying KafkaConsumer.
KafkaSourceProvider.scala:
```
val startingOffsets = caseInsensitiveParams.get(STARTING_OFFSETS_OPTION_KEY).map(_.trim.toLowerCase) match {
case Some("latest") => LatestOffsets
case Some("earliest") => EarliestOffsets
case Some(json) => SpecificOffsets(JsonUtils.partitionOffsets(json))
case None => LatestOffsets
}
```
Thank cbowden for reporting.
Jenkins
Author: uncleGen <hustyugm@gmail.com>
Closes#17209 from uncleGen/SPARK-19853.
## What changes were proposed in this pull request?
Fix the `throw new IllegalStateException` if statement part.
## How is this patch tested
Regression test
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#17228 from brkyvz/kafka-cause-fix.
## What changes were proposed in this pull request?
Add a new Kafka Sink and Kafka Relation for writing streaming and batch queries, respectively, to Apache Kafka.
### Streaming Kafka Sink
- When addBatch is called
-- If batchId is great than the last written batch
--- Write batch to Kafka
---- Topic will be taken from the record, if present, or from a topic option, which overrides topic in record.
-- Else ignore
### Batch Kafka Sink
- KafkaSourceProvider will implement CreatableRelationProvider
- CreatableRelationProvider#createRelation will write the passed in Dataframe to a Kafka
- Topic will be taken from the record, if present, or from topic option, which overrides topic in record.
- Save modes Append and ErrorIfExist supported under identical semantics. Other save modes result in an AnalysisException
tdas zsxwing
## How was this patch tested?
### The following unit tests will be included
- write to stream with topic field: valid stream write with data that includes an existing topic in the schema
- write structured streaming aggregation w/o topic field, with default topic: valid stream write with data that does not include a topic field, but the configuration includes a default topic
- write data with bad schema: various cases of writing data that does not conform to a proper schema e.g., 1. no topic field or default topic, and 2. no value field
- write data with valid schema but wrong types: data with a complete schema but wrong types e.g., key and value types are integers.
- write to non-existing topic: write a stream to a topic that does not exist in Kafka, which has been configured to not auto-create topics.
- write batch to kafka: simple write batch to Kafka, which goes through the same code path as streaming scenario, so validity checks will not be redone here.
### Examples
```scala
// Structured Streaming
val writer = inputStringStream.map(s => s.get(0).toString.getBytes()).toDF("value")
.selectExpr("value as key", "value as value")
.writeStream
.format("kafka")
.option("checkpointLocation", checkpointDir)
.outputMode(OutputMode.Append)
.option("kafka.bootstrap.servers", brokerAddress)
.option("topic", topic)
.queryName("kafkaStream")
.start()
// Batch
val df = spark
.sparkContext
.parallelize(Seq("1", "2", "3", "4", "5"))
.map(v => (topic, v))
.toDF("topic", "value")
df.write
.format("kafka")
.option("kafka.bootstrap.servers",brokerAddress)
.option("topic", topic)
.save()
```
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Tyson Condie <tcondie@gmail.com>
Closes#17043 from tcondie/kafka-writer.
## What changes were proposed in this pull request?
added a limit to getRecords api call call in KinesisBackedBlockRdd. This helps reduce the amount of data returned by kinesis api call making the recovery considerably faster
As we are storing the `fromSeqNum` & `toSeqNum` in checkpoint metadata, we can also store the number of records. Which can later be used for api call.
## How was this patch tested?
The patch was manually tested
Apologies for any silly mistakes, opening first pull request
Author: Gaurav <gaurav@techtinium.com>
Closes#16842 from Gauravshah/kinesis_checkpoint_recovery_fix_2_1_0.
## What changes were proposed in this pull request?
This PR proposes to fix the lint-breaks as below:
```
[ERROR] src/test/java/org/apache/spark/network/TransportResponseHandlerSuite.java:[29,8] (imports) UnusedImports: Unused import - org.apache.spark.network.buffer.ManagedBuffer.
[ERROR] src/main/java/org/apache/spark/unsafe/types/UTF8String.java:[156,10] (modifier) ModifierOrder: 'Nonnull' annotation modifier does not precede non-annotation modifiers.
[ERROR] src/main/java/org/apache/spark/SparkFirehoseListener.java:[122] (sizes) LineLength: Line is longer than 100 characters (found 105).
[ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeExternalSorter.java:[164,78] (coding) OneStatementPerLine: Only one statement per line allowed.
[ERROR] src/test/java/test/org/apache/spark/JavaAPISuite.java:[1157] (sizes) LineLength: Line is longer than 100 characters (found 121).
[ERROR] src/test/java/org/apache/spark/streaming/JavaMapWithStateSuite.java:[149] (sizes) LineLength: Line is longer than 100 characters (found 113).
[ERROR] src/test/java/test/org/apache/spark/streaming/Java8APISuite.java:[146] (sizes) LineLength: Line is longer than 100 characters (found 122).
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[32,8] (imports) UnusedImports: Unused import - org.apache.spark.streaming.Time.
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[611] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/test/java/test/org/apache/spark/streaming/JavaAPISuite.java:[1317] (sizes) LineLength: Line is longer than 100 characters (found 102).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetAggregatorSuite.java:[91] (sizes) LineLength: Line is longer than 100 characters (found 102).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[113] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[164] (sizes) LineLength: Line is longer than 100 characters (found 110).
[ERROR] src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java:[212] (sizes) LineLength: Line is longer than 100 characters (found 114).
[ERROR] src/test/java/org/apache/spark/mllib/tree/JavaDecisionTreeSuite.java:[36] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/main/java/org/apache/spark/examples/streaming/JavaKinesisWordCountASL.java:[26,8] (imports) UnusedImports: Unused import - com.amazonaws.regions.RegionUtils.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java:[20,8] (imports) UnusedImports: Unused import - com.amazonaws.regions.RegionUtils.
[ERROR] src/test/java/org/apache/spark/streaming/kinesis/JavaKinesisStreamSuite.java:[94] (sizes) LineLength: Line is longer than 100 characters (found 103).
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java:[30,8] (imports) UnusedImports: Unused import - org.apache.spark.sql.api.java.UDF1.
[ERROR] src/main/java/org/apache/spark/examples/ml/JavaTokenizerExample.java:[72] (sizes) LineLength: Line is longer than 100 characters (found 104).
[ERROR] src/main/java/org/apache/spark/examples/mllib/JavaRankingMetricsExample.java:[121] (sizes) LineLength: Line is longer than 100 characters (found 101).
[ERROR] src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:[28,8] (imports) UnusedImports: Unused import - org.apache.spark.api.java.JavaRDD.
[ERROR] src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java:[29,8] (imports) UnusedImports: Unused import - org.apache.spark.api.java.JavaSparkContext.
```
## How was this patch tested?
Manually via
```bash
./dev/lint-java
```
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17072 from HyukjinKwon/java-lint.
- Add dependency on aws-java-sdk-sts
- Replace SerializableAWSCredentials with new SerializableCredentialsProvider interface
- Make KinesisReceiver take SerializableCredentialsProvider as argument and
pass credential provider to KCL
- Add new implementations of KinesisUtils.createStream() that take STS
arguments
- Make JavaKinesisStreamSuite test the entire KinesisUtils Java API
- Update KCL/AWS SDK dependencies to 1.7.x/1.11.x
## What changes were proposed in this pull request?
[JIRA link with detailed description.](https://issues.apache.org/jira/browse/SPARK-19405)
* Replace SerializableAWSCredentials with new SerializableKCLAuthProvider class that takes 5 optional config params for configuring AWS auth and returns the appropriate credential provider object
* Add new public createStream() APIs for specifying these parameters in KinesisUtils
## How was this patch tested?
* Manually tested using explicit keypair and instance profile to read data from Kinesis stream in separate account (difficult to write a test orchestrating creation and assumption of IAM roles across separate accounts)
* Expanded JavaKinesisStreamSuite to test the entire Java API in KinesisUtils
## License acknowledgement
This contribution is my original work and that I license the work to the project under the project’s open source license.
Author: Budde <budde@amazon.com>
Closes#16744 from budde/master.
## What changes were proposed in this pull request?
This PR proposes to fix new test failures on WIndows as below:
**Before**
```
KafkaRelationSuite:
- test late binding start offsets *** FAILED *** (7 seconds, 679 milliseconds)
Cause: java.nio.file.FileSystemException: C:\projects\spark\target\tmp\spark-4c4b0cd1-4cb7-4908-949d-1b0cc8addb50\topic-4-0\00000000000000000000.log -> C:\projects\spark\target\tmp\spark-4c4b0cd1-4cb7-4908-949d-1b0cc8addb50\topic-4-0\00000000000000000000.log.deleted: The process cannot access the file because it is being used by another process.
KafkaSourceSuite:
- deserialization of initial offset with Spark 2.1.0 *** FAILED *** (3 seconds, 542 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-97ef64fc-ae61-4ce3-ac59-287fd38bd824
- deserialization of initial offset written by Spark 2.1.0 *** FAILED *** (60 milliseconds)
java.nio.file.InvalidPathException: Illegal char <:> at index 2: /C:/projects/spark/external/kafka-0-10-sql/target/scala-2.11/test-classes/kafka-source-initial-offset-version-2.1.0.b
HiveDDLSuite:
- partitioned table should always put partition columns at the end of table schema *** FAILED *** (657 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-f1b83d09-850a-4bba-8e43-a2a28dfaa757;
DDLSuite:
- create a data source table without schema *** FAILED *** (94 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-a3f3c161-afae-4d6f-9182-e8642f77062b;
- SET LOCATION for managed table *** FAILED *** (219 milliseconds)
org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
Exchange SinglePartit
+- *HashAggregate(keys=[], functions=[partial_count(1)], output=[count#99367L])
+- *FileScan parquet default.tbl[] Batched: true, Format: Parquet, Location: InMemoryFileIndex[file:/C:projectsspark arget mpspark-15be2f2f-4ea9-4c47-bfee-1b7b49363033], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<>
- insert data to a data source table which has a not existed location should succeed *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-34987671-e8d1-4624-ba5b-db1012e1246b;
- insert into a data source table with no existed partition location should succeed *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4c6ccfbf-4091-4032-9fbc-3d40c58267d5;
- read data from a data source table which has a not existed location should succeed *** FAILED *** (0 milliseconds)
- read data from a data source table with no existed partition location should succeed *** FAILED *** (0 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-6af39e37-abd1-44e8-ac68-e2dfcf67a2f3;
InputOutputMetricsSuite:
- output metrics on records written *** FAILED *** (0 milliseconds)
java.lang.IllegalArgumentException: Wrong FS: file://C:\projects\spark\target\tmp\spark-cd69ee77-88f2-4202-bed6-19c0ee05ef55\InputOutputMetricsSuite, expected: file:///
- output metrics on records written - new Hadoop API *** FAILED *** (16 milliseconds)
java.lang.IllegalArgumentException: Wrong FS: file://C:\projects\spark\target\tmp\spark-b69e8fcb-047b-4de8-9cdf-5f026efb6762\InputOutputMetricsSuite, expected: file:///
```
**After**
```
KafkaRelationSuite:
- test late binding start offsets !!! CANCELED !!! (62 milliseconds)
KafkaSourceSuite:
- deserialization of initial offset with Spark 2.1.0 (5 seconds, 341 milliseconds)
- deserialization of initial offset written by Spark 2.1.0 (910 milliseconds)
HiveDDLSuite:
- partitioned table should always put partition columns at the end of table schema (2 seconds)
DDLSuite:
- create a data source table without schema (828 milliseconds)
- SET LOCATION for managed table (406 milliseconds)
- insert data to a data source table which has a not existed location should succeed (406 milliseconds)
- insert into a data source table with no existed partition location should succeed (453 milliseconds)
- read data from a data source table which has a not existed location should succeed (94 milliseconds)
- read data from a data source table with no existed partition location should succeed (265 milliseconds)
InputOutputMetricsSuite:
- output metrics on records written (172 milliseconds)
- output metrics on records written - new Hadoop API (297 milliseconds)
```
## How was this patch tested?
Fixed tests in `InputOutputMetricsSuite`, `KafkaRelationSuite`, `KafkaSourceSuite`, `DDLSuite.scala` and `HiveDDLSuite`.
Manually tested via AppVeyor as below:
`InputOutputMetricsSuite`: https://ci.appveyor.com/project/spark-test/spark/build/633-20170219-windows-test/job/ex8nvwa6tsh7rmto
`KafkaRelationSuite`: https://ci.appveyor.com/project/spark-test/spark/build/633-20170219-windows-test/job/h8dlcowew52y8ncw
`KafkaSourceSuite`: https://ci.appveyor.com/project/spark-test/spark/build/634-20170219-windows-test/job/9ybgjl7yeubxcre4
`DDLSuite`: https://ci.appveyor.com/project/spark-test/spark/build/635-20170219-windows-test
`HiveDDLSuite`: https://ci.appveyor.com/project/spark-test/spark/build/633-20170219-windows-test/job/up6o9n47er087ltb
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16999 from HyukjinKwon/windows-fix.
## What changes were proposed in this pull request?
Convert tests to use Java 8 lambdas, and modest related fixes to surrounding code.
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16964 from srowen/SPARK-19534.
## What changes were proposed in this pull request?
The streaming thread in StreamExecution uses the following ways to check if it should exit:
- Catch an InterruptException.
- `StreamExecution.state` is TERMINATED.
When starting and stopping a query quickly, the above two checks may both fail:
- Hit [HADOOP-14084](https://issues.apache.org/jira/browse/HADOOP-14084) and swallow InterruptException
- StreamExecution.stop is called before `state` becomes `ACTIVE`. Then [runBatches](dcc2d540a5/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/StreamExecution.scala (L252)) changes the state from `TERMINATED` to `ACTIVE`.
If the above cases both happen, the query will hang forever.
This PR changes `state` to `AtomicReference` and uses`compareAndSet` to make sure we only change the state from `INITIALIZING` to `ACTIVE`. It also removes the `runUninterruptibly` hack from ``HDFSMetadata`, because HADOOP-14084 won't cause any problem after we fix the race condition.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16947 from zsxwing/SPARK-19617.
## What changes were proposed in this pull request?
This patch fixes a bug in `KafkaSource` with the (de)serialization of the length of the JSON string that contains the initial partition offsets.
## How was this patch tested?
I ran the test suite for spark-sql-kafka-0-10.
Author: Roberto Agostino Vitillo <ra.vitillo@gmail.com>
Closes#16857 from vitillo/kafka_source_fix.
- Move external/java8-tests tests into core, streaming, sql and remove
- Remove MaxPermGen and related options
- Fix some reflection / TODOs around Java 8+ methods
- Update doc references to 1.7/1.8 differences
- Remove Java 7/8 related build profiles
- Update some plugins for better Java 8 compatibility
- Fix a few Java-related warnings
For the future:
- Update Java 8 examples to fully use Java 8
- Update Java tests to use lambdas for simplicity
- Update Java internal implementations to use lambdas
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#16871 from srowen/SPARK-19493.
## What changes were proposed in this pull request?
The reason for test failure is that the property “oracle.jdbc.mapDateToTimestamp” set by the test was getting converted into all lower case. Oracle database expects this property in case-sensitive manner.
This test was passing in previous releases because connection properties were sent as user specified for the test case scenario. Fixes to handle all option uniformly in case-insensitive manner, converted the JDBC connection properties also to lower case.
This PR enhances CaseInsensitiveMap to keep track of input case-sensitive keys , and uses those when creating connection properties that are passed to the JDBC connection.
Alternative approach PR https://github.com/apache/spark/pull/16847 is to pass original input keys to JDBC data source by adding check in the Data source class and handle case-insensitivity in the JDBC source code.
## How was this patch tested?
Added new test cases to JdbcSuite , and OracleIntegrationSuite. Ran docker integration tests passed on my laptop, all tests passed successfully.
Author: sureshthalamati <suresh.thalamati@gmail.com>
Closes#16891 from sureshthalamati/jdbc_case_senstivity_props_fix-SPARK-19318.
## What changes were proposed in this pull request?
In `KafkaOffsetReader`, when error occurs, we abort the existing consumer and create a new consumer. In our current implementation, the first consumer and the second consumer would be in the same group (which leads to SPARK-19559), **_violating our intention of the two consumers not being in the same group._**
The cause is that, in our current implementation, the first consumer is created before `groupId` and `nextId` are initialized in the constructor. Then even if `groupId` and `nextId` are increased during the creation of that first consumer, `groupId` and `nextId` would still be initialized to default values in the constructor for the second consumer.
We should make sure that `groupId` and `nextId` are initialized before any consumer is created.
## How was this patch tested?
Ran 100 times of `KafkaSourceSuite`; all passed
Author: Liwei Lin <lwlin7@gmail.com>
Closes#16902 from lw-lin/SPARK-19564-.
## What changes were proposed in this pull request?
Today, you can start a stream that reads from kafka. However, given kafka's configurable retention period, it seems like sometimes you might just want to read all of the data that is available now. As such we should add a version that works with spark.read as well.
The options should be the same as the streaming kafka source, with the following differences:
startingOffsets should default to earliest, and should not allow latest (which would always be empty).
endingOffsets should also be allowed and should default to latest. the same assign json format as startingOffsets should also be accepted.
It would be really good, if things like .limit(n) were enough to prevent all the data from being read (this might just work).
## How was this patch tested?
KafkaRelationSuite was added for testing batch queries via KafkaUtils.
Author: Tyson Condie <tcondie@gmail.com>
Closes#16686 from tcondie/SPARK-18682.
## What changes were proposed in this pull request?
This pr is to fix an issue occurred when resharding Kinesis streams; the resharding makes the KCL throw an exception because Spark does not checkpoint `SHARD_END` when finishing reading closed shards in `KinesisRecordProcessor#shutdown`. This bug finally leads to stopping subscribing new split (or merged) shards.
## How was this patch tested?
Added a test in `KinesisStreamSuite` to check if it works well when splitting/merging shards.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#16213 from maropu/SPARK-18020.
## What changes were proposed in this pull request?
JDBC read is failing with NPE due to missing null value check for array data type if the source table has null values in the array type column. For null values Resultset.getArray() returns null.
This PR adds null safe check to the Resultset.getArray() value before invoking method on the Array object.
## How was this patch tested?
Updated the PostgresIntegration test suite to test null values. Ran docker integration tests on my laptop.
Author: sureshthalamati <suresh.thalamati@gmail.com>
Closes#15192 from sureshthalamati/jdbc_array_null_fix-SPARK-14536.
## What changes were proposed in this pull request?
remove ununsed imports and outdated comments, and fix some minor code style issue.
## How was this patch tested?
existing ut
Author: uncleGen <hustyugm@gmail.com>
Closes#16591 from uncleGen/SPARK-19227.
## What changes were proposed in this pull request?
Fix outdated parameter descriptions in kafka010
## How was this patch tested?
cc koeninger zsxwing
Author: uncleGen <hustyugm@gmail.com>
Closes#16569 from uncleGen/SPARK-19206.
## What changes were proposed in this pull request?
This PR proposes to fix all the test failures identified by testing with AppVeyor.
