## What changes were proposed in this pull request?
`ReplSuite.newProductSeqEncoder with REPL defined class` was flaky and throws OOM exception frequently. By analyzing the heap dump, we found the reason is that, in each test case of `ReplSuite`, we create a REPL instance, which creates a classloader and loads a lot of classes related to `SparkContext`. More details please see https://github.com/apache/spark/pull/17833#issuecomment-298711435.
In this PR, we create a new test suite, `SingletonReplSuite`, which shares one REPL instances among all the test cases. Then we move most of the tests from `ReplSuite` to `SingletonReplSuite`, to avoid creating a lot of REPL instances and reduce memory footprint.
## How was this patch tested?
test only change
Author: Wenchen Fan <wenchen@databricks.com>
Closes#17844 from cloud-fan/flaky-test.
## What changes were proposed in this pull request?
Spark Version for a specific application is not displayed on the history page now. It should be nice to switch the spark version on the UI when we click on the specific application.
Currently there seems to be way as SparkListenerLogStart records the application version. So, it should be trivial to listen to this event and provision this change on the UI.
For Example
<img width="1439" alt="screen shot 2017-04-06 at 3 23 41 pm" src="https://cloud.githubusercontent.com/assets/8295799/25092650/41f3970a-2354-11e7-9b0d-4646d0adeb61.png">
<img width="1399" alt="screen shot 2017-04-17 at 9 59 33 am" src="https://cloud.githubusercontent.com/assets/8295799/25092743/9f9e2f28-2354-11e7-9605-f2f1c63f21fe.png">
{"Event":"SparkListenerLogStart","Spark Version":"2.0.0"}
(Please fill in changes proposed in this fix)
Modified the SparkUI for History server to listen to SparkLogListenerStart event and extract the version and print it.
## How was this patch tested?
Manual testing of UI page. Attaching the UI screenshot changes here
(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: Sanket <schintap@untilservice-lm>
Closes#17658 from redsanket/SPARK-20355.
## What changes were proposed in this pull request?
This pr added parsing rules to support aliases in table value functions.
## How was this patch tested?
Added tests in `PlanParserSuite`.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#17666 from maropu/SPARK-20311.
## What changes were proposed in this pull request?
So far, we do not drop all the cataloged objects after each package. Sometimes, we might hit strange test case errors because the previous test suite did not drop the cataloged/temporary objects (tables/functions/database). At least, we can first clean up the environment when completing the package of `sql/core` and `sql/hive`.
## How was this patch tested?
N/A
Author: Xiao Li <gatorsmile@gmail.com>
Closes#17908 from gatorsmile/reset.
## What changes were proposed in this pull request?
Remove ML methods we deprecated in 2.1.
## How was this patch tested?
Existing tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#17867 from yanboliang/spark-20606.
## What changes were proposed in this pull request?
Added a check for for the number of defined values. Previously the argmax function assumed that at least one value was defined if the vector size was greater than zero.
## How was this patch tested?
Tests were added to the existing VectorsSuite to cover this case.
Author: Jon McLean <jon.mclean@atsid.com>
Closes#17877 from jonmclean/vectorArgmaxIndexBug.
This PR is a `DataFrame` version of #17742 for [SPARK-11968](https://issues.apache.org/jira/browse/SPARK-11968), for improving the performance of `recommendAll` methods.
## How was this patch tested?
Existing unit tests.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#17845 from MLnick/ml-als-perf.
The recommendForAll of MLLIB ALS is very slow.
GC is a key problem of the current method.
The task use the following code to keep temp result:
val output = new Array[(Int, (Int, Double))](m*n)
m = n = 4096 (default value, no method to set)
so output is about 4k * 4k * (4 + 4 + 8) = 256M. This is a large memory and cause serious GC problem, and it is frequently OOM.
Actually, we don't need to save all the temp result. Support we recommend topK (topK is about 10, or 20) product for each user, we only need 4k * topK * (4 + 4 + 8) memory to save the temp result.
