### What changes were proposed in this pull request?
This PR adds the structured streaming UI introduction to the Web UI doc.
### Why are the changes needed?
The structured streaming web UI introduced before was missing from the Web UI documentation.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N.A.
Closes#28609 from xccui/ss-ui-doc.
Authored-by: Xingcan Cui <xccui@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
1. Add the following parquet files to the resource folder `sql/core/src/test/resources/test-data`:
- Files saved by Spark 2.4.5 (cee4ecbb16) without meta info `org.apache.spark.version`
- `before_1582_date_v2_4_5.snappy.parquet` with 2 date columns of the type **INT32 L:DATE** - `PLAIN` (8 date values of `1001-01-01`) and `PLAIN_DICTIONARY` (`1001-01-01`..`1001-01-08`).
- `before_1582_timestamp_micros_v2_4_5.snappy.parquet` with 2 timestamp columns of the type **INT64 L:TIMESTAMP(MICROS,true)** - `PLAIN` (8 date values of `1001-01-01 01:02:03.123456`) and `PLAIN_DICTIONARY` (`1001-01-01 01:02:03.123456`..`1001-01-08 01:02:03.123456`).
- `before_1582_timestamp_millis_v2_4_5.snappy.parquet` with 2 timestamp columns of the type **INT64 L:TIMESTAMP(MILLIS,true)** - `PLAIN` (8 date values of `1001-01-01 01:02:03.123`) and `PLAIN_DICTIONARY` (`1001-01-01 01:02:03.123`..`1001-01-08 01:02:03.123`).
- `before_1582_timestamp_int96_plain_v2_4_5.snappy.parquet` with 2 timestamp columns of the type **INT96** - `PLAIN` (8 date values of `1001-01-01 01:02:03.123456`) and `PLAIN` (`1001-01-01 01:02:03.123456`..`1001-01-08 01:02:03.123456`).
- `before_1582_timestamp_int96_dict_v2_4_5.snappy.parquet` with 2 timestamp columns of the type **INT96** - `PLAIN_DICTIONARY` (8 date values of `1001-01-01 01:02:03.123456`) and `PLAIN_DICTIONARY` (`1001-01-01 01:02:03.123456`..`1001-01-08 01:02:03.123456`).
- Files saved by Spark 2.4.6-rc3 (570848da7c) with the meta info `org.apache.spark.version = 2.4.6`:
- `before_1582_date_v2_4_6.snappy.parquet` replaces `before_1582_date_v2_4.snappy.parquet`. And it is similar to `before_1582_date_v2_4_5.snappy.parquet` except Spark version in parquet meta info.
- `before_1582_timestamp_micros_v2_4_6.snappy.parquet` replaces `before_1582_timestamp_micros_v2_4.snappy.parquet`. And it is similar to `before_1582_timestamp_micros_v2_4_5.snappy.parquet` except meta info.
- `before_1582_timestamp_millis_v2_4_6.snappy.parquet` replaces `before_1582_timestamp_millis_v2_4.snappy.parquet`. And it is similar to `before_1582_timestamp_millis_v2_4_5.snappy.parquet` except meta info.
- `before_1582_timestamp_int96_plain_v2_4_6.snappy.parquet` is similar to `before_1582_timestamp_int96_dict_v2_4_5.snappy.parquet` except meta info.
- `before_1582_timestamp_int96_dict_v2_4_6.snappy.parquet` replaces `before_1582_timestamp_int96_v2_4.snappy.parquet`. And it is similar to `before_1582_timestamp_int96_dict_v2_4_5.snappy.parquet` except meta info.
2. Add new test "generate test files for checking compatibility with Spark 2.4" to `ParquetIOSuite` (marked as ignored). The parquet files above were generated by this test.
3. Modified "SPARK-31159: compatibility with Spark 2.4 in reading dates/timestamps" in `ParquetIOSuite` to use new parquet files.
### Why are the changes needed?
To improve test coverage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running `ParquetIOSuite`.
Closes#28630 from MaxGekk/parquet-files-update.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Use the correct API in AlterTableRecoverPartition tests to modify the `RDD_PARALLEL_LISTING_THRESHOLD` conf.