**Scala - aborted tests**
```
WindowQuerySuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.execution.WindowQuerySuite *** ABORTED *** (156 milliseconds)
org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive argetscala-2.11 est-classesdatafilespart_tiny.txt;
OrcSourceSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.orc.OrcSourceSuite *** ABORTED *** (62 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
ParquetMetastoreSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetMetastoreSuite *** ABORTED *** (4 seconds, 703 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
ParquetSourceSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetSourceSuite *** ABORTED *** (3 seconds, 907 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-581a6575-454f-4f21-a516-a07f95266143;
KafkaRDDSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaRDDSuite *** ABORTED *** (5 seconds, 212 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-4722304d-213e-4296-b556-951df1a46807
DirectKafkaStreamSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.DirectKafkaStreamSuite *** ABORTED *** (7 seconds, 127 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d0d3eba7-4215-4e10-b40e-bb797e89338e
at org.apache.spark.util.Utils$.deleteRecursively(Utils.scala:1010)
ReliableKafkaStreamSuite
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.ReliableKafkaStreamSuite *** ABORTED *** (5 seconds, 498 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d33e45a0-287e-4bed-acae-ca809a89d888
KafkaStreamSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaStreamSuite *** ABORTED *** (2 seconds, 892 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-59c9d169-5a56-4519-9ef0-cefdbd3f2e6c
KafkaClusterSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaClusterSuite *** ABORTED *** (1 second, 690 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-3ef402b0-8689-4a60-85ae-e41e274f179d
DirectKafkaStreamSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.DirectKafkaStreamSuite *** ABORTED *** (59 seconds, 626 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-426107da-68cf-4d94-b0d6-1f428f1c53f6
KafkaRDDSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.KafkaRDDSuite *** ABORTED *** (2 minutes, 6 seconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-b9ce7929-5dae-46ab-a0c4-9ef6f58fbc2
```
**Java - failed tests**
```
Test org.apache.spark.streaming.kafka.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-1cee32f4-4390-4321-82c9-e8616b3f0fb0, took 9.61 sec
Test org.apache.spark.streaming.kafka.JavaKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-f42695dd-242e-4b07-847c-f299b8e4676e, took 11.797 sec
Test org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-85c0d062-78cf-459c-a2dd-7973572101ce, took 1.581 sec
Test org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-49eb6b5c-8366-47a6-83f2-80c443c48280, took 17.895 sec
org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-898cf826-d636-4b1c-a61a-c12a364c02e7, took 8.858 sec
```
**Scala - failed tests**
```
PartitionProviderCompatibilitySuite:
- insert overwrite partition of new datasource table overwrites just partition *** FAILED *** (828 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-bb6337b9-4f99-45ab-ad2c-a787ab965c09
- SPARK-18635 special chars in partition values - partition management true *** FAILED *** (5 seconds, 360 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- SPARK-18635 special chars in partition values - partition management false *** FAILED *** (141 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```
```
UtilsSuite:
- reading offset bytes of a file (compressed) *** FAILED *** (0 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-ecb2b7d5-db8b-43a7-b268-1bf242b5a491
- reading offset bytes across multiple files (compressed) *** FAILED *** (0 milliseconds)
java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-25cc47a8-1faa-4da5-8862-cf174df63ce0
```
```
StatisticsSuite:
- MetastoreRelations fallback to HDFS for size estimation *** FAILED *** (110 milliseconds)
org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'csv_table' not found in database 'default';
```
```
SQLQuerySuite:
- permanent UDTF *** FAILED *** (125 milliseconds)
org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count_temp'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 24
- describe functions - user defined functions *** FAILED *** (125 milliseconds)
org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 7
- CTAS without serde with location *** FAILED *** (16 milliseconds)
java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-ed673d73-edfc-404e-829e-2e2b9725d94e/c1
- derived from Hive query file: drop_database_removes_partition_dirs.q *** FAILED *** (47 milliseconds)
java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_database_removes_partition_dirs_table
- derived from Hive query file: drop_table_removes_partition_dirs.q *** FAILED *** (0 milliseconds)
java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_table_removes_partition_dirs_table2
- SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH *** FAILED *** (109 milliseconds)
java.nio.file.InvalidPathException: Illegal char <:> at index 2: /C:/projects/spark/sql/hive/projectsspark arget mpspark-1a122f8c-dfb3-46c4-bab1-f30764baee0e/*part-r*
```
```
HiveDDLSuite:
- drop external tables in default database *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- add/drop partitions - external table *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- create/drop database - location without pre-created directory *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- create/drop database - location with pre-created directory *** FAILED *** (32 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- drop database containing tables - CASCADE *** FAILED *** (94 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- drop an empty database - CASCADE *** FAILED *** (63 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- drop database containing tables - RESTRICT *** FAILED *** (47 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- drop an empty database - RESTRICT *** FAILED *** (47 milliseconds)
CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)
- CREATE TABLE LIKE an external data source table *** FAILED *** (140 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-c5eba16d-07ae-4186-95bb-21c5811cf888;
- CREATE TABLE LIKE an external Hive serde table *** FAILED *** (16 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- desc table for data source table - no user-defined schema *** FAILED *** (125 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-e8bf5bf5-721a-4cbe-9d6 at scala.collection.immutable.List.foreach(List.scala:381)d-5543a8301c1d;
```
```
MetastoreDataSourcesSuite
- CTAS: persisted bucketed data source table *** FAILED *** (16 milliseconds)
java.lang.IllegalArgumentException: Can not create a Path from an empty string
```
```
ShowCreateTableSuite:
- simple external hive table *** FAILED *** (0 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```
```
PartitionedTablePerfStatsSuite:
- hive table: partitioned pruned table reports only selected files *** FAILED *** (313 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: partitioned pruned table reports only selected files *** FAILED *** (219 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-311f45f8-d064-4023-a4bb-e28235bff64d;
- hive table: lazy partition pruning reads only necessary partition data *** FAILED *** (203 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: lazy partition pruning reads only necessary partition data *** FAILED *** (187 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-fde874ca-66bd-4d0b-a40f-a043b65bf957;
- hive table: lazy partition pruning with file status caching enabled *** FAILED *** (188 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: lazy partition pruning with file status caching enabled *** FAILED *** (187 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-e6d20183-dd68-4145-acbe-4a509849accd;
- hive table: file status caching respects refresh table and refreshByPath *** FAILED *** (172 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: file status caching respects refresh table and refreshByPath *** FAILED *** (203 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-8b2c9651-2adf-4d58-874f-659007e21463;
- hive table: file status cache respects size limit *** FAILED *** (219 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: file status cache respects size limit *** FAILED *** (171 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-7835ab57-cb48-4d2c-bb1d-b46d5a4c47e4;
- datasource table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-20598d76-c004-42a7-8061-6c56f0eda5e2;
- hive table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- hive table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 281 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 422 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4cfed321-4d1d-4b48-8d34-5c169afff383;
- hive table: files read and cached when filesource partition management is off *** FAILED *** (234 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
- datasource table: all partition data cached in memory when partition management is off *** FAILED *** (203 milliseconds)
org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4bcc0398-15c9-4f6a-811e-12d40f3eec12;
- SPARK-18700: table loaded only once even when resolved concurrently *** FAILED *** (1 second, 266 milliseconds)
org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```
```
HiveSparkSubmitSuite:
- temporary Hive UDF: define a UDF and use it *** FAILED *** (2 seconds, 94 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- permanent Hive UDF: define a UDF and use it *** FAILED *** (281 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- permanent Hive UDF: use a already defined permanent function *** FAILED *** (718 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-8368: includes jars passed in through --jars *** FAILED *** (3 seconds, 521 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-8020: set sql conf in spark conf *** FAILED *** (0 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-8489: MissingRequirementError during reflection *** FAILED *** (94 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-9757 Persist Parquet relation with decimal column *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-11009 fix wrong result of Window function in cluster mode *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-14244 fix window partition size attribute binding failure *** FAILED *** (78 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- set spark.sql.warehouse.dir *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- set hive.metastore.warehouse.dir *** FAILED *** (15 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-16901: set javax.jdo.option.ConnectionURL *** FAILED *** (16 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
- SPARK-18360: default table path of tables in default database should depend on the location of default database *** FAILED *** (15 milliseconds)
java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
```
```
UtilsSuite:
- resolveURIs with multiple paths *** FAILED *** (0 milliseconds)
".../jar3,file:/C:/pi.py[%23]py.pi,file:/C:/path%..." did not equal ".../jar3,file:/C:/pi.py[#]py.pi,file:/C:/path%..." (UtilsSuite.scala:468)
```
```
CheckpointSuite:
- recovery with file input stream *** FAILED *** (10 seconds, 205 milliseconds)
The code passed to eventually never returned normally. Attempted 660 times over 10.014272499999999 seconds. Last failure message: Unexpected internal error near index 1
\
^. (CheckpointSuite.scala:680)
```
## How was this patch tested?
Manually via AppVeyor as below:
**Scala - aborted tests**
```
WindowQuerySuite - all passed
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
ParquetMetastoreSuite - all passed
ParquetSourceSuite - all passed
KafkaRDDSuite - all passed
DirectKafkaStreamSuite - all passed
ReliableKafkaStreamSuite - all passed
KafkaStreamSuite - all passed
KafkaClusterSuite - all passed
DirectKafkaStreamSuite - all passed
KafkaRDDSuite - all passed
```
**Java - failed tests**
```
org.apache.spark.streaming.kafka.JavaKafkaRDDSuite - all passed
org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka.JavaKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite - all passed
```
**Scala - failed tests**
```
PartitionProviderCompatibilitySuite:
- insert overwrite partition of new datasource table overwrites just partition (1 second, 953 milliseconds)
- SPARK-18635 special chars in partition values - partition management true (6 seconds, 31 milliseconds)
- SPARK-18635 special chars in partition values - partition management false (4 seconds, 578 milliseconds)
```
```
UtilsSuite:
- reading offset bytes of a file (compressed) (203 milliseconds)
- reading offset bytes across multiple files (compressed) (0 milliseconds)
```
```
StatisticsSuite:
- MetastoreRelations fallback to HDFS for size estimation (94 milliseconds)
```
```
SQLQuerySuite:
- permanent UDTF (407 milliseconds)
- describe functions - user defined functions (441 milliseconds)
- CTAS without serde with location (2 seconds, 831 milliseconds)
- derived from Hive query file: drop_database_removes_partition_dirs.q (734 milliseconds)
- derived from Hive query file: drop_table_removes_partition_dirs.q (563 milliseconds)
- SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH (453 milliseconds)
```
```
HiveDDLSuite:
- drop external tables in default database (3 seconds, 5 milliseconds)
- add/drop partitions - external table (2 seconds, 750 milliseconds)
- create/drop database - location without pre-created directory (500 milliseconds)
- create/drop database - location with pre-created directory (407 milliseconds)
- drop database containing tables - CASCADE (453 milliseconds)
- drop an empty database - CASCADE (375 milliseconds)
- drop database containing tables - RESTRICT (328 milliseconds)
- drop an empty database - RESTRICT (391 milliseconds)
- CREATE TABLE LIKE an external data source table (953 milliseconds)
- CREATE TABLE LIKE an external Hive serde table (3 seconds, 782 milliseconds)
- desc table for data source table - no user-defined schema (1 second, 150 milliseconds)
```
```
MetastoreDataSourcesSuite
- CTAS: persisted bucketed data source table (875 milliseconds)
```
```
ShowCreateTableSuite:
- simple external hive table (78 milliseconds)
```
```
PartitionedTablePerfStatsSuite:
- hive table: partitioned pruned table reports only selected files (1 second, 109 milliseconds)
- datasource table: partitioned pruned table reports only selected files (860 milliseconds)
- hive table: lazy partition pruning reads only necessary partition data (859 milliseconds)
- datasource table: lazy partition pruning reads only necessary partition data (1 second, 219 milliseconds)
- hive table: lazy partition pruning with file status caching enabled (875 milliseconds)
- datasource table: lazy partition pruning with file status caching enabled (890 milliseconds)
- hive table: file status caching respects refresh table and refreshByPath (922 milliseconds)
- datasource table: file status caching respects refresh table and refreshByPath (640 milliseconds)
- hive table: file status cache respects size limit (469 milliseconds)
- datasource table: file status cache respects size limit (453 milliseconds)
- datasource table: table setup does not scan filesystem (328 milliseconds)
- hive table: table setup does not scan filesystem (313 milliseconds)
- hive table: num hive client calls does not scale with partition count (5 seconds, 431 milliseconds)
- datasource table: num hive client calls does not scale with partition count (4 seconds, 79 milliseconds)
- hive table: files read and cached when filesource partition management is off (656 milliseconds)
- datasource table: all partition data cached in memory when partition management is off (484 milliseconds)
- SPARK-18700: table loaded only once even when resolved concurrently (2 seconds, 578 milliseconds)
```
```
HiveSparkSubmitSuite:
- temporary Hive UDF: define a UDF and use it (1 second, 745 milliseconds)
- permanent Hive UDF: define a UDF and use it (406 milliseconds)
- permanent Hive UDF: use a already defined permanent function (375 milliseconds)
- SPARK-8368: includes jars passed in through --jars (391 milliseconds)
- SPARK-8020: set sql conf in spark conf (156 milliseconds)
- SPARK-8489: MissingRequirementError during reflection (187 milliseconds)
- SPARK-9757 Persist Parquet relation with decimal column (157 milliseconds)
- SPARK-11009 fix wrong result of Window function in cluster mode (156 milliseconds)
- SPARK-14244 fix window partition size attribute binding failure (156 milliseconds)
- set spark.sql.warehouse.dir (172 milliseconds)
- set hive.metastore.warehouse.dir (156 milliseconds)
- SPARK-16901: set javax.jdo.option.ConnectionURL (157 milliseconds)
- SPARK-18360: default table path of tables in default database should depend on the location of default database (172 milliseconds)
```
```
UtilsSuite:
- resolveURIs with multiple paths (0 milliseconds)
```
```
CheckpointSuite:
- recovery with file input stream (4 seconds, 452 milliseconds)
```
Note: after resolving the aborted tests, there is a test failure identified as below:
```
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
```
This does not look due to this problem so this PR does not fix it here.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16451 from HyukjinKwon/all-path-resource-fixes.
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.
## How was this patch tested?
N/A since only docs or comments were updated.
Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>
Closes#16455 from neurons/np.structure_streaming_doc.
Remove spark-tag's compile-scope dependency (and, indirectly, spark-core's compile-scope transitive-dependency) on scalatest by splitting test-oriented tags into spark-tags' test JAR.
Alternative to #16303.
Author: Ryan Williams <ryan.blake.williams@gmail.com>
Closes#16311 from ryan-williams/tt.
## What changes were proposed in this pull request?
When KafkaSource fails on Kafka errors, we should create a new consumer to retry rather than using the existing broken one because it's possible that the broken one will fail again.
This PR also assigns a new group id to the new created consumer for a possible race condition: the broken consumer cannot talk with the Kafka cluster in `close` but the new consumer can talk to Kafka cluster. I'm not sure if this will happen or not. Just for safety to avoid that the Kafka cluster thinks there are two consumers with the same group id in a short time window. (Note: CachedKafkaConsumer doesn't need this fix since `assign` never uses the group id.)
## How was this patch tested?
In https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/70370/console , it ran this flaky test 120 times and all passed.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16282 from zsxwing/kafka-fix.
## What changes were proposed in this pull request?
Disable KafkaSourceStressForDontFailOnDataLossSuite for now.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16275 from zsxwing/ignore-flaky-test.
## What changes were proposed in this pull request?
This pr is to make input rates in timeline more flat for spark streaming + kinesis.
Since kinesis workers fetch records and push them into block generators in bulk, timeline in web UI has many spikes when `maxRates` applied (See a Figure.1 below). This fix splits fetched input records into multiple `adRecords` calls.
Figure.1 Apply `maxRates=500` in vanilla Spark
<img width="1084" alt="apply_limit in_vanilla_spark" src="https://cloud.githubusercontent.com/assets/692303/20823861/4602f300-b89b-11e6-95f3-164a37061305.png">
Figure.2 Apply `maxRates=500` in Spark with my patch
<img width="1056" alt="apply_limit in_spark_with_my_patch" src="https://cloud.githubusercontent.com/assets/692303/20823882/6c46352c-b89b-11e6-81ab-afd8abfe0cfe.png">
## How was this patch tested?
Add tests to check to split input records into multiple `addRecords` calls.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes#16114 from maropu/SPARK-18620.
## What changes were proposed in this pull request?
- Changed FileStreamSource to use new FileStreamSourceOffset rather than LongOffset. The field is named as `logOffset` to make it more clear that this is a offset in the file stream log.
- Fixed bug in FileStreamSourceLog, the field endId in the FileStreamSourceLog.get(startId, endId) was not being used at all. No test caught it earlier. Only my updated tests caught it.
Other minor changes
- Dont use batchId in the FileStreamSource, as calling it batch id is extremely miss leading. With multiple sources, it may happen that a new batch has no new data from a file source. So offset of FileStreamSource != batchId after that batch.
## How was this patch tested?
Updated unit test.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#16205 from tdas/SPARK-18776.
Based on an informal survey, users find this option easier to understand / remember.
Author: Michael Armbrust <michael@databricks.com>
Closes#16182 from marmbrus/renameRecentProgress.
## What changes were proposed in this pull request?
Fixed the following failures:
```
org.scalatest.exceptions.TestFailedDueToTimeoutException: The code passed to eventually never returned normally. Attempted 3745 times over 1.0000790851666665 minutes. Last failure message: assertion failed: failOnDataLoss-0 not deleted after timeout.
```
```
sbt.ForkMain$ForkError: org.apache.spark.sql.streaming.StreamingQueryException: Query query-66 terminated with exception: null
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:252)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:146)
Caused by: sbt.ForkMain$ForkError: java.lang.NullPointerException: null
at java.util.ArrayList.addAll(ArrayList.java:577)
at org.apache.kafka.clients.Metadata.getClusterForCurrentTopics(Metadata.java:257)
at org.apache.kafka.clients.Metadata.update(Metadata.java:177)
at org.apache.kafka.clients.NetworkClient$DefaultMetadataUpdater.handleResponse(NetworkClient.java:605)
at org.apache.kafka.clients.NetworkClient$DefaultMetadataUpdater.maybeHandleCompletedReceive(NetworkClient.java:582)
at org.apache.kafka.clients.NetworkClient.handleCompletedReceives(NetworkClient.java:450)
at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:269)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.clientPoll(ConsumerNetworkClient.java:360)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:224)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:192)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.awaitPendingRequests(ConsumerNetworkClient.java:260)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator.ensureActiveGroup(AbstractCoordinator.java:222)
at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.ensurePartitionAssignment(ConsumerCoordinator.java:366)
at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:978)
at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:938)
at
...
```
## How was this patch tested?
Tested in #16048 by running many times.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16109 from zsxwing/fix-kafka-flaky-test.
## What changes were proposed in this pull request?
Maven compilation seem to not allow resource is sql/test to be easily referred to in kafka-0-10-sql tests. So moved the kafka-source-offset-version-2.1.0 from sql test resources to kafka-0-10-sql test resources.
## How was this patch tested?
Manually ran maven test
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#16183 from tdas/SPARK-18671-1.
## What changes were proposed in this pull request?
To be able to restart StreamingQueries across Spark version, we have already made the logs (offset log, file source log, file sink log) use json. We should added tests with actual json files in the Spark such that any incompatible changes in reading the logs is immediately caught. This PR add tests for FileStreamSourceLog, FileStreamSinkLog, and OffsetSeqLog.
## How was this patch tested?
new unit tests
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#16128 from tdas/SPARK-18671.
## What changes were proposed in this pull request?
This patch bumps master branch version to 2.2.0-SNAPSHOT.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#16126 from rxin/SPARK-18695.
This PR separates the status of a `StreamingQuery` into two separate APIs:
- `status` - describes the status of a `StreamingQuery` at this moment, including what phase of processing is currently happening and if data is available.