The Test Environment:
3 workers: each work 10 core, each work 30G memory, each work 1 executor.
The Data: User 480,000, and Item 17,000
BlockSize: 1024 2048 4096 8192
Old method: 245s 332s 488s OOM
This solution: 121s 118s 117s 120s
The existing UT.
Author: Peng <peng.meng@intel.com>
Author: Peng Meng <peng.meng@intel.com>
Closes#17742 from mpjlu/OptimizeAls.
## What changes were proposed in this pull request?
Change it to check for relative count like in this test https://github.com/apache/spark/blame/master/R/pkg/inst/tests/testthat/test_sparkSQL.R#L3355 for catalog APIs
## How was this patch tested?
unit tests, this needs to combine with another commit with SQL change to check
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17905 from felixcheung/rtabletests.
## What changes were proposed in this pull request?
Cleaning existing temp tables before running tableNames tests
## How was this patch tested?
SparkR Unit tests
Author: Hossein <hossein@databricks.com>
Closes#17903 from falaki/SPARK-20661.
## What changes were proposed in this pull request?
After SPARK-10997, client mode Netty RpcEnv doesn't require to start server, so port configurations are not used any more, here propose to remove these two configurations: "spark.executor.port" and "spark.am.port".
## How was this patch tested?
Existing UTs.
Author: jerryshao <sshao@hortonworks.com>
Closes#17866 from jerryshao/SPARK-20605.
## What changes were proposed in this pull request?
Currently, `spark.executor.instances` is deprecated in `spark-env.sh`, because we suggest config it in `spark-defaults.conf` or other config file. And also this parameter is useless even if you set it in `spark-env.sh`, so remove it in this patch.
## How was this patch tested?
Existing tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Xianyang Liu <xianyang.liu@intel.com>
Closes#17881 from ConeyLiu/deprecatedParam.
Existing test cases for `recommendForAllX` methods (added in [SPARK-19535](https://issues.apache.org/jira/browse/SPARK-19535)) test `k < num items` and `k = num items`. Technically we should also test that `k > num items` returns the same results as `k = num items`.
## How was this patch tested?
Updated existing unit tests.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes#17860 from MLnick/SPARK-20596-als-rec-tests.
## What changes were proposed in this pull request?
When call the method getLocations of BlockManager, we only compare the data block host. Random selection for non-local data blocks, this may cause the selected data block to be in a different rack. So in this patch to increase the sort of the rack.
## How was this patch tested?
New test case.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Xianyang Liu <xianyang.liu@intel.com>
Closes#17300 from ConeyLiu/blockmanager.
Signed-off-by: liuxian <liu.xian3zte.com.cn>
## What changes were proposed in this pull request?
When the input parameter is null, may be a runtime exception occurs
## How was this patch tested?
Existing unit tests
Author: liuxian <liu.xian3@zte.com.cn>
Closes#17796 from 10110346/wip_lx_0428.
## What changes were proposed in this pull request?
Fix typo in vignettes
Author: Wayne Zhang <actuaryzhang@uber.com>
Closes#17884 from actuaryzhang/typo.
### What changes were proposed in this pull request?
Table comment was not getting set/unset using **ALTER TABLE SET/UNSET TBLPROPERTIES** query
eg: ALTER TABLE table_with_comment SET TBLPROPERTIES("comment"= "modified comment)
when user alter the table properties and adds/updates table comment,table comment which is a field of **CatalogTable** instance is not getting updated and old table comment if exists was shown to user, inorder to handle this issue, update the comment field value in **CatalogTable** with the newly added/modified comment along with other table level properties when user executes **ALTER TABLE SET TBLPROPERTIES** query.
This pr has also taken care of unsetting the table comment when user executes query **ALTER TABLE UNSET TBLPROPERTIES** inorder to unset or remove table comment.
eg: ALTER TABLE table_comment UNSET TBLPROPERTIES IF EXISTS ('comment')
### How was this patch tested?
Added test cases as part of **SQLQueryTestSuite** for verifying table comment using desc formatted table query after adding/modifying table comment as part of **AlterTableSetPropertiesCommand** and unsetting the table comment using **AlterTableUnsetPropertiesCommand**.