### Why are the changes needed?
The existing AlterTableRecoverPartitions test modify the RDD_PARALLEL_LISTING_THRESHOLD as a SQLConf using the withSQLConf API. But since, this is not a SQLConf, it is not overridden and so the test doesn't end up testing the required behaviour.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
This is UT Fix. UTs are still passing after the fix.
Closes#28634 from prakharjain09/SPARK-31810-fix-recover-partitions.
Authored-by: Prakhar Jain <prakharjain09@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to set the alias, and class name in its `ExpressionInfo` for `struct`.
- Class name in `ExpressionInfo`
- from: `org.apache.spark.sql.catalyst.expressions.NamedStruct`
- to:`org.apache.spark.sql.catalyst.expressions.CreateNamedStruct`
- Alias name: `named_struct(col1, v, ...)` -> `struct(v, ...)`
This PR takes over https://github.com/apache/spark/pull/28631
### Why are the changes needed?
To show the correct output name and class names to users.
### Does this PR introduce _any_ user-facing change?
Yes.
**Before:**
```scala
scala> sql("DESC FUNCTION struct").show(false)
+------------------------------------------------------------------------------------+
|function_desc |
+------------------------------------------------------------------------------------+
|Function: struct |
|Class: org.apache.spark.sql.catalyst.expressions.NamedStruct |
|Usage: struct(col1, col2, col3, ...) - Creates a struct with the given field values.|
+------------------------------------------------------------------------------------+
```
```scala
scala> sql("SELECT struct(1, 2)").show(false)
+------------------------------+
|named_struct(col1, 1, col2, 2)|
+------------------------------+
|[1, 2] |
+------------------------------+
```
**After:**
```scala
scala> sql("DESC FUNCTION struct").show(false)
+------------------------------------------------------------------------------------+
|function_desc |
+------------------------------------------------------------------------------------+
|Function: struct |
|Class: org.apache.spark.sql.catalyst.expressions.CreateNamedStruct |
|Usage: struct(col1, col2, col3, ...) - Creates a struct with the given field values.|
+------------------------------------------------------------------------------------+
```
```scala
scala> sql("SELECT struct(1, 2)").show(false)
+------------+
|struct(1, 2)|
+------------+
|[1, 2] |
+------------+
```
### How was this patch tested?
Manually tested, and Jenkins tests.
Closes#28633 from HyukjinKwon/SPARK-31808.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Convert `java.time.Instant` to `java.sql.Timestamp` in pushed down filters to ORC datasource when Java 8 time API enabled.
### Why are the changes needed?
The changes fix the exception raised while pushing date filters when `spark.sql.datetime.java8API.enabled` is set to `true`:
```
java.lang.IllegalArgumentException: Wrong value class java.time.Instant for TIMESTAMP.EQUALS leaf
at org.apache.hadoop.hive.ql.io.sarg.SearchArgumentImpl$PredicateLeafImpl.checkLiteralType(SearchArgumentImpl.java:192)
at org.apache.hadoop.hive.ql.io.sarg.SearchArgumentImpl$PredicateLeafImpl.<init>(SearchArgumentImpl.java:75)
```
### Does this PR introduce any user-facing change?
Yes
### How was this patch tested?
Added tests to `OrcFilterSuite`.
Closes#28636 from MaxGekk/orc-timestamp-filter-pushdown.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Five continuous pattern characters with 'G/M/L/E/u/Q/q' means Narrow-Text Style while we turn to use `java.time.DateTimeFormatterBuilder` since 3.0.0, which output the leading single letter of the value, e.g. `December` would be `D`. In Spark 2.4 they mean Full-Text Style.
In this PR, we explicitly disable Narrow-Text Style for these pattern characters.
### Why are the changes needed?
Without this change, there will be a silent data change.
### Does this PR introduce _any_ user-facing change?
Yes, queries with datetime operations using datetime patterns, e.g. `G/M/L/E/u` will fail if the pattern length is 5 and other patterns, e,g. 'k', 'm' also can accept a certain number of letters.