- `recentProgress` - an array of statistics about the most recent microbatches that have executed.
A recent progress contains the following information:
```
{
"id" : "2be8670a-fce1-4859-a530-748f29553bb6",
"name" : "query-29",
"timestamp" : 1479705392724,
"inputRowsPerSecond" : 230.76923076923077,
"processedRowsPerSecond" : 10.869565217391303,
"durationMs" : {
"triggerExecution" : 276,
"queryPlanning" : 3,
"getBatch" : 5,
"getOffset" : 3,
"addBatch" : 234,
"walCommit" : 30
},
"currentWatermark" : 0,
"stateOperators" : [ ],
"sources" : [ {
"description" : "KafkaSource[Subscribe[topic-14]]",
"startOffset" : {
"topic-14" : {
"2" : 0,
"4" : 1,
"1" : 0,
"3" : 0,
"0" : 0
}
},
"endOffset" : {
"topic-14" : {
"2" : 1,
"4" : 2,
"1" : 0,
"3" : 0,
"0" : 1
}
},
"numRecords" : 3,
"inputRowsPerSecond" : 230.76923076923077,
"processedRowsPerSecond" : 10.869565217391303
} ]
}
```
Additionally, in order to make it possible to correlate progress updates across restarts, we change the `id` field from an integer that is unique with in the JVM to a `UUID` that is globally unique.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#15954 from marmbrus/queryProgress.
## What changes were proposed in this pull request?
This PR make `sbt unidoc` complete with Java 8.
This PR roughly includes several fixes as below:
- Fix unrecognisable class and method links in javadoc by changing it from `[[..]]` to `` `...` ``
```diff
- * A column that will be computed based on the data in a [[DataFrame]].
+ * A column that will be computed based on the data in a `DataFrame`.
```
- Fix throws annotations so that they are recognisable in javadoc
- Fix URL links to `<a href="http..."></a>`.
```diff
- * [[http://en.wikipedia.org/wiki/Decision_tree_learning Decision tree]] model for regression.
+ * <a href="http://en.wikipedia.org/wiki/Decision_tree_learning">
+ * Decision tree (Wikipedia)</a> model for regression.
```
```diff
- * see http://en.wikipedia.org/wiki/Receiver_operating_characteristic
+ * see <a href="http://en.wikipedia.org/wiki/Receiver_operating_characteristic">
+ * Receiver operating characteristic (Wikipedia)</a>
```
- Fix < to > to
- `greater than`/`greater than or equal to` or `less than`/`less than or equal to` where applicable.
- Wrap it with `{{{...}}}` to print them in javadoc or use `{code ...}` or `{literal ..}`. Please refer https://github.com/apache/spark/pull/16013#discussion_r89665558
- Fix `</p>` complaint
## How was this patch tested?
Manually tested by `jekyll build` with Java 7 and 8
```
java version "1.7.0_80"
Java(TM) SE Runtime Environment (build 1.7.0_80-b15)
Java HotSpot(TM) 64-Bit Server VM (build 24.80-b11, mixed mode)
```
```
java version "1.8.0_45"
Java(TM) SE Runtime Environment (build 1.8.0_45-b14)
Java HotSpot(TM) 64-Bit Server VM (build 25.45-b02, mixed mode)
```
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#16013 from HyukjinKwon/SPARK-3359-errors-more.
## What changes were proposed in this pull request?
Ignore the flaky test to unblock other PRs while I'm debugging it.
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#16051 from zsxwing/ignore-flaky-kafka-test.
## What changes were proposed in this pull request?
Changed Kafka timestamp column type to TimestampType.
## How was this patch tested?
`test("Kafka column types")`.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#15969 from zsxwing/SPARK-18530.
## What changes were proposed in this pull request?
This PR adds `CachedKafkaConsumer.getAndIgnoreLostData` to handle corner cases of `failOnDataLoss=false`.
It also resolves [SPARK-18529](https://issues.apache.org/jira/browse/SPARK-18529) after refactoring codes: Timeout will throw a TimeoutException.
## How was this patch tested?
Because I cannot find any way to manually control the Kafka server to clean up logs, it's impossible to write unit tests for each corner case. Therefore, I just created `test("stress test for failOnDataLoss=false")` which should cover most of corner cases.
I also modified some existing tests to test for both `failOnDataLoss=false` and `failOnDataLoss=true` to make sure it doesn't break existing logic.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#15820 from zsxwing/failOnDataLoss.
## What changes were proposed in this pull request?
Avoid NPE in KinesisRecordProcessor when shutdown happens without successful init
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes#15882 from srowen/SPARK-18400.
## What changes were proposed in this pull request?
Allow configuration of max rate on a per-topicpartition basis.
## How was this patch tested?
Unit tests.
The reporter (Jeff Nadler) said he could test on his workload, so let's wait on that report.
Author: cody koeninger <cody@koeninger.org>
Closes#15132 from koeninger/SPARK-17510.
## What changes were proposed in this pull request?
This is a follow-up work of #15618.
Close file source;
For any newly created streaming context outside the withContext, explicitly close the context.
## How was this patch tested?
Existing unit tests.
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes#15818 from wangmiao1981/rtest.
## What changes were proposed in this pull request?
Currently we use java serialization for the WAL that stores the offsets contained in each batch. This has two main issues:
It can break across spark releases (though this is not the only thing preventing us from upgrading a running query)
It is unnecessarily opaque to the user.
I'd propose we require offsets to provide a user readable serialization and use that instead. JSON is probably a good option.
## How was this patch tested?
Tests were added for KafkaSourceOffset in [KafkaSourceOffsetSuite](external/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaSourceOffsetSuite.scala) and for LongOffset in [OffsetSuite](sql/core/src/test/scala/org/apache/spark/sql/streaming/OffsetSuite.scala)
Please review https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark before opening a pull request.
zsxwing marmbrus
Author: Tyson Condie <tcondie@gmail.com>
Author: Tyson Condie <tcondie@clash.local>
Closes#15626 from tcondie/spark-8360.
## What changes were proposed in this pull request?
Added test to check whether default starting offset in latest
## How was this patch tested?
new unit test
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#15778 from tdas/SPARK-18283.
## What changes were proposed in this pull request?
Increase poll timeout to try and address flaky test
## How was this patch tested?
Ran existing unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#15737 from koeninger/SPARK-18212.
## What changes were proposed in this pull request?
maxOffsetsPerTrigger option for rate limiting, proportionally based on volume of different topicpartitions.
## How was this patch tested?
Added unit test
Author: cody koeninger <cody@koeninger.org>
Closes#15527 from koeninger/SPARK-17813.
## What changes were proposed in this pull request?
startingOffsets takes specific per-topicpartition offsets as a json argument, usable with any consumer strategy
assign with specific topicpartitions as a consumer strategy
## How was this patch tested?
Unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#15504 from koeninger/SPARK-17812.
## What changes were proposed in this pull request?
The newly implemented Structured Streaming `KafkaSource` did calculate the preferred locations for each topic partition, but didn't offer this information through RDD's `getPreferredLocations` method. So here propose to add this method in `KafkaSourceRDD`.
## How was this patch tested?
Manual verification.
Author: jerryshao <sshao@hortonworks.com>
Closes#15545 from jerryshao/SPARK-17999.
## What changes were proposed in this pull request?
Actually drain commit queue rather than just iterating it.
iterator() on a concurrent linked queue won't remove items from the queue, poll() will.
## How was this patch tested?
Unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#15407 from koeninger/SPARK-17841.
## What changes were proposed in this pull request?
Metrics are needed for monitoring structured streaming apps. Here is the design doc for implementing the necessary metrics.
https://docs.google.com/document/d/1NIdcGuR1B3WIe8t7VxLrt58TJB4DtipWEbj5I_mzJys/edit?usp=sharing
Specifically, this PR adds the following public APIs changes.
### New APIs
- `StreamingQuery.status` returns a `StreamingQueryStatus` object (renamed from `StreamingQueryInfo`, see later)
- `StreamingQueryStatus` has the following important fields
- inputRate - Current rate (rows/sec) at which data is being generated by all the sources
- processingRate - Current rate (rows/sec) at which the query is processing data from
all the sources
- ~~outputRate~~ - *Does not work with wholestage codegen*
- latency - Current average latency between the data being available in source and the sink writing the corresponding output
- sourceStatuses: Array[SourceStatus] - Current statuses of the sources
- sinkStatus: SinkStatus - Current status of the sink
- triggerStatus - Low-level detailed status of the last completed/currently active trigger
- latencies - getOffset, getBatch, full trigger, wal writes
- timestamps - trigger start, finish, after getOffset, after getBatch
- numRows - input, output, state total/updated rows for aggregations
- `SourceStatus` has the following important fields
- inputRate - Current rate (rows/sec) at which data is being generated by the source
- processingRate - Current rate (rows/sec) at which the query is processing data from the source
- triggerStatus - Low-level detailed status of the last completed/currently active trigger
- Python API for `StreamingQuery.status()`
### Breaking changes to existing APIs
**Existing direct public facing APIs**
- Deprecated direct public-facing APIs `StreamingQuery.sourceStatuses` and `StreamingQuery.sinkStatus` in favour of `StreamingQuery.status.sourceStatuses/sinkStatus`.
- Branch 2.0 should have it deprecated, master should have it removed.
**Existing advanced listener APIs**
- `StreamingQueryInfo` renamed to `StreamingQueryStatus` for consistency with `SourceStatus`, `SinkStatus`
- Earlier StreamingQueryInfo was used only in the advanced listener API, but now it is used in direct public-facing API (StreamingQuery.status)
- Field `queryInfo` in listener events `QueryStarted`, `QueryProgress`, `QueryTerminated` changed have name `queryStatus` and return type `StreamingQueryStatus`.
- Field `offsetDesc` in `SourceStatus` was Option[String], converted it to `String`.
- For `SourceStatus` and `SinkStatus` made constructor private instead of private[sql] to make them more java-safe. Instead added `private[sql] object SourceStatus/SinkStatus.apply()` which are harder to accidentally use in Java.
## How was this patch tested?
Old and new unit tests.
- Rate calculation and other internal logic of StreamMetrics tested by StreamMetricsSuite.
- New info in statuses returned through StreamingQueryListener is tested in StreamingQueryListenerSuite.
- New and old info returned through StreamingQuery.status is tested in StreamingQuerySuite.
- Source-specific tests for making sure input rows are counted are is source-specific test suites.
- Additional tests to test minor additions in LocalTableScanExec, StateStore, etc.
Metrics also manually tested using Ganglia sink
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#15307 from tdas/SPARK-17731.
## What changes were proposed in this pull request?
Because `KafkaConsumer.poll(0)` may update the partition offsets, this PR just calls `seekToBeginning` to manually set the earliest offsets for the KafkaSource initial offsets.
## How was this patch tested?
Existing tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#15397 from zsxwing/SPARK-17834.
## What changes were proposed in this pull request?
Alternative approach to https://github.com/apache/spark/pull/15387
Author: cody koeninger <cody@koeninger.org>
Closes#15401 from koeninger/SPARK-17782-alt.
## What changes were proposed in this pull request?
Generate the sql test jar to fix the maven build
## How was this patch tested?
Jenkins
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#15368 from zsxwing/sql-test-jar.
## What changes were proposed in this pull request?
This PR adds a new project ` external/kafka-0-10-sql` for Structured Streaming Kafka source.
It's based on the design doc: https://docs.google.com/document/d/19t2rWe51x7tq2e5AOfrsM9qb8_m7BRuv9fel9i0PqR8/edit?usp=sharing
tdas did most of work and part of them was inspired by koeninger's work.
### Introduction
The Kafka source is a structured streaming data source to poll data from Kafka. The schema of reading data is as follows:
Column | Type
---- | ----
key | binary
value | binary
topic | string
partition | int
offset | long
timestamp | long
timestampType | int
The source can deal with deleting topics. However, the user should make sure there is no Spark job processing the data when deleting a topic.
### Configuration
The user can use `DataStreamReader.option` to set the following configurations.
Kafka Source's options | value | default | meaning
------ | ------- | ------ | -----
startingOffset | ["earliest", "latest"] | "latest" | The start point when a query is started, either "earliest" which is from the earliest offset, or "latest" which is just from the latest offset. Note: This only applies when a new Streaming query is started, and that resuming will always pick up from where the query left off.
failOnDataLost | [true, false] | true | Whether to fail the query when it's possible that data is lost (e.g., topics are deleted, or offsets are out of range). This may be a false alarm. You can disable it when it doesn't work as you expected.
subscribe | A comma-separated list of topics | (none) | The topic list to subscribe. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source.
subscribePattern | Java regex string | (none) | The pattern used to subscribe the topic. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source.
kafka.consumer.poll.timeoutMs | long | 512 | The timeout in milliseconds to poll data from Kafka in executors
fetchOffset.numRetries | int | 3 | Number of times to retry before giving up fatch Kafka latest offsets.
fetchOffset.retryIntervalMs | long | 10 | milliseconds to wait before retrying to fetch Kafka offsets
Kafka's own configurations can be set via `DataStreamReader.option` with `kafka.` prefix, e.g, `stream.option("kafka.bootstrap.servers", "host:port")`
### Usage
* Subscribe to 1 topic
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribe", "topic1")
.load()
```
* Subscribe to multiple topics
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribe", "topic1,topic2")
.load()
```
* Subscribe to a pattern
```Scala
spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "host:port")
.option("subscribePattern", "topic.*")
.load()
```
## How was this patch tested?
The new unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Author: Tathagata Das <tathagata.das1565@gmail.com>
Author: Shixiong Zhu <zsxwing@gmail.com>
Author: cody koeninger <cody@koeninger.org>
Closes#15102 from zsxwing/kafka-source.
This patch updates the `kinesis-asl-assembly` build to prevent that module from being published as part of Maven releases and snapshot builds.
The `kinesis-asl-assembly` includes classes from the Kinesis Client Library (KCL) and Kinesis Producer Library (KPL), both of which are licensed under the Amazon Software License and are therefore prohibited from being distributed in Apache releases.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#15167 from JoshRosen/stop-publishing-kinesis-assembly.
## What changes were proposed in this pull request?
Docker tests are using older version of jersey jars (1.19), which was used in older releases of spark. In 2.0 releases Spark was upgraded to use 2.x verison of Jersey. After upgrade to new versions, docker tests are failing with AbstractMethodError. Now that spark is upgraded to 2.x jersey version, using of shaded docker jars may not be required any more. Removed the exclusions/overrides of jersey related classes from pom file, and changed the docker-client to use regular jar instead of shaded one.
## How was this patch tested?
Tested using existing docker-integration-tests
Author: sureshthalamati <suresh.thalamati@gmail.com>
Closes#15114 from sureshthalamati/docker_testfix-spark-17473.
**## What changes were proposed in this pull request?**
There are two tests in this suite that are particularly flaky on the following hardware:
2x Intel(R) Xeon(R) CPU E5-2697 v2 2.70GHz and 16 GB of RAM, 1 TB HDD
This simple PR increases the timeout times and batch duration so they can reliably pass
**## How was this patch tested?**
Existing unit tests with the two core box where I was seeing the failures often
Author: Adam Roberts <aroberts@uk.ibm.com>
Closes#15094 from a-roberts/patch-6.
## What changes were proposed in this pull request?
We should generally use `ArrayBuffer.+=(A)` rather than `ArrayBuffer.append(A)`, because `append(A)` would involve extra boxing / unboxing.
## How was this patch tested?
N/A
Author: Liwei Lin <lwlin7@gmail.com>
Closes#14914 from lw-lin/append_to_plus_eq_v2.
## What changes were proposed in this pull request?
When reading float4 and smallint columns from PostgreSQL, Spark's `PostgresDialect` widens these types to Decimal and Integer rather than using the narrower Float and Short types. According to https://www.postgresql.org/docs/7.1/static/datatype.html#DATATYPE-TABLE, Postgres maps the `smallint` type to a signed two-byte integer and the `real` / `float4` types to single precision floating point numbers.
This patch fixes this by adding more special-cases to `getCatalystType`, similar to what was done for the Derby JDBC dialect. I also fixed a similar problem in the write path which causes Spark to create integer columns in Postgres for what should have been ShortType columns.
## How was this patch tested?
New test cases in `PostgresIntegrationSuite` (which I ran manually because Jenkins can't run it right now).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#14796 from JoshRosen/postgres-jdbc-type-fixes.
## What changes were proposed in this pull request?
Update Kafka streaming connector to use Kafka 0.10.0.1 release
## How was this patch tested?
Tested via Spark unit and integration tests
Author: Luciano Resende <lresende@apache.org>
Closes#14606 from lresende/kafka-upgrade.
## What changes were proposed in this pull request?
Ability to use KafkaUtils.createDirectStream with starting offsets in python 3 by using java.lang.Number instead of Long during param mapping in scala helper. This allows py4j to pass Integer or Long to the map and resolves ClassCastException problems.
## How was this patch tested?
unit tests
jerryshao - could you please look at this PR?
Author: Mariusz Strzelecki <mariusz.strzelecki@allegrogroup.com>
Closes#14540 from szczeles/kafka_pyspark.
## What changes were proposed in this pull request?
Avoid using postfix operation for command execution in SQLQuerySuite where it wasn't whitelisted and audit existing whitelistings removing postfix operators from most places. Some notable places where postfix operation remains is in the XML parsing & time units (seconds, millis, etc.) where it arguably can improve readability.
## How was this patch tested?
Existing tests.
Author: Holden Karau <holden@us.ibm.com>
Closes#14407 from holdenk/SPARK-16779.
The current ganglia reporter doesn't set metric expiration time (dmax). The metrics of all finished applications are indefinitely left displayed in ganglia web. The dmax parameter allows user to set the lifetime of the metrics. The default value is 0 for compatibility with previous versions.
Author: Ekasit Kijsipongse <ekasitk@gmail.com>
Closes#11127 from ekasitk/ganglia-dmax.
## What changes were proposed in this pull request?
Spark will convert **BooleanType** to **BIT(1)**, **LongType** to **BIGINT**, **ByteType** to **BYTE** when saving DataFrame to Oracle, but Oracle does not support BIT, BIGINT and BYTE types.
This PR is convert following _Spark Types_ to _Oracle types_ refer to [Oracle Developer's Guide](https://docs.oracle.com/cd/E19501-01/819-3659/gcmaz/)
Spark Type | Oracle
----|----
BooleanType | NUMBER(1)
IntegerType | NUMBER(10)
LongType | NUMBER(19)
FloatType | NUMBER(19, 4)
DoubleType | NUMBER(19, 4)
ByteType | NUMBER(3)
ShortType | NUMBER(5)
## How was this patch tested?
Add new tests in [JDBCSuite.scala](22b0c2a422 (diff-dc4b58851b084b274df6fe6b189db84d)) and [OracleDialect.scala](22b0c2a422 (diff-5e0cadf526662f9281aa26315b3750ad))
Author: Yuming Wang <wgyumg@gmail.com>
Closes#14377 from wangyum/SPARK-16625.
## What changes were proposed in this pull request?
This PR replaces the old Kafka API to 0.10.0 ones in `KafkaTestUtils`.
The change include:
- `Producer` to `KafkaProducer`
- Change configurations to equalvant ones. (I referred [here](http://kafka.apache.org/documentation.html#producerconfigs) for 0.10.0 and [here](http://kafka.apache.org/082/documentation.html#producerconfigs
) for old, 0.8.2).
This PR will remove the build warning as below:
```scala
[WARNING] .../spark/external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaTestUtils.scala:71: class Producer in package producer is deprecated: This class has been deprecated and will be removed in a future release. Please use org.apache.kafka.clients.producer.KafkaProducer instead.