Author: sujith71955 <sujithchacko.2010@gmail.com>
Closes#17649 from sujith71955/alter_table_comment.
## What changes were proposed in this pull request?
set timezone on windows
## How was this patch tested?
unit test, AppVeyor
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17892 from felixcheung/rtimestamptest.
## What changes were proposed in this pull request?
This change allows timestamps in parquet-based hive table to behave as a "floating time", without a timezone, as timestamps are for other file formats. If the storage timezone is the same as the session timezone, this conversion is a no-op. When data is read from a hive table, the table property is *always* respected. This allows spark to not change behavior when reading old data, but read newly written data correctly (whatever the source of the data is).
Spark inherited the original behavior from Hive, but Hive is also updating behavior to use the same scheme in HIVE-12767 / HIVE-16231.
The default for Spark remains unchanged; created tables do not include the new table property.
This will only apply to hive tables; nothing is added to parquet metadata to indicate the timezone, so data that is read or written directly from parquet files will never have any conversions applied.
## How was this patch tested?
Added a unit test which creates tables, reads and writes data, under a variety of permutations (different storage timezones, different session timezones, vectorized reading on and off).
Author: Imran Rashid <irashid@cloudera.com>
Closes#16781 from squito/SPARK-12297.
## What changes were proposed in this pull request?
Adds Python wrappers for `DataFrameWriter.bucketBy` and `DataFrameWriter.sortBy` ([SPARK-16931](https://issues.apache.org/jira/browse/SPARK-16931))
## How was this patch tested?
Unit tests covering new feature.
__Note__: Based on work of GregBowyer (f49b9a23468f7af32cb53d2b654272757c151725)
CC HyukjinKwon
Author: zero323 <zero323@users.noreply.github.com>
Author: Greg Bowyer <gbowyer@fastmail.co.uk>
Closes#17077 from zero323/SPARK-16931.
## What changes were proposed in this pull request?
- Add SparkR wrapper for `Dataset.alias`.
- Adjust roxygen annotations for `functions.alias` (including example usage).
## How was this patch tested?
Unit tests, `check_cran.sh`.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17825 from zero323/SPARK-20550.
## What changes were proposed in this pull request?
* Docs are consistent (across different `unix_timestamp` variants and their internal expressions)
* typo hunting
## How was this patch tested?
local build
Author: Jacek Laskowski <jacek@japila.pl>
Closes#17801 from jaceklaskowski/unix_timestamp.
## What changes were proposed in this pull request?
add environment
## How was this patch tested?
wait for appveyor run
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17878 from felixcheung/appveyorrcran.
## What changes were proposed in this pull request?
Add a new `spark-hadoop-cloud` module and maven profile to pull in object store support from `hadoop-openstack`, `hadoop-aws` and `hadoop-azure` (Hadoop 2.7+) JARs, along with their dependencies, fixing up the dependencies so that everything works, in particular Jackson.
It restores `s3n://` access to S3, adds its `s3a://` replacement, OpenStack `swift://` and azure `wasb://`.
There's a documentation page, `cloud_integration.md`, which covers the basic details of using Spark with object stores, referring the reader to the supplier's own documentation, with specific warnings on security and the possible mismatch between a store's behavior and that of a filesystem. In particular, users are advised be very cautious when trying to use an object store as the destination of data, and to consult the documentation of the storage supplier and the connector.
(this is the successor to #12004; I can't re-open it)
## How was this patch tested?
Downstream tests exist in [https://github.com/steveloughran/spark-cloud-examples/tree/master/cloud-examples](https://github.com/steveloughran/spark-cloud-examples/tree/master/cloud-examples)
Those verify that the dependencies are sufficient to allow downstream applications to work with s3a, azure wasb and swift storage connectors, and perform basic IO & dataframe operations thereon. All seems well.