1. datetime patterns that are not supported by the new parser but the legacy will get SparkUpgradeException, e.g. "GGGGG", "MMMMM", "LLLLL", "EEEEE", "uuuuu", "aa", "aaa". 2 options are given to end-users, one is to use legacy mode, and the other is to follow the new online doc for correct datetime patterns
2, datetime patterns that are not supported by both the new parser and the legacy, e.g. "QQQQQ", "qqqqq", will get IllegalArgumentException which is captured by Spark internally and results NULL to end-users.
### How was this patch tested?
add unit tests
Closes#28592 from yaooqinn/SPARK-31771.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Re-generate results of:
- DateTimeBenchmark
- CSVBenchmark
- JsonBenchmark
in the environment:
| Item | Description |
| ---- | ----|
| Region | us-west-2 (Oregon) |
| Instance | r3.xlarge |
| AMI | ubuntu/images/hvm-ssd/ubuntu-bionic-18.04-amd64-server-20190722.1 (ami-06f2f779464715dc5) |
| Java | OpenJDK 64-Bit Server VM 1.8.0_242 and OpenJDK 64-Bit Server VM 11.0.6+10 |
### Why are the changes needed?
1. The PR https://github.com/apache/spark/pull/28576 changed date-time parser. The `DateTimeBenchmark` should confirm that the PR didn't slow down date/timestamp parsing.
2. CSV/JSON datasources are affected by the above PR too. This PR updates the benchmark results in the same environment as other benchmarks to have a base line for future optimizations.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running benchmarks via the script:
```python
#!/usr/bin/env python3
import os
from sparktestsupport.shellutils import run_cmd
benchmarks = [
['sql/test', 'org.apache.spark.sql.execution.benchmark.DateTimeBenchmark'],
['sql/test', 'org.apache.spark.sql.execution.datasources.csv.CSVBenchmark'],
['sql/test', 'org.apache.spark.sql.execution.datasources.json.JsonBenchmark']
]
print('Set SPARK_GENERATE_BENCHMARK_FILES=1')
os.environ['SPARK_GENERATE_BENCHMARK_FILES'] = '1'
for b in benchmarks:
print("Run benchmark: %s" % b[1])
run_cmd(['build/sbt', '%s:runMain %s' % (b[0], b[1])])
```
Closes#28613 from MaxGekk/missing-hour-year-benchmarks.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
As we support multiple catalogs with DataSourceV2, we may need the `CURRENT_CATALOG` value expression from the SQL standard.
`CURRENT_CATALOG` is a general value specification in the SQL Standard, described as:
> The value specified by CURRENT_CATALOG is the character string that represents the current default catalog name.
### Why are the changes needed?
improve catalog v2 with ANSI SQL standard.
### Does this PR introduce any user-facing change?
yes, add a new function `current_catalog()` to point the current active catalog
### How was this patch tested?
add ut
Closes#27006 from yaooqinn/SPARK-30352.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Add weight support in ClusteringEvaluator
### Why are the changes needed?
Currently, BinaryClassificationEvaluator, RegressionEvaluator, and MulticlassClassificationEvaluator support instance weight, but ClusteringEvaluator doesn't, so we will add instance weight support in ClusteringEvaluator.
### Does this PR introduce _any_ user-facing change?
Yes.
ClusteringEvaluator.setWeightCol
### How was this patch tested?
add new unit test
Closes#28553 from huaxingao/weight_evaluator.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Use `format()` methods for Java date-time types in `Row.jsonValue`. The PR https://github.com/apache/spark/pull/28582 added the methods to avoid conversions to days and microseconds.
### Why are the changes needed?
To avoid unnecessary overhead of converting Java date-time types to micros/days before formatting. Also formatters have to convert input micros/days back to Java types to pass instances to standard library API.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By existing tests in `RowJsonSuite`.
Closes#28620 from MaxGekk/toJson-format-Java-datetime-types.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Add unit tests to the 'number of output rows metric' for some join types in the SQLMetricSuite. A list of unit tests added are as follows.