[WARNING] private var producer: Producer[String, String] = _
[WARNING] ^
[WARNING] .../spark/external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaTestUtils.scala:181: class Producer in package producer is deprecated: This class has been deprecated and will be removed in a future release. Please use org.apache.kafka.clients.producer.KafkaProducer instead.
[WARNING] producer = new Producer[String, String](new ProducerConfig(producerConfiguration))
[WARNING] ^
[WARNING] .../spark/streaming/kafka010/KafkaTestUtils.scala:181: class ProducerConfig in package producer is deprecated: This class has been deprecated and will be removed in a future release. Please use org.apache.kafka.clients.producer.ProducerConfig instead.
[WARNING] producer = new Producer[String, String](new ProducerConfig(producerConfiguration))
[WARNING] ^
[WARNING] .../spark/external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaTestUtils.scala:182: class KeyedMessage in package producer is deprecated: This class has been deprecated and will be removed in a future release. Please use org.apache.kafka.clients.producer.ProducerRecord instead.
[WARNING] producer.send(messages.map { new KeyedMessage[String, String](topic, _ ) }: _*)
[WARNING] ^
[WARNING] four warnings found
[WARNING] warning: [options] bootstrap class path not set in conjunction with -source 1.7
[WARNING] 1 warning
```
## How was this patch tested?
Existing tests that use `KafkaTestUtils` should cover this.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#14416 from HyukjinKwon/SPARK-16776.
## What changes were proposed in this pull request?
The current test is incorrect, because
- The expected number of messages does not take into account that the topic has 2 partitions, and rate is set per partition.
- Also in some cases, the test ran out of data in Kafka while waiting for the right amount of data per batch.
The PR
- Reduces the number of partitions to 1
- Adds more data to Kafka
- Runs with 0.5 second so that batches are created slowly
## How was this patch tested?
Ran many times locally, going to run it many times in Jenkins
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#14361 from tdas/kafka-rate-test-fix.
https://issues.apache.org/jira/browse/SPARK-16535
## What changes were proposed in this pull request?
When I scan through the pom.xml of sub projects, I found this warning as below and attached screenshot
```
Definition of groupId is redundant, because it's inherited from the parent
```
I've tried to remove some of the lines with groupId definition, and the build on my local machine is still ok.
```
<groupId>org.apache.spark</groupId>
```
As I just find now `<maven.version>3.3.9</maven.version>` is being used in Spark 2.x, and Maven-3 supports versionless parent elements: Maven 3 will remove the need to specify the parent version in sub modules. THIS is great (in Maven 3.1).
ref: http://stackoverflow.com/questions/3157240/maven-3-worth-it/3166762#3166762
## How was this patch tested?
I've tested by re-building the project, and build succeeded.
Author: Xin Ren <iamshrek@126.com>
Closes#14189 from keypointt/SPARK-16535.
## What changes were proposed in this pull request?
After SPARK-16476 (committed earlier today as #14128), we can finally bump the version number.
## How was this patch tested?
N/A
Author: Reynold Xin <rxin@databricks.com>
Closes#14130 from rxin/SPARK-16477.
## What changes were proposed in this pull request?
Allow for kafka topic subscriptions based on a regex pattern.
## How was this patch tested?
Unit tests, manual tests
Author: cody koeninger <cody@koeninger.org>
Closes#14026 from koeninger/SPARK-13569.
## What changes were proposed in this pull request?
Bring the kafka-0-8 subproject up to date with some test modifications from development on 0-10.
Main changes are
- eliminating waits on concurrent queue in favor of an assert on received results,
- atomics instead of volatile (although this probably doesn't matter)
- increasing uniqueness of topic names
## How was this patch tested?
Unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#14073 from koeninger/kafka-0-8-test-direct-cleanup.
## What changes were proposed in this pull request?
Testing for 0.10 uncovered an issue with a fixed port number being used in KafkaTestUtils. This is making a roughly equivalent fix for the 0.8 connector
## How was this patch tested?
Unit tests, manual tests
Author: cody koeninger <cody@koeninger.org>
Closes#14018 from koeninger/kafka-0-8-test-port.
## What changes were proposed in this pull request?
This is an alternative to the refactoring proposed by https://github.com/apache/spark/pull/13996
## How was this patch tested?
unit tests
also tested under scala 2.10 via
mvn -Dscala-2.10
Author: cody koeninger <cody@koeninger.org>
Closes#13998 from koeninger/kafka-0-10-refactor.
## What changes were proposed in this pull request?
code cleanup in kafka-0-8 to match suggested changes for kafka-0-10 branch
## How was this patch tested?
unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#13908 from koeninger/kafka-0-8-cleanup.
## What changes were proposed in this pull request?
The commented lines failed scala 2.10 build. This is because of change in behavior of case classes between 2.10 and 2.11. In scala 2.10, if companion object of a case class has explicitly defined apply(), then the implicit apply method is not generated. In scala 2.11 it is generated. Hence, the lines compile fine in 2.11 but not in 2.10.
This simply comments the tests to fix broken build. Correct solution is pending.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#13992 from tdas/SPARK-12177.
## What changes were proposed in this pull request?
New Kafka consumer api for the released 0.10 version of Kafka
## How was this patch tested?
Unit tests, manual tests
Author: cody koeninger <cody@koeninger.org>
Closes#11863 from koeninger/kafka-0.9.
## What changes were proposed in this pull request?
- Deprecate old Java accumulator API; should use Scala now
- Update Java tests and examples
- Don't bother testing old accumulator API in Java 8 (too)
- (fix a misspelling too)
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#13606 from srowen/SPARK-15086.
## What changes were proposed in this pull request?
`an -> a`
Use cmds like `find . -name '*.R' | xargs -i sh -c "grep -in ' an [^aeiou]' {} && echo {}"` to generate candidates, and review them one by one.
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes#13515 from zhengruifeng/an_a.
This helps with preventing jdk8-specific calls being checked in,
because PR builders are running the compiler with the wrong settings.
If the JAVA_7_HOME env variable is set, assume it points at
a jdk7 and use its rt.jar when invoking javac. For zinc, just run
it with jdk7, and disable it when building jdk8-specific code.
A big note for sbt usage: adding the bootstrap options forces sbt
to fork the compiler, and that disables incremental compilation.
That means that it's really not convenient to use for normal
development, but should be ok for automated builds.
Tested with JAVA_HOME=jdk8 and JAVA_7_HOME=jdk7:
- mvn + zinc
- mvn sans zinc
- sbt
Verified that in all cases, jdk8-specific library calls fail to
compile.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#13272 from vanzin/SPARK-15451.
## What changes were proposed in this pull request?
This is a simple patch that makes package names for Java 8 test suites consistent. I moved everything to test.org.apache.spark to we can test package private APIs properly. Also added "java8" as the package name so we can easily run all the tests related to Java 8.
## How was this patch tested?
This is a test only change.
Author: Reynold Xin <rxin@databricks.com>
Closes#13364 from rxin/SPARK-15633.
## What changes were proposed in this pull request?
`JavaKafkaStreamSuite.testKafkaStream` assumes when `sent.size == result.size`, the contents of `sent` and `result` should be same. However, that's not true. The content of `result` may not be the final content.
This PR modified the test to always retry the assertions even if the contents of `sent` and `result` are not same.
Here is the failure in Jenkins: http://spark-tests.appspot.com/tests/org.apache.spark.streaming.kafka.JavaKafkaStreamSuite/testKafkaStream
## How was this patch tested?
Jenkins unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#13281 from zsxwing/flaky-kafka-test.
## What changes were proposed in this pull request?
(See https://github.com/apache/spark/pull/12416 where most of this was already reviewed and committed; this is just the module structure and move part. This change does not move the annotations into test scope, which was the apparently problem last time.)
Rename `spark-test-tags` -> `spark-tags`; move common annotations like `Since` to `spark-tags`
## How was this patch tested?
Jenkins tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#13074 from srowen/SPARK-15290.
## What changes were proposed in this pull request?
(Retry of https://github.com/apache/spark/pull/13049)
- update to httpclient 4.5 / httpcore 4.4
- remove some defunct exclusions
- manage httpmime version to match
- update selenium / httpunit to support 4.5 (possible now that Jetty 9 is used)
## How was this patch tested?
Jenkins tests. Also, locally running the same test command of one Jenkins profile that failed: `mvn -Phadoop-2.6 -Pyarn -Phive -Phive-thriftserver -Pkinesis-asl ...`
Author: Sean Owen <sowen@cloudera.com>
Closes#13117 from srowen/SPARK-12972.2.
## What changes were proposed in this pull request?
- update httpcore/httpclient to latest
- centralize version management
- remove excludes that are no longer relevant according to SBT/Maven dep graphs
- also manage httpmime to match httpclient
## How was this patch tested?
Jenkins tests, plus review of dependency graphs from SBT/Maven, and review of test-dependencies.sh output
Author: Sean Owen <sowen@cloudera.com>
Closes#13049 from srowen/SPARK-12972.
## What changes were proposed in this pull request?
When running with Kinesis Consumer Library (KCL), against a stream that contains aggregated data, the KCL needs access to protobuf to de-aggregate the records. Without this patch, that results in the following error message:
```
Caused by: java.lang.ClassNotFoundException: com.google.protobuf.ProtocolStringList
```
This PR upgrades the protobuf dependency within the kinesis-asl-assembly, and relocates that package (as not to conflict with Spark's use of 2.5.0), which fixes the above CNFE.
## How was this patch tested?
Used kinesis word count example against a stream containing aggregated data.
See: SPARK-14421
Author: Brian O'Neill <bone@alumni.brown.edu>
Closes#13054 from boneill42/protobuf-relocation-for-kcl.
## What changes were proposed in this pull request?
Renaming the streaming-kafka artifact to include kafka version, in anticipation of needing a different artifact for later kafka versions
## How was this patch tested?
Unit tests
Author: cody koeninger <cody@koeninger.org>
Closes#12946 from koeninger/SPARK-15085.
https://issues.apache.org/jira/browse/SPARK-14936
## What changes were proposed in this pull request?
FlumePollingStreamSuite contains two tests which run for a minute each. This seems excessively slow and we should speed it up if possible.
In this PR, instead of creating `StreamingContext` directly from `conf`, here an underlying `SparkContext` is created before all and it is used to create each`StreamingContext`.
Running time is reduced by avoiding multiple `SparkContext` creations and destroys.
## How was this patch tested?
Tested on my local machine running `testOnly *.FlumePollingStreamSuite`
Author: Xin Ren <iamshrek@126.com>
Closes#12845 from keypointt/SPARK-14936.
## What changes were proposed in this pull request?
Because this test extracts data from `DStream.generatedRDDs` before stopping, it may get data before checkpointing. Then after recovering from the checkpoint, `recoveredOffsetRanges` may contain something not in `offsetRangesBeforeStop`, which will fail the test. Adding `Thread.sleep(1000)` before `ssc.stop()` will reproduce this failure.
This PR just moves the logic of `offsetRangesBeforeStop` (also renamed to `offsetRangesAfterStop`) after `ssc.stop()` to fix the flaky test.
## How was this patch tested?
Jenkins unit tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#12903 from zsxwing/SPARK-6005.
## What changes were proposed in this pull request?
PR fixes the import issue which breaks udf functions.
The following code snippet throws an error
```
scala> import org.apache.spark.sql.functions._
import org.apache.spark.sql.functions._
scala> import org.apache.spark.sql.expressions._
import org.apache.spark.sql.expressions._
scala> udf((v: String) => v.stripSuffix("-abc"))
<console>:30: error: No TypeTag available for String
udf((v: String) => v.stripSuffix("-abc"))
```
This PR resolves the issue.
## How was this patch tested?
patch tested with unit tests.
(If this patch involves UI changes, please attach a screenshot; otherwise, remove this)
Author: Subhobrata Dey <sbcd90@gmail.com>
Closes#12458 from sbcd90/udfFuncBreak.
## What changes were proposed in this pull request?
Create a maven profile for executing the docker integration tests using maven
Remove docker integration tests from main sbt build
Update documentation on how to run docker integration tests from sbt
## How was this patch tested?
Manual test of the docker integration tests as in :
mvn -Pdocker-integration-tests -pl :spark-docker-integration-tests_2.11 compile test
## Other comments
Note that the the DB2 Docker Tests are still disabled as there is a kernel version issue on the AMPLab Jenkins slaves and we would need to get them on the right level before enabling those tests. They do run ok locally with the updates from PR #12348
Author: Luciano Resende <lresende@apache.org>
Closes#12508 from lresende/docker.
## What changes were proposed in this pull request?
Enhance the DB2 JDBC Dialect docker tests as they seemed to have had some issues on previous merge causing some tests to fail.
## How was this patch tested?
By running the integration tests locally.
Author: Luciano Resende <lresende@apache.org>
Closes#12348 from lresende/SPARK-14589.
## What changes were proposed in this pull request?
Replace com.sun.jersey with org.glassfish.jersey. Changes to the Spark Web UI code were required to compile. The changes were relatively standard Jersey migration things.
## How was this patch tested?
I did a manual test for the standalone web APIs. Although I didn't test the functionality of the security filter itself, the code that changed non-trivially is how we actually register the filter. I attached a debugger to the Spark master and verified that the SecurityFilter code is indeed invoked upon hitting /api/v1/applications.
Author: mcheah <mcheah@palantir.com>
Closes#12715 from mccheah/feature/upgrade-jersey.
## What changes were proposed in this pull request?
This PR adds `since` tag into the matrix and vector classes in spark-mllib-local.
## How was this patch tested?
Scala-style checks passed.
Author: Pravin Gadakh <prgadakh@in.ibm.com>
Closes#12416 from pravingadakh/SPARK-14613.
## What changes were proposed in this pull request?
Spark uses `NewLineAtEofChecker` rule in Scala by ScalaStyle. And, most Java code also comply with the rule. This PR aims to enforce the same rule `NewlineAtEndOfFile` by CheckStyle explicitly. Also, this fixes lint-java errors since SPARK-14465. The followings are the items.
- Adds a new line at the end of the files (19 files)
- Fixes 25 lint-java errors (12 RedundantModifier, 6 **ArrayTypeStyle**, 2 LineLength, 2 UnusedImports, 2 RegexpSingleline, 1 ModifierOrder)
## How was this patch tested?
After the Jenkins test succeeds, `dev/lint-java` should pass. (Currently, Jenkins dose not run lint-java.)
```bash
$ dev/lint-java
Using `mvn` from path: /usr/local/bin/mvn
Checkstyle checks passed.
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12632 from dongjoon-hyun/SPARK-14868.
## What changes were proposed in this pull request?
`JavaStreamingContext.awaitTermination` methods should be declared as `throws[InterruptedException]` so that this exception can be handled in Java code. Note this is not just a doc change, but an API change, since now (in Java) the method has a checked exception to handle. All await-like methods in Java APIs behave this way, so seems worthwhile for 2.0.
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#12418 from srowen/SPARK-8393.
The Docker integration tests are failing very often (https://spark-tests.appspot.com/failed-tests) so I think we should disable these suites for now until we have time to improve them.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#12549 from JoshRosen/ignore-all-docker-tests.
## What changes were proposed in this pull request?
Enable Oracle docker tests
## How was this patch tested?
Existing tests
Author: Luciano Resende <lresende@apache.org>
Closes#12270 from lresende/oracle.
## What changes were proposed in this pull request?
This PR removes extra anonymous closure within functional transformations.
For example,
```scala
.map(item => {
...
})
```
which can be just simply as below:
```scala
.map { item =>
...
}
```
## How was this patch tested?
Related unit tests and `sbt scalastyle`.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#12382 from HyukjinKwon/minor-extra-closers.
## What changes were proposed in this pull request?
According to the [Spark Code Style Guide](https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide) and [Scala Style Guide](http://docs.scala-lang.org/style/control-structures.html#curlybraces), we had better enforce the following rule.
```
case: Always omit braces in case clauses.
```
This PR makes a new ScalaStyle rule, 'OmitBracesInCase', and enforces it to the code.
## How was this patch tested?
Pass the Jenkins tests (including Scala style checking)
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12280 from dongjoon-hyun/SPARK-14508.
Add integration tests based on docker to test DB2 JDBC dialect support
Author: Luciano Resende <lresende@apache.org>
Closes#9893 from lresende/SPARK-10521.
## What changes were proposed in this pull request?
Currently, `checkstyle` is configured to check the files under `src/main/java`. However, Spark has Java files in `src/main/scala`, too. This PR fixes the following configuration in `pom.xml` and the unchecked-so-far violations on those files.
```xml
-<sourceDirectory>${basedir}/src/main/java</sourceDirectory>
+<sourceDirectories>${basedir}/src/main/java,${basedir}/src/main/scala</sourceDirectories>
```
## How was this patch tested?
After passing the Jenkins build and manually `dev/lint-java`. (Note that Jenkins does not run `lint-java`)
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12242 from dongjoon-hyun/SPARK-14465.
The current package name uses a dash, which is a little weird but seemed
to work. That is, until a new test tried to mock a class that references
one of those shaded types, and then things started failing.
Most changes are just noise to fix the logging configs.
For reference, SPARK-8815 also raised this issue, although at the time it
did not cause any issues in Spark, so it was not addressed.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#11941 from vanzin/SPARK-14134.
## What changes were proposed in this pull request?
According to the [Spark Code Style Guide](https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide#SparkCodeStyleGuide-Indentation), this PR adds a new scalastyle rule to prevent the followings.
```
/** In Spark, we don't use the ScalaDoc style so this
* is not correct.
*/
```
## How was this patch tested?
Pass the Jenkins tests (including `lint-scala`).
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12221 from dongjoon-hyun/SPARK-14444.
## What changes were proposed in this pull request?
Adds unit tests for java 8 lambda syntax with typed aggregates as a follow-up to #12168
## How was this patch tested?
Unit tests.
Author: Eric Liang <ekl@databricks.com>
Closes#12181 from ericl/sc-2794-2.
## What changes were proposed in this pull request?
This PR contains the following 5 types of maintenance fix over 59 files (+94 lines, -93 lines).
- Fix typos(exception/log strings, testcase name, comments) in 44 lines.
- Fix lint-java errors (MaxLineLength) in 6 lines. (New codes after SPARK-14011)
- Use diamond operators in 40 lines. (New codes after SPARK-13702)
- Fix redundant semicolon in 5 lines.
- Rename class `InferSchemaSuite` to `CSVInferSchemaSuite` in CSVInferSchemaSuite.scala.
## How was this patch tested?
Manual and pass the Jenkins tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12139 from dongjoon-hyun/SPARK-14355.
## What changes were proposed in this pull request?
This PR aims to fix all Scala-Style multiline comments into Java-Style multiline comments in Scala codes.
(All comment-only changes over 77 files: +786 lines, −747 lines)
## How was this patch tested?
Manual.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#12130 from dongjoon-hyun/use_multiine_javadoc_comments.
This patch fixes a compilation / build break in Spark's `java8-tests` and refactors their POM to simplify the build. See individual commit messages for more details.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#12073 from JoshRosen/fix-java8-tests.
## What changes were proposed in this pull request?
This PR moves flume back to Spark as per the discussion in the dev mail-list.
## How was this patch tested?
Existing Jenkins tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#11895 from zsxwing/move-flume-back.
## What changes were proposed in this pull request?
- Removed two methods that has been deprecated since 1.4
- Fixed two other compilation warnings
## How was this patch tested?
existing test suits
Author: proflin <proflin.me@gmail.com>
Closes#11850 from lw-lin/streaming-kinesis-deprecates-warnings.