Manually clean build & verify that assembly contains the relevant aws-* hadoop-* artifacts on Hadoop 2.6; azure on a hadoop-2.7 profile.
SBT build: `build/sbt -Phadoop-cloud -Phadoop-2.7 package`
maven build `mvn install -Phadoop-cloud -Phadoop-2.7`
This PR *does not* update `dev/deps/spark-deps-hadoop-2.7` or `dev/deps/spark-deps-hadoop-2.6`, because unless the hadoop-cloud profile is enabled, no extra JARs show up in the dependency list. The dependency check in Jenkins isn't setting the property, so the new JARs aren't visible.
Author: Steve Loughran <stevel@apache.org>
Author: Steve Loughran <stevel@hortonworks.com>
Closes#17834 from steveloughran/cloud/SPARK-7481-current.
## What changes were proposed in this pull request?
This PR adds documentation to the ALS code.
## How was this patch tested?
Existing tests were used.
mengxr srowen
This contribution is my original work. I have the license to work on this project under the Spark project’s open source license.
Author: Daniel Li <dan@danielyli.com>
Closes#17793 from danielyli/spark-20484.
## What changes were proposed in this pull request?
This PR adds the new unit tests to support ShuffleDataBlockId , ShuffleIndexBlockId , TempShuffleBlockId , TempLocalBlockId
## How was this patch tested?
The new unit test.
Author: caoxuewen <cao.xuewen@zte.com.cn>
Closes#17794 from heary-cao/blockidsuite.
## What changes were proposed in this pull request?
- Move udf wrapping code from `functions.udf` to `functions.UserDefinedFunction`.
- Return wrapped udf from `catalog.registerFunction` and dependent methods.
- Update docstrings in `catalog.registerFunction` and `SQLContext.registerFunction`.
- Unit tests.
## How was this patch tested?
- Existing unit tests and docstests.
- Additional tests covering new feature.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17831 from zero323/SPARK-18777.
### 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?
Currently, there are flooding logs in AppVeyor (in the console). This has been fine because we can download all the logs. However, (given my observations so far), logs are truncated when there are too many. It has been grown recently and it started to get truncated. For example, see https://ci.appveyor.com/project/ApacheSoftwareFoundation/spark/build/1209-master
Even after the log is downloaded, it looks truncated as below:
```
[00:44:21] 17/05/04 18:56:18 INFO TaskSetManager: Finished task 197.0 in stage 601.0 (TID 9211) in 0 ms on localhost (executor driver) (194/200)
[00:44:21] 17/05/04 18:56:18 INFO Executor: Running task 199.0 in stage 601.0 (TID 9213)
[00:44:21] 17/05/04 18:56:18 INFO Executor: Finished task 198.0 in stage 601.0 (TID 9212). 2473 bytes result sent to driver
...
```
Probably, it looks better to use the same log4j configuration that we are using for SparkR tests in Jenkins(please see fc472bddd1/R/run-tests.sh (L26) and fc472bddd1/R/log4j.properties)
```
# Set everything to be logged to the file target/unit-tests.log
log4j.rootCategory=INFO, file
log4j.appender.file=org.apache.log4j.FileAppender
log4j.appender.file.append=true
log4j.appender.file.file=R/target/unit-tests.log
log4j.appender.file.layout=org.apache.log4j.PatternLayout
log4j.appender.file.layout.ConversionPattern=%d{yy/MM/dd HH:mm:ss.SSS} %t %p %c{1}: %m%n
# Ignore messages below warning level from Jetty, because it's a bit verbose
log4j.logger.org.eclipse.jetty=WARN
org.eclipse.jetty.LEVEL=WARN
```
## How was this patch tested?
Manually tested with spark-test account
- https://ci.appveyor.com/project/spark-test/spark/build/672-r-log4j (there is an example for flaky test here)
- https://ci.appveyor.com/project/spark-test/spark/build/673-r-log4j (I re-ran the build).
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17873 from HyukjinKwon/appveyor-reduce-logs.