- ShuffledHashJoin: leftOuter, RightOuter, LeftAnti, LeftSemi
- BroadcastNestedLoopJoin: RightOuter
- BroadcastHashJoin: LeftAnti
### Why are the changes needed?
For some combinations of JoinType and Join algorithm there is no test coverage for the 'number of output rows' metric.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
I added debug statements in the code to ensure the correct combination if JoinType and Join algorithms are triggered.
I further used Intellij debugger to test the same.
Closes#28330 from sririshindra/SPARK-31377.
Authored-by: rishi <spothireddi@cloudera.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
UnionRDD of PairRDDs causing a bug. The fix is to check for instance type before proceeding
### Why are the changes needed?
Changes are needed to avoid users running into issues with union rdd operation with any other type other than JavaRDD.
### Does this PR introduce _any_ user-facing change?
Yes
Before:
SparkSession available as 'spark'.
>>> rdd1 = sc.parallelize([1,2,3,4,5])
>>> rdd2 = sc.parallelize([6,7,8,9,10])
>>> pairRDD1 = rdd1.zip(rdd2)
>>> unionRDD1 = sc.union([pairRDD1, pairRDD1])
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/gs/spark/latest/python/pyspark/context.py", line 870,
in union jrdds[i] = rdds[i]._jrdd
File "/home/gs/spark/latest/python/lib/py4j-0.10.9-src.zip/py4j/java_collections.py", line 238, in setitem File "/home/gs/spark/latest/python/lib/py4j-0.10.9-src.zip/py4j/java_collections.py", line 221,
in __set_item File "/home/gs/spark/latest/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 332, in get_return_value py4j.protocol.Py4JError: An error occurred while calling None.None. Trace: py4j.Py4JException: Cannot convert org.apache.spark.api.java.JavaPairRDD to org.apache.spark.api.java.JavaRDD at py4j.commands.ArrayCommand.convertArgument(ArrayCommand.java:166) at py4j.commands.ArrayCommand.setArray(ArrayCommand.java:144) at py4j.commands.ArrayCommand.execute(ArrayCommand.java:97) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:748)
After:
>>> rdd2 = sc.parallelize([6,7,8,9,10])
>>> pairRDD1 = rdd1.zip(rdd2)
>>> unionRDD1 = sc.union([pairRDD1, pairRDD1])
>>> unionRDD1.collect()
[(1, 6), (2, 7), (3, 8), (4, 9), (5, 10), (1, 6), (2, 7), (3, 8), (4, 9), (5, 10)]
### How was this patch tested?
Tested with the reproduced piece of code above manually
Closes#28603 from redsanket/SPARK-31788.
Authored-by: schintap <schintap@verizonmedia.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to use the style that is compatible with both python 2 and 3.
### Why are the changes needed?
This will help python 3 migration.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual.
Closes#28632 from williamhyun/use_python3_style.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
add getMetrics in Evaluators to get the corresponding Metrics instance, so users can use it to get any of the metrics scores. For example:
```
val trainer = new LinearRegression
val model = trainer.fit(dataset)
val predictions = model.transform(dataset)
val evaluator = new RegressionEvaluator()
val metrics = evaluator.getMetrics(predictions)
val rmse = metrics.rootMeanSquaredError
val r2 = metrics.r2
val mae = metrics.meanAbsoluteError
val variance = metrics.explainedVariance
```
### Why are the changes needed?
Currently, Evaluator.evaluate only access to one metrics, but most users may need to get multiple metrics. This PR adds getMetrics in all the Evaluators, so users can use it to get an instance of the corresponding Metrics to get any of the metrics they want.
### Does this PR introduce _any_ user-facing change?
Yes. Add getMetrics in Evaluators.
For example:
```
/**
* Get a RegressionMetrics, which can be used to get any of the regression
* metrics such as rootMeanSquaredError, meanSquaredError, etc.
*
* param dataset a dataset that contains labels/observations and predictions.