## What changes were proposed in this pull request?
[Spark Coding Style Guide](https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide) has 100-character limit on lines, but it's disabled for Java since 11/09/15. This PR enables **LineLength** checkstyle again. To help that, this also introduces **RedundantImport** and **RedundantModifier**, too. The following is the diff on `checkstyle.xml`.
```xml
- <!-- TODO: 11/09/15 disabled - the lengths are currently > 100 in many places -->
- <!--
<module name="LineLength">
<property name="max" value="100"/>
<property name="ignorePattern" value="^package.*|^import.*|a href|href|http://|https://|ftp://"/>
</module>
- -->
<module name="NoLineWrap"/>
<module name="EmptyBlock">
<property name="option" value="TEXT"/>
-167,5 +164,7
</module>
<module name="CommentsIndentation"/>
<module name="UnusedImports"/>
+ <module name="RedundantImport"/>
+ <module name="RedundantModifier"/>
```
## How was this patch tested?
Currently, `lint-java` is disabled in Jenkins. It needs a manual test.
After passing the Jenkins tests, `dev/lint-java` should passes locally.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#11831 from dongjoon-hyun/SPARK-14011.
## What changes were proposed in this pull request?
Logging was made private in Spark 2.0. If we move it, then users would be able to create a Logging trait themselves to avoid changing their own code.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#11764 from cloud-fan/logger.
## What changes were proposed in this pull request?
Currently there are a few sub-projects, each for integrating with different external sources for Streaming. Now that we have better ability to include external libraries (spark packages) and with Spark 2.0 coming up, we can move the following projects out of Spark to https://github.com/spark-packages
- streaming-flume
- streaming-akka
- streaming-mqtt
- streaming-zeromq
- streaming-twitter
They are just some ancillary packages and considering the overhead of maintenance, running tests and PR failures, it's better to maintain them out of Spark. In addition, these projects can have their different release cycles and we can release them faster.
I have already copied these projects to https://github.com/spark-packages
## How was this patch tested?
Jenkins tests
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#11672 from zsxwing/remove-external-pkg.
This patch upgrades Py4J from 0.9.1 to 0.9.2 in order to include a patch which modifies Py4J to use the current thread's ContextClassLoader when performing reflection / class loading. This is necessary in order to fix [SPARK-5185](https://issues.apache.org/jira/browse/SPARK-5185), a longstanding issue affecting the use of `--jars` and `--packages` in PySpark.
In order to demonstrate that the fix works, I removed the workarounds which were added as part of [SPARK-6027](https://issues.apache.org/jira/browse/SPARK-6027) / #4779 and other patches.
Py4J diff: https://github.com/bartdag/py4j/compare/0.9.1...0.9.2
/cc zsxwing tdas davies brkyvz
Author: Josh Rosen <joshrosen@databricks.com>
Closes#11687 from JoshRosen/py4j-0.9.2.
trait SynchronizedSet in package mutable is deprecated
Author: Wilson Wu <wilson888888888@gmail.com>
Closes#11580 from wilson888888888/spark-synchronizedset.
## What changes were proposed in this pull request?
This PR fixes 135 typos over 107 files:
* 121 typos in comments
* 11 typos in testcase name
* 3 typos in log messages
## How was this patch tested?
Manual.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#11689 from dongjoon-hyun/fix_more_typos.
## What changes were proposed in this pull request?
- Fixes calls to `new String(byte[])` or `String.getBytes()` that rely on platform default encoding, to use UTF-8
- Same for `InputStreamReader` and `OutputStreamWriter` constructors
- Standardizes on UTF-8 everywhere
- Standardizes specifying the encoding with `StandardCharsets.UTF-8`, not the Guava constant or "UTF-8" (which means handling `UnuspportedEncodingException`)
- (also addresses the other remaining Coverity scan issues, which are pretty trivial; these are separated into commit 1deecd8d9c )
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes#11657 from srowen/SPARK-13823.
## What changes were proposed in this pull request?
Move `docker` dirs out of top level into `external/`; move `extras/*` into `external/`
## How was this patch tested?
This is tested with Jenkins tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#11523 from srowen/SPARK-13595.
…ing partitions
I'm pretty sure this is the reason we couldn't easily recover from an unbalanced Kafka partition under heavy load when using backpressure.
`maxMessagesPerPartition` calculates an appropriate limit for the message rate from all partitions, and then divides by the number of partitions to determine how many messages to retrieve per partition. The problem with this approach is that when one partition is behind by millions of records (due to random Kafka issues), but the rate estimator calculates only 100k total messages can be retrieved, each partition (out of say 32) only retrieves max 100k/32=3125 messages.
This PR (still needing a test) determines a per-partition desired message count by using the current lag for each partition to preferentially weight the total message limit among the partitions. In this situation, if each partition gets 1k messages, but 1 partition starts 1M behind, then the total number of messages to retrieve is (32 * 1k + 1M) = 1032000 messages, of which the one partition needs 1001000. So, it gets (1001000 / 1032000) = 97% of the 100k messages, and the other 31 partitions share the remaining 3%.
Assuming all of 100k the messages are retrieved and processed within the batch window, the rate calculator will increase the number of messages to retrieve in the next batch, until it reaches a new stable point or the backlog is finished processed.
We're going to try deploying this internally at Shopify to see if this resolves our issue.
tdas koeninger holdenk
Author: Jason White <jason.white@shopify.com>
Closes#10089 from JasonMWhite/rate_controller_offsets.
## What changes were proposed in this pull request?
After SPARK-6990, `dev/lint-java` keeps Java code healthy and helps PR review by saving much time.
This issue aims remove unused imports from Java/Scala code and add `UnusedImports` checkstyle rule to help developers.
## How was this patch tested?
```
./dev/lint-java
./build/sbt compile
```
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#11438 from dongjoon-hyun/SPARK-13583.
## What changes were proposed in this pull request?
Make some cross-cutting code improvements according to static analysis. These are individually up for discussion since they exist in separate commits that can be reverted. The changes are broadly:
- Inner class should be static
- Mismatched hashCode/equals
- Overflow in compareTo
- Unchecked warnings
- Misuse of assert, vs junit.assert
- get(a) + getOrElse(b) -> getOrElse(a,b)
- Array/String .size -> .length (occasionally, -> .isEmpty / .nonEmpty) to avoid implicit conversions
- Dead code
- tailrec
- exists(_ == ) -> contains find + nonEmpty -> exists filter + size -> count
- reduce(_+_) -> sum map + flatten -> map
The most controversial may be .size -> .length simply because of its size. It is intended to avoid implicits that might be expensive in some places.
## How was the this patch tested?
Existing Jenkins unit tests.
Author: Sean Owen <sowen@cloudera.com>
Closes#11292 from srowen/SPARK-13423.
Introduces a "ask" style ```store``` in ```ActorReceiver``` as a way to allow actor receiver blocked by back pressure or maxRate.
Author: Lin Zhao <lin@exabeam.com>
Closes#11176 from lin-zhao/SPARK-13069.
trait SynchronizedMap in package mutable is deprecated: Synchronization via traits is deprecated as it is inherently unreliable. Change to java.util.concurrent.ConcurrentHashMap instead.
Author: Huaxin Gao <huaxing@us.ibm.com>
Closes#11250 from huaxingao/spark__13186.
Building with Scala 2.11 results in the warning trait SynchronizedBuffer in package mutable is deprecated: Synchronization via traits is deprecated as it is inherently unreliable. Consider java.util.concurrent.ConcurrentLinkedQueue as an alternative - we already use ConcurrentLinkedQueue elsewhere so lets replace it.
Some notes about how behaviour is different for reviewers:
The Seq from a SynchronizedBuffer that was implicitly converted would continue to receive updates - however when we do the same conversion explicitly on the ConcurrentLinkedQueue this isn't the case. Hence changing some of the (internal & test) APIs to pass an Iterable. toSeq is safe to use if there are no more updates.
Author: Holden Karau <holden@us.ibm.com>
Author: tedyu <yuzhihong@gmail.com>
Closes#11067 from holdenk/SPARK-13165-replace-deprecated-synchronizedBuffer-in-streaming.
This patch changes Spark's build to make Scala 2.11 the default Scala version. To be clear, this does not mean that Spark will stop supporting Scala 2.10: users will still be able to compile Spark for Scala 2.10 by following the instructions on the "Building Spark" page; however, it does mean that Scala 2.11 will be the default Scala version used by our CI builds (including pull request builds).
The Scala 2.11 compiler is faster than 2.10, so I think we'll be able to look forward to a slight speedup in our CI builds (it looks like it's about 2X faster for the Maven compile-only builds, for instance).
After this patch is merged, I'll update Jenkins to add new compile-only jobs to ensure that Scala 2.10 compilation doesn't break.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#10608 from JoshRosen/SPARK-6363.
Include the following changes:
1. Add "streaming-akka" project and org.apache.spark.streaming.akka.AkkaUtils for creating an actorStream
2. Remove "StreamingContext.actorStream" and "JavaStreamingContext.actorStream"
3. Update the ActorWordCount example and add the JavaActorWordCount example
4. Make "streaming-zeromq" depend on "streaming-akka" and update the codes accordingly
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#10744 from zsxwing/streaming-akka-2.
Fix the style violation (space before , and :).
This PR is a followup for #10643.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#10685 from sarutak/SPARK-12692-followup-streaming.
This patch removes all non-Maven-central repositories from Spark's build, thereby avoiding any risk of future build-breaks due to us accidentally depending on an artifact which is not present in an immutable public Maven repository.
I tested this by running
```
build/mvn \
-Phive \
-Phive-thriftserver \
-Pkinesis-asl \
-Pspark-ganglia-lgpl \
-Pyarn \
dependency:go-offline
```
inside of a fresh Ubuntu Docker container with no Ivy or Maven caches (I did a similar test for SBT).
Author: Josh Rosen <joshrosen@databricks.com>
Closes#10659 from JoshRosen/SPARK-4628.
Fix most build warnings: mostly deprecated API usages. I'll annotate some of the changes below. CC rxin who is leading the charge to remove the deprecated APIs.
Author: Sean Owen <sowen@cloudera.com>
Closes#10570 from srowen/SPARK-12618.
This PR includes the following changes:
1. Rename `ActorReceiver` to `ActorReceiverSupervisor`
2. Remove `ActorHelper`
3. Add a new `ActorReceiver` for Scala and `JavaActorReceiver` for Java
4. Add `JavaActorWordCount` example
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#10457 from zsxwing/java-actor-stream.
Also included a few miscelaneous other modules that had very few violations.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#10532 from vanzin/SPARK-3873-streaming.
`ByteBuffer` doesn't guarantee all contents in `ByteBuffer.array` are valid. E.g, a ByteBuffer returned by `ByteBuffer.slice`. We should not use the whole content of `ByteBuffer` unless we know that's correct.
This patch fixed all places that use `ByteBuffer.array` incorrectly.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#10083 from zsxwing/bytebuffer-array.
We should upgrade to SBT 0.13.9, since this is a requirement in order to use SBT's new Maven-style resolution features (which will be done in a separate patch, because it's blocked by some binary compatibility issues in the POM reader plugin).
I also upgraded Scalastyle to version 0.8.0, which was necessary in order to fix a Scala 2.10.5 compatibility issue (see https://github.com/scalastyle/scalastyle/issues/156). The newer Scalastyle is slightly stricter about whitespace surrounding tokens, so I fixed the new style violations.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#10112 from JoshRosen/upgrade-to-sbt-0.13.9.
this is to fix some typo in external/kafka/src/main/scala/org/apache/spark/streaming/kafka/OffsetRange.scala
Author: microwishing <wei.zhu@kaiyuandao.com>
Closes#10121 from microwishing/master.
Sometimes, EmbeddedZookeeper may need more than 6 seconds to setup up in a slow Jenkins worker. So just increase the timeout, it won't increase the test time if the test passes.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#9778 from zsxwing/SPARK-11790.
This PR just checks the test results and returns 1 if the test fails, so that `run-tests.py` can mark it fail.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes#9669 from zsxwing/streaming-python-tests.
Currently, when a DStream sets the scope for RDD generated by it, that scope is not allowed to be overridden by the RDD operations. So in case of `DStream.foreachRDD`, all the RDDs generated inside the foreachRDD get the same scope - `foreachRDD <time>`, as set by the `ForeachDStream`. So it is hard to debug generated RDDs in the RDD DAG viz in the Spark UI.
This patch allows the RDD operations inside `DStream.transform` and `DStream.foreachRDD` to append their own scopes to the earlier DStream scope.
I have also slightly tweaked how callsites are set such that the short callsite reflects the RDD operation name and line number. This tweak is necessary as callsites are not managed through scopes (which support nesting and overriding) and I didnt want to add another local property to control nesting and overriding of callsites.
## Before:
## After:
The code that was used to generate this is:
```
val lines = ssc.socketTextStream(args(0), args(1).toInt, StorageLevel.MEMORY_AND_DISK_SER)
val words = lines.flatMap(_.split(" "))
val wordCounts = words.map(x => (x, 1)).reduceByKey(_ + _)
wordCounts.foreachRDD { rdd =>
val temp = rdd.map { _ -> 1 }.reduceByKey( _ + _)
val temp2 = temp.map { _ -> 1}.reduceByKey(_ + _)
val count = temp2.count
println(count)
}
```
Note
- The inner scopes of the RDD operations map/reduceByKey inside foreachRDD is visible
- The short callsites of stages refers to the line number of the RDD ops rather than the same line number of foreachRDD in all three cases.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#9315 from tdas/SPARK-11361.
…reads.
Wait for a minute for the receiver threads to shutdown before interrupting them.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#9041 from harishreedharan/flume-graceful-shutdown.
This change does two things:
- tag a few tests and adds the mechanism in the build to be able to disable those tags,
both in maven and sbt, for both junit and scalatest suites.
- add some logic to run-tests.py to disable some tags depending on what files have
changed; that's used to disable expensive tests when a module hasn't explicitly
been changed, to speed up testing for changes that don't directly affect those
modules.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#8437 from vanzin/test-tags.
Fix a few Java API test style issues: unused generic types, exceptions, wrong assert argument order
Author: Sean Owen <sowen@cloudera.com>
Closes#8706 from srowen/SPARK-10547.
The bulk of the changes are on `transient` annotation on class parameter. Often the compiler doesn't generate a field for this parameters, so the the transient annotation would be unnecessary.
But if the class parameter are used in methods, then fields are created. So it is safer to keep the annotations.
The remainder are some potential bugs, and deprecated syntax.
Author: Luc Bourlier <luc.bourlier@typesafe.com>
Closes#8433 from skyluc/issue/sbt-2.11.
Replace `JavaConversions` implicits with `JavaConverters`
Most occurrences I've seen so far are necessary conversions; a few have been avoidable. None are in critical code as far as I see, yet.
Author: Sean Owen <sowen@cloudera.com>
Closes#8033 from srowen/SPARK-9613.
In addition, some random cleanup of import ordering
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#8387 from tdas/SPARK-9791 and squashes the following commits:
67f3ee9 [Tathagata Das] Change private class to private[package] class to prevent them from showing up in the docs
This PR removed the `outputFile` configuration from pom.xml and updated `tests.py` to search jars for both sbt build and maven build.
I ran ` mvn -Pkinesis-asl -DskipTests clean install` locally, and verified the jars in my local repository were correct. I also checked Python tests for maven build, and it passed all tests.
Author: zsxwing <zsxwing@gmail.com>
Closes#8373 from zsxwing/SPARK-10168 and squashes the following commits:
e0b5818 [zsxwing] Fix the sbt build
c697627 [zsxwing] Add the jar pathes to the exception message
be1d8a5 [zsxwing] Fix the issue that maven publishes wrong artifact jars
Removed contents already included in Spark assembly jar from spark-streaming-XXX-assembly jars.
Author: zsxwing <zsxwing@gmail.com>
Closes#8069 from zsxwing/SPARK-9574.
…fails
Author: cody koeninger <cody@koeninger.org>
Closes#8133 from koeninger/SPARK-9780 and squashes the following commits:
406259d [cody koeninger] [SPARK-9780][Streaming][Kafka] prevent NPE if KafkaRDD instantiation fails
This PR is based on #4229, thanks prabeesh.
Closes#4229
Author: Prabeesh K <prabsmails@gmail.com>
Author: zsxwing <zsxwing@gmail.com>
Author: prabs <prabsmails@gmail.com>
Author: Prabeesh K <prabeesh.k@namshi.com>
Closes#7833 from zsxwing/pr4229 and squashes the following commits:
9570bec [zsxwing] Fix the variable name and check null in finally
4a9c79e [zsxwing] Fix pom.xml indentation
abf5f18 [zsxwing] Merge branch 'master' into pr4229
935615c [zsxwing] Fix the flaky MQTT tests
47278c5 [zsxwing] Include the project class files
478f844 [zsxwing] Add unpack
5f8a1d4 [zsxwing] Make the maven build generate the test jar for Python MQTT tests
734db99 [zsxwing] Merge branch 'master' into pr4229
126608a [Prabeesh K] address the comments
b90b709 [Prabeesh K] Merge pull request #1 from zsxwing/pr4229
d07f454 [zsxwing] Register StreamingListerner before starting StreamingContext; Revert unncessary changes; fix the python unit test
a6747cb [Prabeesh K] wait for starting the receiver before publishing data
87fc677 [Prabeesh K] address the comments:
97244ec [zsxwing] Make sbt build the assembly test jar for streaming mqtt
80474d1 [Prabeesh K] fix
1f0cfe9 [Prabeesh K] python style fix
e1ee016 [Prabeesh K] scala style fix
a5a8f9f [Prabeesh K] added Python test
9767d82 [Prabeesh K] implemented Python-friendly class
a11968b [Prabeesh K] fixed python style
795ec27 [Prabeesh K] address comments
ee387ae [Prabeesh K] Fix assembly jar location of mqtt-assembly
3f4df12 [Prabeesh K] updated version
b34c3c1 [prabs] adress comments
3aa7fff [prabs] Added Python streaming mqtt word count example
b7d42ff [prabs] Mqtt streaming support in Python
…tually visible
Author: cody koeninger <cody@koeninger.org>
Closes#7995 from koeninger/doc-fixes and squashes the following commits:
87af9ea [cody koeninger] [Docs][Streaming] make the existing parameter docs for OffsetRange actually visible
In some receivers, instead of using the default `BlockGenerator` in `ReceiverSupervisorImpl`, custom generator with their custom listeners are used for reliability (see [`ReliableKafkaReceiver`](https://github.com/apache/spark/blob/master/external/kafka/src/main/scala/org/apache/spark/streaming/kafka/ReliableKafkaReceiver.scala#L99) and [updated `KinesisReceiver`](https://github.com/apache/spark/pull/7825/files)). These custom generators do not receive rate updates. This PR modifies the code to allow custom `BlockGenerator`s to be created through the `ReceiverSupervisorImpl` so that they can be kept track and rate updates can be applied.
In the process, I did some simplification, and de-flaki-fication of some rate controller related tests. In particular.
- Renamed `Receiver.executor` to `Receiver.supervisor` (to match `ReceiverSupervisor`)
- Made `RateControllerSuite` faster (by increasing batch interval) and less flaky
- Changed a few internal API to return the current rate of block generators as Long instead of Option\[Long\] (was inconsistent at places).