## What changes were proposed in this pull request?
Due to a likely typo, the logDebug msg printing the diff of query plans shows a diff to the initial plan, not diff to the start of batch.
## How was this patch tested?
Now the debug message prints the diff between start and end of batch.
Author: Juliusz Sompolski <julek@databricks.com>
Closes#17875 from juliuszsompolski/SPARK-20616.
## 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?
ObjectHashAggregateExec is missing numOutputRows, add this metrics for it.
## How was this patch tested?
Added unit tests for the new metrics.
Author: Yucai <yucai.yu@intel.com>
Closes#17678 from yucai/objectAgg_numOutputRows.
## What changes were proposed in this pull request?
Quotes are already added to the RUNNER variable on line 54. There is no need to put quotes on line 67. If you do, you will get an error when launching Spark.
'""C:\Program' is not recognized as an internal or external command, operable program or batch file.
## How was this patch tested?
Tested manually on Windows 10.
Author: Jarrett Meyer <jarrettmeyer@gmail.com>
Closes#17861 from jarrettmeyer/fix-windows-cmd.
## What changes were proposed in this pull request?
Currently cacheTable API only supports MEMORY_AND_DISK. This PR adds additional API to take different storage levels.
## How was this patch tested?
unit tests
Author: madhu <phatak.dev@gmail.com>
Closes#17802 from phatak-dev/cacheTableAPI.
## What changes were proposed in this pull request?
Updated spark-class to turn off posix mode so the process substitution doesn't cause a syntax error.
## How was this patch tested?
Existing unit tests, manual spark-shell testing with posix mode on
Author: jyu00 <jessieyu@us.ibm.com>
Closes#17852 from jyu00/master.
## What changes were proposed in this pull request?
Replace the deprecated property name `fs.default.name` to `fs.defaultFS` that newly introduced.
## How was this patch tested?
Existing tests
Author: Yuming Wang <wgyumg@gmail.com>
Closes#17856 from wangyum/SPARK-19660.
## What changes were proposed in this pull request?
This PR proposes to close a stale PR, several PRs suggested to be closed by a committer and obviously inappropriate PRs.
Closes#11119Closes#17853Closes#17732Closes#17456Closes#17410Closes#17314Closes#17362Closes#17542
## How was this patch tested?
N/A
Author: hyukjinkwon <gurwls223@gmail.com>
Closes#17855 from HyukjinKwon/close-pr.
## What changes were proposed in this pull request?
Bucketizer currently requires input column to be Double, but the logic should work on any numeric data types. Many practical problems have integer/float data types, and it could get very tedious to manually cast them into Double before calling bucketizer. This PR extends bucketizer to handle all numeric types.
## How was this patch tested?
New test.
Author: Wayne Zhang <actuaryzhang@uber.com>
Closes#17840 from actuaryzhang/bucketizer.
## What changes were proposed in this pull request?
Address some minor comments for #17715:
* Put bound-constrained optimization params under expertParams.
* Update some docs.
## How was this patch tested?
Existing tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#17829 from yanboliang/spark-20047-followup.
## What changes were proposed in this pull request?
Make tests more reliable by having it till processed.
Increasing timeout value might help but ultimately the flakiness from processing delay when Jenkins is hard to account for. This isn't an actual public API supported
## How was this patch tested?
unit tests
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17857 from felixcheung/rsstestrelia.
## What changes were proposed in this pull request?
Adds wrapper for `o.a.s.sql.functions.input_file_name`
## How was this patch tested?
Existing unit tests, additional unit tests, `check-cran.sh`.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17818 from zero323/SPARK-20544.
## What changes were proposed in this pull request?
Adds support for generic hints on `SparkDataFrame`
## How was this patch tested?
Unit tests, `check-cran.sh`
Author: zero323 <zero323@users.noreply.github.com>
Closes#17851 from zero323/SPARK-20585.
## What changes were proposed in this pull request?
Add
- R vignettes
- R programming guide
- SS programming guide
- R example
Also disable spark.als in vignettes for now since it's failing (SPARK-20402)
## How was this patch tested?
manually
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17814 from felixcheung/rdocss.