- Updated existing `ReceiverTrackerSuite` to test that custom block generators get rate updates as well.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#7913 from tdas/SPARK-9556 and squashes the following commits:
41d4461 [Tathagata Das] fix scala style
eb9fd59 [Tathagata Das] Updated kinesis receiver
d24994d [Tathagata Das] Updated BlockGeneratorSuite to use manual clock in BlockGenerator
d70608b [Tathagata Das] Updated BlockGenerator with states and proper synchronization
f6bd47e [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-9556
31da173 [Tathagata Das] Fix bug
12116df [Tathagata Das] Add BlockGeneratorSuite
74bd069 [Tathagata Das] Fix style
989bb5c [Tathagata Das] Made BlockGenerator fail is used after stop, and added better unit tests for it
3ff618c [Tathagata Das] Fix test
b40eff8 [Tathagata Das] slight refactoring
f0df0f1 [Tathagata Das] Scala style fixes
51759cb [Tathagata Das] Refactored rate controller tests and added the ability to update rate of any custom block generator
Author: Dean Wampler <dean@concurrentthought.com>
Author: Nilanjan Raychaudhuri <nraychaudhuri@gmail.com>
Author: François Garillot <francois@garillot.net>
Closes#7796 from dragos/topic/streaming-bp/kafka-direct and squashes the following commits:
50d1f21 [Nilanjan Raychaudhuri] Taking care of the remaining nits
648c8b1 [Dean Wampler] Refactored rate controller test to be more predictable and run faster.
e43f678 [Nilanjan Raychaudhuri] fixing doc and nits
ce19d2a [Dean Wampler] Removing an unreliable assertion.
9615320 [Dean Wampler] Give me a break...
6372478 [Dean Wampler] Found a few ways to make this test more robust...
9e69e37 [Dean Wampler] Attempt to fix flakey test that fails in CI, but not locally :(
d3db1ea [Dean Wampler] Fixing stylecheck errors.
d04a288 [Nilanjan Raychaudhuri] adding test to make sure rate controller is used to calculate maxMessagesPerPartition
b6ecb67 [Nilanjan Raychaudhuri] Fixed styling issue
3110267 [Nilanjan Raychaudhuri] [SPARK-8978][Streaming] Implements the DirectKafkaRateController
393c580 [François Garillot] [SPARK-8978][Streaming] Implements the DirectKafkaRateController
51e78c6 [Nilanjan Raychaudhuri] Rename and fix build failure
2795509 [Nilanjan Raychaudhuri] Added missing RateController
19200f5 [Dean Wampler] Removed usage of infix notation. Changed a private variable name to be more consistent with usage.
aa4a70b [François Garillot] [SPARK-8978][Streaming] Implements the DirectKafkaController
Enable most javac lint warnings; fix a lot of build warnings. In a few cases, touch up surrounding code in the process.
I'll explain several of the changes inline in comments.
Author: Sean Owen <sowen@cloudera.com>
Closes#7862 from srowen/SPARK-9534 and squashes the following commits:
ea51618 [Sean Owen] Enable most javac lint warnings; fix a lot of build warnings. In a few cases, touch up surrounding code in the process.
Spark has an option called spark.localExecution.enabled; according to the docs:
> Enables Spark to run certain jobs, such as first() or take() on the driver, without sending tasks to the cluster. This can make certain jobs execute very quickly, but may require shipping a whole partition of data to the driver.
This feature ends up adding quite a bit of complexity to DAGScheduler, especially in the runLocallyWithinThread method, but as far as I know nobody uses this feature (I searched the mailing list and haven't seen any recent mentions of the configuration nor stacktraces including the runLocally method). As a step towards scheduler complexity reduction, I propose that we remove this feature and all code related to it for Spark 1.5.
This pull request simply brings #7484 up to date.
Author: Josh Rosen <joshrosen@databricks.com>
Author: Reynold Xin <rxin@databricks.com>
Closes#7585 from rxin/remove-local-exec and squashes the following commits:
84bd10e [Reynold Xin] Python fix.
1d9739a [Reynold Xin] Merge pull request #7484 from JoshRosen/remove-localexecution
eec39fa [Josh Rosen] Remove allowLocal(); deprecate user-facing uses of it.
b0835dc [Josh Rosen] Remove local execution code in DAGScheduler
8975d96 [Josh Rosen] Remove local execution tests.
ffa8c9b [Josh Rosen] Remove documentation for configuration
This pull request adds a Scalastyle regex rule which fails the style check if `Class.forName` is used directly. `Class.forName` always loads classes from the default / system classloader, but in a majority of cases, we should be using Spark's own `Utils.classForName` instead, which tries to load classes from the current thread's context classloader and falls back to the classloader which loaded Spark when the context classloader is not defined.
<!-- Reviewable:start -->
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Author: Josh Rosen <joshrosen@databricks.com>
Closes#7350 from JoshRosen/ban-Class.forName and squashes the following commits:
e3e96f7 [Josh Rosen] Merge remote-tracking branch 'origin/master' into ban-Class.forName
c0b7885 [Josh Rosen] Hopefully fix the last two cases
d707ba7 [Josh Rosen] Fix uses of Class.forName that I missed in my first cleanup pass
046470d [Josh Rosen] Merge remote-tracking branch 'origin/master' into ban-Class.forName
62882ee [Josh Rosen] Fix uses of Class.forName or add exclusion.
d9abade [Josh Rosen] Add stylechecker rule to ban uses of Class.forName
Author: Jonathan Alter <jonalter@users.noreply.github.com>
Closes#7093 from jonalter/SPARK-7977 and squashes the following commits:
ccd44cc [Jonathan Alter] Changed println to log in ThreadingSuite
7fcac3e [Jonathan Alter] Reverting to println in ThreadingSuite
10724b6 [Jonathan Alter] Changing some printlns to logs in tests
eeec1e7 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
0b1dcb4 [Jonathan Alter] More println cleanup
aedaf80 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
925fd98 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
0c16fa3 [Jonathan Alter] Replacing some printlns with logs
45c7e05 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
5c8e283 [Jonathan Alter] Allowing println in audit-release examples
5b50da1 [Jonathan Alter] Allowing printlns in example files
ca4b477 [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
83ab635 [Jonathan Alter] Fixing new printlns
54b131f [Jonathan Alter] Merge branch 'master' of github.com:apache/spark into SPARK-7977
1cd8a81 [Jonathan Alter] Removing some unnecessary comments and printlns
b837c3a [Jonathan Alter] Disallowing println
Also, add support for the *-provided profiles. This avoids repackaging
things that are already in the Spark assembly, or, in the case of the
*-provided profiles, are provided by the distribution.
The flume-ng-auth dependency was also excluded since it's not really
used by Spark.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#7247 from vanzin/SPARK-8852 and squashes the following commits:
298a7d5 [Marcelo Vanzin] Feedback.
c962082 [Marcelo Vanzin] [SPARK-8852] [flume] Trim dependencies in flume assembly.
This PR propose a simple way to expose OffsetRange in Python code, also the usage of offsetRanges is similar to Scala/Java way, here in Python we could get OffsetRange like:
```
dstream.foreachRDD(lambda r: KafkaUtils.offsetRanges(r))
```
Reason I didn't follow the way what SPARK-8389 suggested is that: Python Kafka API has one more step to decode the message compared to Scala/Java, Which makes Python API return a transformed RDD/DStream, not directly wrapped so-called JavaKafkaRDD, so it is hard to backtrack to the original RDD to get the offsetRange.
Author: jerryshao <saisai.shao@intel.com>
Closes#7185 from jerryshao/SPARK-8389 and squashes the following commits:
4c6d320 [jerryshao] Another way to fix subclass deserialization issue
e6a8011 [jerryshao] Address the comments
fd13937 [jerryshao] Fix serialization bug
7debf1c [jerryshao] bug fix
cff3893 [jerryshao] refactor the code according to the comments
2aabf9e [jerryshao] Style fix
848c708 [jerryshao] Add HasOffsetRanges for Python
This PR adds `metadata` to `InputInfo`. `InputDStream` can report its metadata for a batch and it will be shown in the batch page.
For example,
FileInputDStream will display the new files for a batch, and DirectKafkaInputDStream will display its offset ranges.
Author: zsxwing <zsxwing@gmail.com>
Closes#7081 from zsxwing/input-metadata and squashes the following commits:
f7abd9b [zsxwing] Revert the space changes in project/MimaExcludes.scala
d906209 [zsxwing] Merge branch 'master' into input-metadata
74762da [zsxwing] Fix MiMa tests
7903e33 [zsxwing] Merge branch 'master' into input-metadata
450a46c [zsxwing] Address comments
1d94582 [zsxwing] Raname InputInfo to StreamInputInfo and change "metadata" to Map[String, Any]
d496ae9 [zsxwing] Add input metadata in the batch page
To fix Spark Streaming unit test with maven build. Previously the name and path of maven generated jar is different from sbt, which will lead to following exception. This fix keep the same behavior with both Maven and sbt build.
```
Failed to find Spark Streaming Kafka assembly jar in /home/xyz/spark/external/kafka-assembly
You need to build Spark with 'build/sbt assembly/assembly streaming-kafka-assembly/assembly' or 'build/mvn package' before running this program
```
Author: jerryshao <saisai.shao@intel.com>
Closes#5632 from jerryshao/SPARK-7050 and squashes the following commits:
74b068d [jerryshao] Fix mvn build issue
Author: zsxwing <zsxwing@gmail.com>
Closes#6830 from zsxwing/flume-python and squashes the following commits:
78dfdac [zsxwing] Fix the compile error in the test code
f1bf3c0 [zsxwing] Address TD's comments
0449723 [zsxwing] Add sbt goal streaming-flume-assembly/assembly
e93736b [zsxwing] Fix the test case for determine_modules_to_test
9d5821e [zsxwing] Fix pyspark_core dependencies
f9ee681 [zsxwing] Merge branch 'master' into flume-python
7a55837 [zsxwing] Add streaming_flume_assembly to run-tests.py
b96b0de [zsxwing] Merge branch 'master' into flume-python
ce85e83 [zsxwing] Fix incompatible issues for Python 3
01cbb3d [zsxwing] Add import sys
152364c [zsxwing] Fix the issue that StringIO doesn't work in Python 3
14ba0ff [zsxwing] Add flume-assembly for sbt building
b8d5551 [zsxwing] Merge branch 'master' into flume-python
4762c34 [zsxwing] Fix the doc
0336579 [zsxwing] Refactor Flume unit tests and also add tests for Python API
9f33873 [zsxwing] Add the Python API for Flume
…nk. Also bump Flume version to 1.6.0
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#6910 from harishreedharan/remove-commons-lang3 and squashes the following commits:
9875f7d [Hari Shreedharan] Revert back to Flume 1.4.0
ca35eb0 [Hari Shreedharan] [SPARK-8483][Streaming] Remove commons-lang3 dependency from Flume Sink. Also bump Flume version to 1.6.0
…ed KafkaRDD methods. Possible fix for [SPARK-7122], but probably a worthwhile optimization regardless.
Author: cody koeninger <cody@koeninger.org>
Closes#6632 from koeninger/kafka-rdd-count and squashes the following commits:
321340d [cody koeninger] [SPARK-8127][Streaming][Kafka] additional test of ordering of take()
5a05d0f [cody koeninger] [SPARK-8127][Streaming][Kafka] additional test of isEmpty
f68bd32 [cody koeninger] [Streaming][Kafka][SPARK-8127] code cleanup
9555b73 [cody koeninger] Merge branch 'master' into kafka-rdd-count
253031d [cody koeninger] [Streaming][Kafka][SPARK-8127] mima exclusion for change to private method
8974b9e [cody koeninger] [Streaming][Kafka][SPARK-8127] check offset ranges before constructing KafkaRDD
c3768c5 [cody koeninger] [Streaming][Kafka] Take advantage of offset range info for size-related KafkaRDD methods. Possible fix for [SPARK-7122], but probably a worthwhile optimization regardless.
Author: cody koeninger <cody@koeninger.org>
Closes#6863 from koeninger/SPARK-8390 and squashes the following commits:
26a06bd [cody koeninger] Merge branch 'master' into SPARK-8390
3744492 [cody koeninger] [Streaming][Kafka][SPARK-8390] doc changes per TD, test to make sure approach shown in docs actually compiles + runs
b108c9d [cody koeninger] [Streaming][Kafka][SPARK-8390] further doc fixes, clean up spacing
bb4336b [cody koeninger] [Streaming][Kafka][SPARK-8390] fix docs related to HasOffsetRanges, cleanup
3f3c57a [cody koeninger] [Streaming][Kafka][SPARK-8389] Example of getting offset ranges out of the existing java direct stream api
…f the existing java direct stream api
Author: cody koeninger <cody@koeninger.org>
Closes#6846 from koeninger/SPARK-8389 and squashes the following commits:
3f3c57a [cody koeninger] [Streaming][Kafka][SPARK-8389] Example of getting offset ranges out of the existing java direct stream api
KafkaStreamSuite, DirectKafkaStreamSuite, JavaKafkaStreamSuite and JavaDirectKafkaStreamSuite use non-thread-safe collections to collect data in one thread and check it in another thread. It may fail the tests.
This PR changes them to thread-safe collections.
Note: I cannot reproduce the test failures in my environment. But at least, this PR should make the tests more reliable.
Author: zsxwing <zsxwing@gmail.com>
Closes#6852 from zsxwing/fix-KafkaStreamSuite and squashes the following commits:
d464211 [zsxwing] Use thread-safe collections to make the tests more reliable
see if requiring producer acks eliminates the need for waitUntilLeaderOffset calls in tests
Author: cody koeninger <cody@koeninger.org>
Closes#5921 from koeninger/kafka-0.8.2-test-cleanup and squashes the following commits:
1e89dc8 [cody koeninger] Merge branch 'master' into kafka-0.8.2-test-cleanup
4662828 [cody koeninger] [Streaming][Kafka] filter mima issue for removal of method from private test class
af1e083 [cody koeninger] Merge branch 'master' into kafka-0.8.2-test-cleanup
4298ac2 [cody koeninger] [Streaming][Kafka] update comment to trigger jenkins attempt
1274afb [cody koeninger] [Streaming][Kafka] see if requiring producer acks eliminates the need for waitUntilLeaderOffset calls in tests
Author: Patrick Wendell <patrick@databricks.com>
Closes#6328 from pwendell/spark-1.5-update and squashes the following commits:
2f42d02 [Patrick Wendell] A few more excludes
4bebcf0 [Patrick Wendell] Update to RC4
61aaf46 [Patrick Wendell] Using new release candidate
55f1610 [Patrick Wendell] Another exclude
04b4f04 [Patrick Wendell] More issues with transient 1.4 changes
36f549b [Patrick Wendell] [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0
The minimal change would be to disable shading of Guava in the module,
and rely on the transitive dependency from other libraries instead. But
since Guava's use is so localized, I think it's better to just not use
it instead, so I replaced that code and removed all traces of Guava from
the module's build.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#6555 from vanzin/SPARK-8015 and squashes the following commits:
c0ceea8 [Marcelo Vanzin] Add comments about dependency management.
c38228d [Marcelo Vanzin] Add guava dep in test scope.
b7a0349 [Marcelo Vanzin] Add libthrift exclusion.
6e0942d [Marcelo Vanzin] Add comment in pom.
2d79260 [Marcelo Vanzin] [SPARK-8015] [flume] Remove Guava dependency from flume-sink.
This is a follow-up patch to #6441.
Author: Andrew Or <andrew@databricks.com>
Closes#6510 from andrewor14/extends-funsuite-check and squashes the following commits:
6618b46 [Andrew Or] Exempt SparkSinkSuite from the FunSuite check
99d02ac [Andrew Or] Merge branch 'master' of github.com:apache/spark into extends-funsuite-check
48874dd [Andrew Or] Guard against direct uses of FunSuite / FunSuiteLike
This patch fixes a build break in maven caused by #6441.
Note that this patch reverts the changes in flume-sink because
this module does not currently depend on Spark core, but the
tests require it. There is not an easy way to make this work
because mvn test dependencies are not transitive (MNG-1378).
For now, we will leave the one test suite in flume-sink out
until we figure out a better solution. This patch is mainly
intended to unbreak the maven build.
Author: Andrew Or <andrew@databricks.com>
Closes#6511 from andrewor14/fix-build-mvn and squashes the following commits:
3d53643 [Andrew Or] [HOT FIX#6441] Fix maven build failures
Right now `unit-tests.log` are not of much value because we can't tell where the test boundaries are easily. This patch adds log statements before and after each test to outline the test boundaries, e.g.:
```
===== TEST OUTPUT FOR o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' =====
15/05/27 12:36:39.596 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO SparkContext: Starting job: count at KryoSerializerSuite.scala:230
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Got job 3 (count at KryoSerializerSuite.scala:230) with 4 output partitions (allowLocal=false)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Final stage: ResultStage 3(count at KryoSerializerSuite.scala:230)
15/05/27 12:36:39.596 dag-scheduler-event-loop INFO DAGScheduler: Parents of final stage: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Missing parents: List()
15/05/27 12:36:39.597 dag-scheduler-event-loop INFO DAGScheduler: Submitting ResultStage 3 (ParallelCollectionRDD[5] at parallelize at KryoSerializerSuite.scala:230), which has no missing parents
...
15/05/27 12:36:39.624 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO DAGScheduler: Job 3 finished: count at KryoSerializerSuite.scala:230, took 0.028563 s
15/05/27 12:36:39.625 pool-1-thread-1-ScalaTest-running-KryoSerializerSuite INFO KryoSerializerSuite:
***** FINISHED o.a.s.serializer.KryoSerializerSuite: 'kryo with parallelize for primitive arrays' *****
...
```
Author: Andrew Or <andrew@databricks.com>
Closes#6441 from andrewor14/demarcate-tests and squashes the following commits:
879b060 [Andrew Or] Fix compile after rebase
d622af7 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
017c8ba [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
7790b6c [Andrew Or] Fix tests after logical merge conflict
c7460c0 [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
c43ffc4 [Andrew Or] Fix tests?
8882581 [Andrew Or] Fix tests
ee22cda [Andrew Or] Fix log message
fa9450e [Andrew Or] Merge branch 'master' of github.com:apache/spark into demarcate-tests
12d1e1b [Andrew Or] Various whitespace changes (minor)
69cbb24 [Andrew Or] Make all test suites extend SparkFunSuite instead of FunSuite
bbce12e [Andrew Or] Fix manual things that cannot be covered through automation
da0b12f [Andrew Or] Add core tests as dependencies in all modules
f7d29ce [Andrew Or] Introduce base abstract class for all test suites
PR per [SPARK-7621](https://issues.apache.org/jira/browse/SPARK-7621), which makes both `KafkaReceiver` and `ReliableKafkaReceiver` report its errors to the `ReceiverTracker`, which in turn will add the events to the bus to fire off any registered `StreamingListener`s.
Author: jerluc <jeremyalucas@gmail.com>
Closes#6204 from jerluc/master and squashes the following commits:
82439a5 [jerluc] [SPARK-7621] [STREAMING] Report Kafka errors to StreamingListeners
This is similar to #5999, but for streaming. Roughly 200 lines are tests.
One thing to note here is that we already do some kind of scoping thing for call sites, so this patch adds the new RDD operation scoping logic in the same place. Also, this patch adds a `try finally` block to set the relevant variables in a safer way.
tdas zsxwing
------------------------
**Before**
<img src="https://cloud.githubusercontent.com/assets/2133137/7625996/d88211b8-f9b4-11e4-90b9-e11baa52d6d7.png" width="450px"/>
--------------------------
**After**
<img src="https://cloud.githubusercontent.com/assets/2133137/7625997/e0878f8c-f9b4-11e4-8df3-7dd611b13c87.png" width="650px"/>
Author: Andrew Or <andrew@databricks.com>
Closes#6034 from andrewor14/dag-viz-streaming and squashes the following commits:
932a64a [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
e685df9 [Andrew Or] Rename createRDDWith
84d0656 [Andrew Or] Review feedback
697c086 [Andrew Or] Fix tests
53b9936 [Andrew Or] Set scopes for foreachRDD properly
1881802 [Andrew Or] Refactor DStream scope names again
af4ba8d [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
fd07d22 [Andrew Or] Make MQTT lower case
f6de871 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
0ca1801 [Andrew Or] Remove a few unnecessary withScopes on aliases
fa4e5fb [Andrew Or] Pass in input stream name rather than defining it from within
1af0b0e [Andrew Or] Fix style
074c00b [Andrew Or] Review comments
d25a324 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
e4a93ac [Andrew Or] Fix tests?
25416dc [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
9113183 [Andrew Or] Add tests for DStream scopes
b3806ab [Andrew Or] Fix test
bb80bbb [Andrew Or] Fix MIMA?
5c30360 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
5703939 [Andrew Or] Rename operations that create InputDStreams
7c4513d [Andrew Or] Group RDDs by DStream operations and batches
bf0ab6e [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
05c2676 [Andrew Or] Wrap many more methods in withScope
c121047 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-streaming
65ef3e9 [Andrew Or] Fix NPE
a0d3263 [Andrew Or] Scope streaming operations instead of RDD operations
This is meant to make the FlumePollingStreamSuite deterministic. Now we basically count the number of batches that have been completed - and then verify the results rather than sleeping for random periods of time.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#5918 from harishreedharan/flume-test-fix and squashes the following commits:
93f24f3 [Hari Shreedharan] Add an eventually block to ensure that all received data is processed. Refactor the dstream creation and remove redundant code.
1108804 [Hari Shreedharan] [SPARK-7356][STREAMING] Fix flakey tests in FlumePollingStreamSuite using SparkSink's batch CountDownLatch.
Author: jerryshao <saisai.shao@intel.com>
Closes#5879 from jerryshao/SPARK-7113 and squashes the following commits:
b0b506c [jerryshao] Address the comments
0babe66 [jerryshao] Support input information reporting for Direct Kafka stream
i don't think this should be merged until after 1.3.0 is final
Author: cody koeninger <cody@koeninger.org>
Author: Helena Edelson <helena.edelson@datastax.com>
Closes#4537 from koeninger/wip-2808-kafka-0.8.2-upgrade and squashes the following commits:
803aa2c [cody koeninger] [SPARK-2808][Streaming][Kafka] code cleanup per TD
e6dfaf6 [cody koeninger] [SPARK-2808][Streaming][Kafka] pointless whitespace change to trigger jenkins again
1770abc [cody koeninger] [SPARK-2808][Streaming][Kafka] make waitUntilLeaderOffset easier to call, call it from python tests as well
d4267e9 [cody koeninger] [SPARK-2808][Streaming][Kafka] fix stderr redirect in python test script
30d991d [cody koeninger] [SPARK-2808][Streaming][Kafka] remove stderr prints since it breaks python 3 syntax
1d896e2 [cody koeninger] [SPARK-2808][Streaming][Kafka] add even even more logging to python test
4c4557f [cody koeninger] [SPARK-2808][Streaming][Kafka] add even more logging to python test
115aeee [cody koeninger] Merge branch 'master' into wip-2808-kafka-0.8.2-upgrade
2712649 [cody koeninger] [SPARK-2808][Streaming][Kafka] add more logging to python test, see why its timing out in jenkins
2b92d3f [cody koeninger] [SPARK-2808][Streaming][Kafka] wait for leader offsets in the java test as well
3824ce3 [cody koeninger] [SPARK-2808][Streaming][Kafka] naming / comments per tdas
61b3464 [cody koeninger] [SPARK-2808][Streaming][Kafka] delay for second send in boundary condition test
af6f3ec [cody koeninger] [SPARK-2808][Streaming][Kafka] delay test until latest leader offset matches expected value
9edab4c [cody koeninger] [SPARK-2808][Streaming][Kafka] more shots in the dark on jenkins failing test
c70ee43 [cody koeninger] [SPARK-2808][Streaming][Kafka] add more asserts to test, try to figure out why it fails on jenkins but not locally
1d10751 [cody koeninger] Merge branch 'master' into wip-2808-kafka-0.8.2-upgrade
ed02d2c [cody koeninger] [SPARK-2808][Streaming][Kafka] move default argument for api version to overloaded method, for binary compat
407382e [cody koeninger] [SPARK-2808][Streaming][Kafka] update kafka to 0.8.2.1
77de6c2 [cody koeninger] Merge branch 'master' into wip-2808-kafka-0.8.2-upgrade
6953429 [cody koeninger] [SPARK-2808][Streaming][Kafka] update kafka to 0.8.2
2e67c66 [Helena Edelson] #SPARK-2808 Update to Kafka 0.8.2.0 GA from beta.
d9dc2bc [Helena Edelson] Merge remote-tracking branch 'upstream/master' into wip-2808-kafka-0.8.2-upgrade
e768164 [Helena Edelson] #2808 update kafka to version 0.8.2
Users may want the WAL data to be written to non-HDFS data storage systems. To allow that, we have to make the WAL pluggable. The following design doc outlines the plan.
https://docs.google.com/a/databricks.com/document/d/1A2XaOLRFzvIZSi18i_luNw5Rmm9j2j4AigktXxIYxmY/edit?usp=sharing
Things to add.
* Unit tests for WriteAheadLogUtils
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#5645 from tdas/wal-pluggable and squashes the following commits:
2c431fd [Tathagata Das] Minor fixes.
c2bc7384 [Tathagata Das] More changes based on PR comments.
569a416 [Tathagata Das] fixed long line
bde26b1 [Tathagata Das] Renamed segment to record handle everywhere
b65e155 [Tathagata Das] More changes based on PR comments.
d7cd15b [Tathagata Das] Fixed test
1a32a4b [Tathagata Das] Fixed test
e0d19fb [Tathagata Das] Fixed defaults
9310cbf [Tathagata Das] style fix.
86abcb1 [Tathagata Das] Refactored WriteAheadLogUtils, and consolidated all WAL related configuration into it.
84ce469 [Tathagata Das] Added unit test and fixed compilation error.
bce5e75 [Tathagata Das] Fixed long lines.
837c4f5 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into wal-pluggable
754fbf8 [Tathagata Das] Added license and docs.
09bc6fe [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into wal-pluggable
7dd2d4b [Tathagata Das] Added pluggable WriteAheadLog interface, and refactored all code along with it
Currently only added `createDirectStream` API, I'm not sure if `createRDD` is also needed, since some Java object needs to be wrapped in Python. Please help to review, thanks a lot.
Author: jerryshao <saisai.shao@intel.com>
Author: Saisai Shao <saisai.shao@intel.com>
Closes#4723 from jerryshao/direct-kafka-python-api and squashes the following commits:
a1fe97c [jerryshao] Fix rebase issue
eebf333 [jerryshao] Address the comments
da40f4e [jerryshao] Fix Python 2.6 Syntax error issue
5c0ee85 [jerryshao] Style fix
4aeac18 [jerryshao] Fix bug in example code
7146d86 [jerryshao] Add unit test
bf3bdd6 [jerryshao] Add more APIs and address the comments
f5b3801 [jerryshao] Small style fix
8641835 [Saisai Shao] Rebase and update the code
589c05b [Saisai Shao] Fix the style
d6fcb6a [Saisai Shao] Address the comments
dfda902 [Saisai Shao] Style fix
0f7d168 [Saisai Shao] Add the doc and fix some style issues
67e6880 [Saisai Shao] Fix test bug
917b0db [Saisai Shao] Add Python createRDD API for Kakfa direct stream
c3fc11d [jerryshao] Modify the docs
2c00936 [Saisai Shao] address the comments
3360f44 [jerryshao] Fix code style
e0e0f0d [jerryshao] Code clean and bug fix
338c41f [Saisai Shao] Add python API and example for direct kafka stream
Remove use of commons-lang in favor of commons-lang3 classes; remove commons-io use in favor of Guava
Author: Sean Owen <sowen@cloudera.com>
Closes#5703 from srowen/SPARK-7145 and squashes the following commits:
21fbe03 [Sean Owen] Remove use of commons-lang in favor of commons-lang3 classes; remove commons-io use in favor of Guava
As per rxin 's suggestion in https://github.com/apache/spark/pull/5392/files#r28757176
What's more, there is a race condition in the global shared `daemonThreadFactoryBuilder`. `daemonThreadFactoryBuilder` may be modified by multiple threads. This PR removed the global `daemonThreadFactoryBuilder` and created a new `ThreadFactoryBuilder` every time.
Author: zsxwing <zsxwing@gmail.com>
Closes#5631 from zsxwing/thread-utils and squashes the following commits:
9fe5b0e [zsxwing] Add ThreadUtils and move thread methods from Utils to ThreadUtils
...ests
The original reported problem was misdiagnosed; the topic just didn't exist yet. Agreed upon solution was to improve error handling / message
Author: cody koeninger <cody@koeninger.org>
Closes#5454 from koeninger/spark-6431-master and squashes the following commits:
44300f8 [cody koeninger] [SPARK-6431][Streaming][Kafka] Error message for partition metadata requests
Refactor the Kafka unit test and add Python API support. CC tdas davies please help to review, thanks a lot.
Author: jerryshao <saisai.shao@intel.com>
Author: Saisai Shao <saisai.shao@intel.com>
Closes#4961 from jerryshao/SPARK-6211 and squashes the following commits:
ee4b919 [jerryshao] Fixed newly merged issue
82c756e [jerryshao] Address the comments
92912d1 [jerryshao] Address the commits
0708bb1 [jerryshao] Fix rebase issue
40b47a3 [Saisai Shao] Style fix
f889657 [Saisai Shao] Update the code according
8a2f3e2 [jerryshao] Address the issues
0f1b7ce [jerryshao] Still fix the bug
61a04f0 [jerryshao] Fix bugs and address the issues
64d9877 [jerryshao] Fix rebase bugs
8ad442f [jerryshao] Add kafka-assembly in run-tests
6020b00 [jerryshao] Add more debug info in Shell
8102d6e [jerryshao] Fix bug in Jenkins test
fde1213 [jerryshao] Code style changes
5536f95 [jerryshao] Refactor the Kafka unit test and add Python Kafka unittest support
https://issues.apache.org/jira/browse/SPARK-6758
I am not sure if it is ok to block them in test resources too (as we shade jetty in assembly?).
Author: WangTaoTheTonic <wangtao111@huawei.com>
Closes#5406 from WangTaoTheTonic/SPARK-6758 and squashes the following commits:
e09605b [WangTaoTheTonic] block the right jetty package
So we can turn style checker on for test code.
Author: Reynold Xin <rxin@databricks.com>
Closes#5409 from rxin/test-style-streaming and squashes the following commits:
7aea69b [Reynold Xin] [SPARK-6765] Fix test code style for streaming.
Reduce "is the same as ending offset" message to INFO level per JIRA discussion
Author: Sean Owen <sowen@cloudera.com>
Closes#5366 from srowen/SPARK-6569 and squashes the following commits:
8a5b992 [Sean Owen] Reduce "is the same as ending offset" message to INFO level per JIRA discussion
This builds on my earlier pull requests and turns on the explicit type checking in scalastyle.
Author: Reynold Xin <rxin@databricks.com>
Closes#5342 from rxin/SPARK-6428 and squashes the following commits:
7b531ab [Reynold Xin] import ordering
2d9a8a5 [Reynold Xin] jl
e668b1c [Reynold Xin] override
9b9e119 [Reynold Xin] Parenthesis.
82e0cf5 [Reynold Xin] [SPARK-6428] Turn on explicit type checking for public methods.
When we run FlumeStreamSuite on Jenkins, sometimes we get error like as follows.
sbt.ForkMain$ForkError: The code passed to eventually never returned normally. Attempted 52 times over 10.094849836 seconds. Last failure message: Error connecting to localhost/127.0.0.1:23456.
at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:420)
at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438)
at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:307)
at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
at org.apache.spark.streaming.flume.FlumeStreamSuite.writeAndVerify(FlumeStreamSuite.scala:116)
at org.apache.spark.streaming.flume.FlumeStreamSuite.org$apache$spark$streaming$flume$FlumeStreamSuite$$testFlumeStream(FlumeStreamSuite.scala:74)
at org.apache.spark.streaming.flume.FlumeStreamSuite$$anonfun$3.apply$mcV$sp(FlumeStreamSuite.scala:66)
at org.apache.spark.streaming.flume.FlumeStreamSuite$$anonfun$3.apply(FlumeStreamSuite.scala:66)
at org.apache.spark.streaming.flume.FlumeStreamSuite$$anonfun$3.apply(FlumeStreamSuite.scala:66)
at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
at org.scalatest.Transformer.apply(Transformer.scala:22)
at org.scalatest.Transformer.apply(Transformer.scala:20)
at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
at org.scalatest.Suite$class.withFixture(Suite.scala:1122)
at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555)
at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163)
at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175)
This error is caused by check-then-act logic when it find free-port .
/** Find a free port */
private def findFreePort(): Int = {
Utils.startServiceOnPort(23456, (trialPort: Int) => {
val socket = new ServerSocket(trialPort)
socket.close()
(null, trialPort)
}, conf)._2
}
Removing the check-then-act is not easy but we can reduce the chance of having the error by choosing random value for initial port instead of 23456.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#4337 from sarutak/SPARK-5559 and squashes the following commits:
16f109f [Kousuke Saruta] Added `require` to Utils#startServiceOnPort
c39d8b6 [Kousuke Saruta] Merge branch 'SPARK-5559' of github.com:sarutak/spark into SPARK-5559
1610ba2 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5559
33357e3 [Kousuke Saruta] Changed "findFreePort" method in MQTTStreamSuite and FlumeStreamSuite so that it can choose valid random port
a9029fe [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5559
9489ef9 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-5559
8212e42 [Kousuke Saruta] Modified default port used in FlumeStreamSuite from 23456 to random value
Use `Utils.createTempDir()` to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
Author: Sean Owen <sowen@cloudera.com>
Closes#5029 from srowen/SPARK-6338 and squashes the following commits:
27b740a [Sean Owen] Fix hive-thriftserver tests that don't expect an existing dir
4a212fa [Sean Owen] Standardize a bit more temp dir management
9004081 [Sean Owen] Revert some added recursive-delete calls
57609e4 [Sean Owen] Use Utils.createTempDir() to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
Author: Sean Owen <sowen@cloudera.com>
Closes#4950 from srowen/SPARK-6225 and squashes the following commits:
3080972 [Sean Owen] Ordered imports: Java, Scala, 3rd party, Spark
c67985b [Sean Owen] Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
In KafkaRDD.scala, Miss expressions flag "s" at logging string
In logging file, it print `Beginning offset $
{part.fromOffset}
is the same as ending offset ` but not `Beginning offset 111 is the same as ending offset `.
Author: zzcclp <xm_zzc@sina.com>
Closes#4979 from zzcclp/SPARK-6279 and squashes the following commits:
768f88e [zzcclp] Miss expressions flag "s"
Option 1 of 2: Convert spark-parent module name to spark-parent_2.10 / spark-parent_2.11
Author: Sean Owen <sowen@cloudera.com>
Closes#4912 from srowen/SPARK-6182.1 and squashes the following commits:
eff60de [Sean Owen] Convert spark-parent module name to spark-parent_2.10 / spark-parent_2.11
cc tdas .
Author: Saisai Shao <saisai.shao@intel.com>
Closes#4817 from jerryshao/signature-minor-fix and squashes the following commits:
eebfaac [Saisai Shao] Remove useless type parameter
The problem with SPARK-6027 in short is that JARs like the kafka-assembly.jar does not work in python as the added JAR is not visible in the classloader used by Py4J. Py4J uses Class.forName(), which does not uses the systemclassloader, but the JARs are only visible in the Thread's contextclassloader. So this back uses the context class loader to create the KafkaUtils dstream object. This works for both cases where the Kafka libraries are added with --jars spark-streaming-kafka-assembly.jar or with --packages spark-streaming-kafka
Also improves the error message.
davies
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#4779 from tdas/kafka-python-fix and squashes the following commits:
fb16b04 [Tathagata Das] Removed import
c1fdf35 [Tathagata Das] Fixed long line and improved documentation
7b88be8 [Tathagata Das] Fixed --jar not working for KafkaUtils and improved error message
modified to adhere to accepted coding standards as pointed by tdas in PR #3844
Author: prabs <prabsmails@gmail.com>
Author: Prabeesh K <prabsmails@gmail.com>
Closes#4178 from prabeesh/master and squashes the following commits:
bd2cb49 [Prabeesh K] adress the comment
ccc0765 [prabs] adress the comment
46f9619 [prabs] adress the comment
c035bdc [prabs] adress the comment
22dd7f7 [prabs] address the comments
0cc67bd [prabs] adress the comment
838c38e [prabs] adress the comment
cd57029 [prabs] address the comments
66919a3 [Prabeesh K] changed MqttDefaultFilePersistence to MemoryPersistence
5857989 [prabs] modified to adhere to accepted coding standards
Published Kafka-assembly JAR was empty in 1.3.0-RC1
This is because the maven build generated two Jars-
1. an empty JAR file (since kafka-assembly has no code of its own)
2. a assembly JAR file containing everything in a different location as 1
The maven publishing plugin uploaded 1 and not 2.
Instead if 2 is not configure to generate in a different location, there is only 1 jar containing everything, which gets published.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#4753 from tdas/SPARK-5993 and squashes the following commits:
c390db8 [Tathagata Das] Fix assembly jar location of kafka-assembly
Another one from JoshRosen 's wish list. The first commit is much smaller and removes 2 of the 4 Clock classes. The second is much larger, necessary for consolidating the streaming one. I put together implementations in the way that seemed simplest. Almost all the change is standardizing class and method names.
Author: Sean Owen <sowen@cloudera.com>
Closes#4514 from srowen/SPARK-4682 and squashes the following commits:
5ed3a03 [Sean Owen] Javadoc Clock classes; make ManualClock private[spark]
169dd13 [Sean Owen] Add support for legacy org.apache.spark.streaming clock class names
277785a [Sean Owen] Reduce the net change in this patch by reversing some unnecessary syntax changes along the way
b5e53df [Sean Owen] FakeClock -> ManualClock; getTime() -> getTimeMillis()
160863a [Sean Owen] Consolidate Streaming Clock class into common util Clock
7c956b2 [Sean Owen] Consolidate Clocks except for Streaming Clock
The test was incorrect. Instead of counting the number of records, it counted the number of partitions of RDD generated by DStream. Which is not its intention. I will be testing this patch multiple times to understand its flakiness.
PS: This was caused by my refactoring in https://github.com/apache/spark/pull/4384/
koeninger check it out.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#4597 from tdas/kafka-flaky-test and squashes the following commits:
d236235 [Tathagata Das] Unignored last test.
e9a1820 [Tathagata Das] fix test
Author: Patrick Wendell <patrick@databricks.com>
Closes#4638 from pwendell/SPARK-5850 and squashes the following commits:
386126f [Patrick Wendell] SPARK-5850: Remove experimental label for Scala 2.11 and FlumePollingStream.