## What changes were proposed in this pull request?
General rule on skip or not:
skip if
- RDD tests
- tests could run long or complicated (streaming, hivecontext)
- tests on error conditions
- tests won't likely change/break
## How was this patch tested?
unit tests, `R CMD check --as-cran`, `R CMD check`
Author: Felix Cheung <felixcheung_m@hotmail.com>
Closes#17817 from felixcheung/rskiptest.
## What changes were proposed in this pull request?
Adds `hint` method to PySpark `DataFrame`.
## How was this patch tested?
Unit tests, doctests.
Author: zero323 <zero323@users.noreply.github.com>
Closes#17850 from zero323/SPARK-20584.
## The Problem
Right now DataFrame batch reader may fail to infer partitions when reading FileStreamSink's output:
```
[info] - partitioned writing and batch reading with 'basePath' *** FAILED *** (3 seconds, 928 milliseconds)
[info] java.lang.AssertionError: assertion failed: Conflicting directory structures detected. Suspicious paths:
[info] ***/stream.output-65e3fa45-595a-4d29-b3df-4c001e321637
[info] ***/stream.output-65e3fa45-595a-4d29-b3df-4c001e321637/_spark_metadata
[info]
[info] If provided paths are partition directories, please set "basePath" in the options of the data source to specify the root directory of the table. If there are multiple root directories, please load them separately and then union them.
[info] at scala.Predef$.assert(Predef.scala:170)
[info] at org.apache.spark.sql.execution.datasources.PartitioningUtils$.parsePartitions(PartitioningUtils.scala:133)
[info] at org.apache.spark.sql.execution.datasources.PartitioningUtils$.parsePartitions(PartitioningUtils.scala:98)
[info] at org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex.inferPartitioning(PartitioningAwareFileIndex.scala:156)
[info] at org.apache.spark.sql.execution.datasources.InMemoryFileIndex.partitionSpec(InMemoryFileIndex.scala:54)
[info] at org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex.partitionSchema(PartitioningAwareFileIndex.scala:55)
[info] at org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:133)
[info] at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:361)
[info] at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:160)
[info] at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:536)
[info] at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:520)
[info] at org.apache.spark.sql.streaming.FileStreamSinkSuite$$anonfun$8.apply$mcV$sp(FileStreamSinkSuite.scala:292)
[info] at org.apache.spark.sql.streaming.FileStreamSinkSuite$$anonfun$8.apply(FileStreamSinkSuite.scala:268)
[info] at org.apache.spark.sql.streaming.FileStreamSinkSuite$$anonfun$8.apply(FileStreamSinkSuite.scala:268)
```
## What changes were proposed in this pull request?
This patch alters `InMemoryFileIndex` to filter out these `basePath`s whose ancestor is the streaming metadata dir (`_spark_metadata`). E.g., the following and other similar dir or files will be filtered out:
- (introduced by globbing `basePath/*`)
- `basePath/_spark_metadata`
- (introduced by globbing `basePath/*/*`)
- `basePath/_spark_metadata/0`
- `basePath/_spark_metadata/1`
- ...
## How was this patch tested?
Added unit tests
Author: Liwei Lin <lwlin7@gmail.com>
Closes#17346 from lw-lin/filter-metadata.
## What changes were proposed in this pull request?
We allow users to specify hints (currently only "broadcast" is supported) in SQL and DataFrame. However, while SQL has a standard hint format (/*+ ... */), DataFrame doesn't have one and sometimes users are confused that they can't find how to apply a broadcast hint. This ticket adds a generic hint function on DataFrame that allows using the same hint on DataFrames as well as SQL.
As an example, after this patch, the following will apply a broadcast hint on a DataFrame using the new hint function:
```
df1.join(df2.hint("broadcast"))
```
## How was this patch tested?
Added a test case in DataFrameJoinSuite.
Author: Reynold Xin <rxin@databricks.com>
Closes#17839 from rxin/SPARK-20576.