Use temp dir for ActiveMQ database
Author: Sean Owen <sowen@cloudera.com>
Closes#4517 from srowen/SPARK-5728 and squashes the following commits:
1d3aeb8 [Sean Owen] Use temp dir for ActiveMQ database
Author: cody koeninger <cody@koeninger.org>
Closes#4511 from koeninger/kafkaRdd-leader-to-broker and squashes the following commits:
f7151d4 [cody koeninger] [SPARK-4964] test refactoring
6f8680b [cody koeninger] [SPARK-4964] add test of the scala api for KafkaUtils.createRDD
f81e016 [cody koeninger] [SPARK-4964] leave KafkaStreamSuite host and port as private
5173f3f [cody koeninger] [SPARK-4964] test the Java variations of createRDD
e9cece4 [cody koeninger] [SPARK-4964] pass leaders as a map to ensure 1 leader per TopicPartition
Changes
- Added example
- Added a critical unit test that verifies that offset ranges can be recovered through checkpoints
Might add more changes.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#4384 from tdas/new-kafka-fixes and squashes the following commits:
7c931c3 [Tathagata Das] Small update
3ed9284 [Tathagata Das] updated scala doc
83d0402 [Tathagata Das] Added JavaDirectKafkaWordCount example.
26df23c [Tathagata Das] Updates based on PR comments from Cody
e4abf69 [Tathagata Das] Scala doc improvements and stuff.
bb65232 [Tathagata Das] Fixed test bug and refactored KafkaStreamSuite
50f2b56 [Tathagata Das] Added Java API and added more Scala and Java unit tests. Also updated docs.
e73589c [Tathagata Das] Minor changes.
4986784 [Tathagata Das] Added unit test to kafka offset recovery
6a91cab [Tathagata Das] Added example
Using String constructor instead of CharsetDecoder to see if it fixes the issue of empty strings in Flume test output.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#4371 from harishreedharan/Flume-stream-attempted-fix and squashes the following commits:
550d363 [Hari Shreedharan] Fix imports.
8695950 [Hari Shreedharan] Use Charsets.UTF_8 instead of "UTF-8" in String constructors.
af3ba14 [Hari Shreedharan] [SPARK-4905][STREAMING] FlumeStreamSuite fix.
...ck generator fails to store data.
The Reliable Kafka Receiver commits offsets only when events are actually stored, which ensures that on restart we will actually start where we left off. But if the failure happens in the store() call, and the block generator reports an error the receiver does not do anything and will continue reading from the current offset and not the last commit. This means that messages between the last commit and the current offset will be lost.
This PR retries the store call four times and then stops the receiver with an error message and the last exception that was received from the store.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#3655 from harishreedharan/kafka-failure-fix and squashes the following commits:
5e2e7ad [Hari Shreedharan] [SPARK-4704][STREAMING] Reliable Kafka Receiver can lose data if the block generator fails to store data.
Author: cody koeninger <cody@koeninger.org>
Closes#3798 from koeninger/kafkaRdd and squashes the following commits:
1dc2941 [cody koeninger] [SPARK-4964] silence ConsumerConfig warnings about broker connection props
59e29f6 [cody koeninger] [SPARK-4964] settle on "Direct" as a naming convention for the new stream
8c31855 [cody koeninger] [SPARK-4964] remove HasOffsetRanges interface from return types
0df3ebe [cody koeninger] [SPARK-4964] add comments per pwendell / dibbhatt
8991017 [cody koeninger] [SPARK-4964] formatting
825110f [cody koeninger] [SPARK-4964] rename stuff per TD
4354bce [cody koeninger] [SPARK-4964] per td, remove java interfaces, replace with final classes, corresponding changes to KafkaRDD constructor and checkpointing
9adaa0a [cody koeninger] [SPARK-4964] formatting
0090553 [cody koeninger] [SPARK-4964] javafication of interfaces
9a838c2 [cody koeninger] [SPARK-4964] code cleanup, add more tests
2b340d8 [cody koeninger] [SPARK-4964] refactor per TD feedback
80fd6ae [cody koeninger] [SPARK-4964] Rename createExactlyOnceStream so it isnt over-promising, change doc
99d2eba [cody koeninger] [SPARK-4964] Reduce level of nesting. If beginning is past end, its actually an error (may happen if Kafka topic was deleted and recreated)
19406cc [cody koeninger] Merge branch 'master' of https://github.com/apache/spark into kafkaRdd
2e67117 [cody koeninger] [SPARK-4964] one potential way of hiding most of the implementation, while still allowing access to offsets (but not subclassing)
bb80bbe [cody koeninger] [SPARK-4964] scalastyle line length
d4a7cf7 [cody koeninger] [SPARK-4964] allow for use cases that need to override compute for custom kafka dstreams
c1bd6d9 [cody koeninger] [SPARK-4964] use newly available attemptNumber for correct retry behavior
548d529 [cody koeninger] Merge branch 'master' of https://github.com/apache/spark into kafkaRdd
0458e4e [cody koeninger] [SPARK-4964] recovery of generated rdds from checkpoint
e86317b [cody koeninger] [SPARK-4964] try seed brokers in random order to spread metadata requests
e93eb72 [cody koeninger] [SPARK-4964] refactor to add preferredLocations. depends on SPARK-4014
356c7cc [cody koeninger] [SPARK-4964] code cleanup per helena
adf99a6 [cody koeninger] [SPARK-4964] fix serialization issues for checkpointing
1d50749 [cody koeninger] [SPARK-4964] code cleanup per tdas
8bfd6c0 [cody koeninger] [SPARK-4964] configure rate limiting via spark.streaming.receiver.maxRate
e09045b [cody koeninger] [SPARK-4964] add foreachPartitionWithIndex, to avoid doing equivalent map + empty foreach boilerplate
cac63ee [cody koeninger] additional testing, fix fencepost error
37d3053 [cody koeninger] make KafkaRDDPartition available to users so offsets can be committed per partition
bcca8a4 [cody koeninger] Merge branch 'master' of https://github.com/apache/spark into kafkaRdd
6bf14f2 [cody koeninger] first attempt at a Kafka dstream that allows for exactly-once semantics
326ff3c [cody koeninger] add some tests
38bb727 [cody koeninger] give easy access to the parameters of a KafkaRDD
979da25 [cody koeninger] dont allow empty leader offsets to be returned
8d7de4a [cody koeninger] make sure leader offsets can be found even for leaders that arent in the seed brokers
4b078bf [cody koeninger] differentiate between leader and consumer offsets in error message
3c2a96a [cody koeninger] fix scalastyle errors
29c6b43 [cody koeninger] cleanup logging
783b477 [cody koeninger] update tests for kafka 8.1.1
7d050bc [cody koeninger] methods to set consumer offsets and get topic metadata, switch back to inclusive start / exclusive end to match typical kafka consumer behavior
ce91c59 [cody koeninger] method to get consumer offsets, explicit error handling
4dafd1b [cody koeninger] method to get leader offsets, switch rdd bound to being exclusive start, inclusive end to match offsets typically returned from cluster
0b94b33 [cody koeninger] use dropWhile rather than filter to trim beginning of fetch response
1d70625 [cody koeninger] WIP on kafka cluster
76913e2 [cody koeninger] Batch oriented kafka rdd, WIP. todo: cluster metadata / finding leader
Timeout increased to allow overloaded Jenkins to cope with delay in topic creation.
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#4342 from tdas/SPARK-5153 and squashes the following commits:
dc42762 [Tathagata Das] Increased timeout to deal with delays in overloaded Jenkins.
This PR brings the Python API for Spark Streaming Kafka data source.
```
class KafkaUtils(__builtin__.object)
| Static methods defined here:
|
| createStream(ssc, zkQuorum, groupId, topics, storageLevel=StorageLevel(True, True, False, False,
2), keyDecoder=<function utf8_decoder>, valueDecoder=<function utf8_decoder>)
| Create an input stream that pulls messages from a Kafka Broker.
|
| :param ssc: StreamingContext object
| :param zkQuorum: Zookeeper quorum (hostname:port,hostname:port,..).
| :param groupId: The group id for this consumer.
| :param topics: Dict of (topic_name -> numPartitions) to consume.
| Each partition is consumed in its own thread.
| :param storageLevel: RDD storage level.
| :param keyDecoder: A function used to decode key
| :param valueDecoder: A function used to decode value
| :return: A DStream object
```
run the example:
```
bin/spark-submit --driver-class-path external/kafka-assembly/target/scala-*/spark-streaming-kafka-assembly-*.jar examples/src/main/python/streaming/kafka_wordcount.py localhost:2181 test
```
Author: Davies Liu <davies@databricks.com>
Author: Tathagata Das <tdas@databricks.com>
Closes#3715 from davies/kafka and squashes the following commits:
d93bfe0 [Davies Liu] Update make-distribution.sh
4280d04 [Davies Liu] address comments
e6d0427 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka
f257071 [Davies Liu] add tests for null in RDD
23b039a [Davies Liu] address comments
9af51c4 [Davies Liu] Merge branch 'kafka' of github.com:davies/spark into kafka
a74da87 [Davies Liu] address comments
dc1eed0 [Davies Liu] Update kafka_wordcount.py
31e2317 [Davies Liu] Update kafka_wordcount.py
370ba61 [Davies Liu] Update kafka.py
97386b3 [Davies Liu] address comment
2c567a5 [Davies Liu] update logging and comment
33730d1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka
adeeb38 [Davies Liu] Merge pull request #3 from tdas/kafka-python-api
aea8953 [Tathagata Das] Kafka-assembly for Python API
eea16a7 [Davies Liu] refactor
f6ce899 [Davies Liu] add example and fix bugs
98c8d17 [Davies Liu] fix python style
5697a01 [Davies Liu] bypass decoder in scala
048dbe6 [Davies Liu] fix python style
75d485e [Davies Liu] add mqtt
07923c4 [Davies Liu] support kafka in Python
This fixes two sources of non-deterministic failures in this test:
- wait for a receiver to be up before pushing data through MQTT
- gracefully handle the case where the MQTT client is overloaded. There’s
a hard-coded limit of 10 in-flight messages, and this test may hit it.
Instead of crashing, we retry sending the message.
Both of these are needed to make the test pass reliably on my machine.
Author: Iulian Dragos <jaguarul@gmail.com>
Closes#4270 from dragos/issue/fix-flaky-test-SPARK-4631 and squashes the following commits:
f66c482 [Iulian Dragos] [SPARK-4631][streaming] Wait for a receiver to start before publishing test data.
d408a8e [Iulian Dragos] Install callback before connecting to MQTT broker.
https://issues.apache.org/jira/browse/SPARK-5006
I think the issue is produced in https://github.com/apache/spark/pull/1777.
Not digging mesos's backend yet. Maybe should add same logic either.
Author: WangTaoTheTonic <barneystinson@aliyun.com>
Author: WangTao <barneystinson@aliyun.com>
Closes#3841 from WangTaoTheTonic/SPARK-5006 and squashes the following commits:
8cdf96d [WangTao] indent thing
2d86d65 [WangTaoTheTonic] fix line length
7cdfd98 [WangTaoTheTonic] fit for new HttpServer constructor
61a370d [WangTaoTheTonic] some minor fixes
bc6e1ec [WangTaoTheTonic] rebase
67bcb46 [WangTaoTheTonic] put conf at 3rd position, modify suite class, add comments
f450cd1 [WangTaoTheTonic] startServiceOnPort will use a SparkConf arg
29b751b [WangTaoTheTonic] rebase as ExecutorRunnableUtil changed to ExecutorRunnable
396c226 [WangTaoTheTonic] make the grammar more like scala
191face [WangTaoTheTonic] invalid value name
62ec336 [WangTaoTheTonic] spark.port.maxRetries doesn't work
cc andrewor14
Author: GuoQiang Li <witgo@qq.com>
Closes#3989 from witgo/MQTTStreamSuite and squashes the following commits:
a6e967e [GuoQiang Li] Resolve sbt warnings during build (MQTTStreamSuite.scala).
This change does a few things to make the hadoop-provided profile more useful:
- Create new profiles for other libraries / services that might be provided by the infrastructure
- Simplify and fix the poms so that the profiles are only activated while building assemblies.
- Fix tests so that they're able to run when the profiles are activated
- Add a new env variable to be used by distributions that use these profiles to provide the runtime
classpath for Spark jobs and daemons.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#2982 from vanzin/SPARK-4048 and squashes the following commits:
82eb688 [Marcelo Vanzin] Add a comment.
eb228c0 [Marcelo Vanzin] Fix borked merge.
4e38f4e [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
9ef79a3 [Marcelo Vanzin] Alternative way to propagate test classpath to child processes.
371ebee [Marcelo Vanzin] Review feedback.
52f366d [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
83099fc [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
7377e7b [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
322f882 [Marcelo Vanzin] Fix merge fail.
f24e9e7 [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
8b00b6a [Marcelo Vanzin] Merge branch 'master' into SPARK-4048
9640503 [Marcelo Vanzin] Cleanup child process log message.
115fde5 [Marcelo Vanzin] Simplify a comment (and make it consistent with another pom).
e3ab2da [Marcelo Vanzin] Fix hive-thriftserver profile.
7820d58 [Marcelo Vanzin] Fix CliSuite with provided profiles.
1be73d4 [Marcelo Vanzin] Restore flume-provided profile.
d1399ed [Marcelo Vanzin] Restore jetty dependency.
82a54b9 [Marcelo Vanzin] Remove unused profile.
5c54a25 [Marcelo Vanzin] Fix HiveThriftServer2Suite with *-provided profiles.
1fc4d0b [Marcelo Vanzin] Update dependencies for hive-thriftserver.
f7b3bbe [Marcelo Vanzin] Add snappy to hadoop-provided list.
9e4e001 [Marcelo Vanzin] Remove duplicate hive profile.
d928d62 [Marcelo Vanzin] Redirect child stderr to parent's log.
4d67469 [Marcelo Vanzin] Propagate SPARK_DIST_CLASSPATH on Yarn.
417d90e [Marcelo Vanzin] Introduce "SPARK_DIST_CLASSPATH".
2f95f0d [Marcelo Vanzin] Propagate classpath to child processes during testing.
1adf91c [Marcelo Vanzin] Re-enable maven-install-plugin for a few projects.
284dda6 [Marcelo Vanzin] Rework the "hadoop-provided" profile, add new ones.
This PR:
- Reenables `surefire`, and copies config from `scalatest` (which is itself an old fork of `surefire`, so similar)
- Tells `surefire` to test only Java tests
- Enables `surefire` and `scalatest` for all children, and in turn eliminates some duplication.
For me this causes the Scala and Java tests to be run once each, it seems, as desired. It doesn't affect the SBT build but works for Maven. I still need to verify that all of the Scala tests and Java tests are being run.
Author: Sean Owen <sowen@cloudera.com>
Closes#3651 from srowen/SPARK-4159 and squashes the following commits:
2e8a0af [Sean Owen] Remove specialized SPARK_HOME setting for REPL, YARN tests as it appears to be obsolete
12e4558 [Sean Owen] Append to unit-test.log instead of overwriting, so that both surefire and scalatest output is preserved. Also standardize/correct comments a bit.
e6f8601 [Sean Owen] Reenable Java tests by reenabling surefire with config cloned from scalatest; centralize test config in the parent
Several of our tests call System.setProperty (or test code which implicitly sets system properties) and don't always reset/clear the modified properties, which can create ordering dependencies between tests and cause hard-to-diagnose failures.
This patch removes most uses of System.setProperty from our tests, since in most cases we can use SparkConf to set these configurations (there are a few exceptions, including the tests of SparkConf itself).
For the cases where we continue to use System.setProperty, this patch introduces a `ResetSystemProperties` ScalaTest mixin class which snapshots the system properties before individual tests and to automatically restores them on test completion / failure. See the block comment at the top of the ResetSystemProperties class for more details.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#3739 from JoshRosen/cleanup-system-properties-in-tests and squashes the following commits:
0236d66 [Josh Rosen] Replace setProperty uses in two example programs / tools
3888fe3 [Josh Rosen] Remove setProperty use in LocalJavaStreamingContext
4f4031d [Josh Rosen] Add note on why SparkSubmitSuite needs ResetSystemProperties
4742a5b [Josh Rosen] Clarify ResetSystemProperties trait inheritance ordering.
0eaf0b6 [Josh Rosen] Remove setProperty call in TaskResultGetterSuite.
7a3d224 [Josh Rosen] Fix trait ordering
3fdb554 [Josh Rosen] Remove setProperty call in TaskSchedulerImplSuite
bee20df [Josh Rosen] Remove setProperty calls in SparkContextSchedulerCreationSuite
655587c [Josh Rosen] Remove setProperty calls in JobCancellationSuite
3f2f955 [Josh Rosen] Remove System.setProperty calls in DistributedSuite
cfe9cce [Josh Rosen] Remove use of system properties in SparkContextSuite
8783ab0 [Josh Rosen] Remove TestUtils.setSystemProperty, since it is subsumed by the ResetSystemProperties trait.
633a84a [Josh Rosen] Remove use of system properties in FileServerSuite
25bfce2 [Josh Rosen] Use ResetSystemProperties in UtilsSuite
1d1aa5a [Josh Rosen] Use ResetSystemProperties in SizeEstimatorSuite
dd9492b [Josh Rosen] Use ResetSystemProperties in AkkaUtilsSuite
b0daff2 [Josh Rosen] Use ResetSystemProperties in BlockManagerSuite
e9ded62 [Josh Rosen] Use ResetSystemProperties in TaskSchedulerImplSuite
5b3cb54 [Josh Rosen] Use ResetSystemProperties in SparkListenerSuite
0995c4b [Josh Rosen] Use ResetSystemProperties in SparkContextSchedulerCreationSuite
c83ded8 [Josh Rosen] Use ResetSystemProperties in SparkConfSuite
51aa870 [Josh Rosen] Use withSystemProperty in ShuffleSuite
60a63a1 [Josh Rosen] Use ResetSystemProperties in JobCancellationSuite
14a92e4 [Josh Rosen] Use withSystemProperty in FileServerSuite
628f46c [Josh Rosen] Use ResetSystemProperties in DistributedSuite
9e3e0dd [Josh Rosen] Add ResetSystemProperties test fixture mixin; use it in SparkSubmitSuite.
4dcea38 [Josh Rosen] Move withSystemProperty to TestUtils class.
changed "form" to "from" in 3 documentation entries for Kafka integration
Author: Peter Klipfel <peter@klipfel.me>
Closes#3691 from peterklipfel/master and squashes the following commits:
0fe7fc5 [Peter Klipfel] fixed spelling errors in documentation
Since `sequenceNumberToProcessor` and `stopped` are both protected by the lock `sequenceNumberToProcessor`, `ConcurrentHashMap` and `volatile` is unnecessary. So this PR updated them accordingly.
Author: zsxwing <zsxwing@gmail.com>
Closes#3634 from zsxwing/SPARK-3154 and squashes the following commits:
0d087ac [zsxwing] Replace ConcurrentHashMap with mutable.HashMap and remove @volatile from 'stopped'
Somehow maven shade plugin is set in infinite loop of creating effective pom.
Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Prashant Sharma <scrapcodes@gmail.com>
Closes#2959 from ScrapCodes/SPARK-3962/scope-provided and squashes the following commits:
994d1d3 [Prashant Sharma] Fixed failing flume tests
270b4fb [Prashant Sharma] Removed most of the unused code.
bb3bbfd [Prashant Sharma] SPARK-3962 Marked scope as provided for external.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Closes#3277 from vanzin/version-1.3 and squashes the following commits:
7c3c396 [Marcelo Vanzin] Added temp repo to sbt build.
5f404ff [Marcelo Vanzin] Add another exclusion.
19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo.
3c8d705 [Marcelo Vanzin] Workaround for MIMA checks.
e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