* return RegressionMetrics
*/
Since("3.1.0")
def getMetrics(dataset: Dataset[_]): RegressionMetrics
```
### How was this patch tested?
Add new unit tests
Closes#28590 from huaxingao/getMetrics.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Currently, the data source scan node stores all the paths in its metadata. The metadata is kept when a SparkPlan is converted into SparkPlanInfo. SparkPlanInfo can be used to construct the Spark plan graph in UI.
However, the paths can be very large (e.g. it can be many partitions after partition pruning), while UI pages only require up to 100 bytes for the location metadata. We can reduce the paths stored in metadata to reduce memory usage.
### Why are the changes needed?
Reduce unnecessary memory cost.
In the heap dump of a driver, the SparkPlanInfo instances are quite large and it should be avoided:
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit tests
Closes#28610 from gengliangwang/improveLocationMetadata.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This PR aims to upgrade `kubernetes-client` library to bring the JDK8 related fixes. Please note that JDK11 works fine without any problem.
- https://github.com/fabric8io/kubernetes-client/releases/tag/v4.9.2
- JDK8 always uses http/1.1 protocol (Prevent OkHttp from wrongly enabling http/2)
### Why are the changes needed?
OkHttp "wrongly" detects the Platform as Jdk9Platform on JDK 8u251.
- https://github.com/fabric8io/kubernetes-client/issues/2212
- https://stackoverflow.com/questions/61565751/why-am-i-not-able-to-run-sparkpi-example-on-a-kubernetes-k8s-cluster
Although there is a workaround `export HTTP2_DISABLE=true` and `Downgrade JDK or K8s`, we had better avoid this problematic situation.
### Does this PR introduce _any_ user-facing change?
No. This will recover the failures on JDK 8u252.
### How was this patch tested?
- [x] Pass the Jenkins UT (https://github.com/apache/spark/pull/28601#issuecomment-632474270)
- [x] Pass the Jenkins K8S IT with the K8s 1.13 (https://github.com/apache/spark/pull/28601#issuecomment-632438452)
- [x] Manual testing with K8s 1.17.3. (Below)
**v1.17.6 result (on Minikube)**
```
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark with Python2 to test a pyfiles example
- Run PySpark with Python3 to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- Test basic decommissioning
Run completed in 8 minutes, 27 seconds.
Total number of tests run: 19
Suites: completed 2, aborted 0
Tests: succeeded 19, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#28601 from dongjoon-hyun/SPARK-K8S-CLIENT.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Add Pagination Support for structured streaming page. Now both tables `Active Queries` and `Completed Queries` will have pagination.
To implement pagination, pagination framework from #7399 is used.
* Also tables will only be shown if there is at least one entry in the table.
### Why are the changes needed?
* This will help users in analysing their structured streaming queries in much better way.
* Other Web UI pages support pagination in their table. So this will make web UI more consistent across pages.
* This can prevent potential OOM errors.
### Does this PR introduce _any_ user-facing change?
Yes. Both tables will support pagination.
### How was this patch tested?
Manually. I will add snapshots soon.
Closes#28485 from iRakson/SPARK-31642.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Kousuke Saruta <sarutak@oss.nttdata.com>
### What changes were proposed in this pull request?
Increase the timeout and register the listener earlier to avoid any race condition of the job starting before the listener is registered.
### Why are the changes needed?
The test is currently semi-flaky.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
I'm currently running the following bash script on my dev machine to verify the flakiness decreases. It has gotten to 356 iterations without any test failures so I believe issue is fixed.
```
set -ex
./build/sbt clean compile package
((failures=0))
for (( i=0;i<1000;++i )); do
echo "Run $i"
((failed=0))
./build/sbt "core/testOnly org.apache.spark.scheduler.WorkerDecommissionSuite" || ((failed=1))
echo "Resulted in $failed"
((failures=failures+failed))
echo "Current status is failures: $failures out of $i runs"
done
```
Closes#28614 from holdenk/SPARK-31791-improve-cache-block-migration-test-reliability.
Authored-by: Holden Karau <hkarau@apple.com>
Signed-off-by: Holden Karau <hkarau@apple.com>
### What changes were proposed in this pull request?
This PR intends to add trivial tests to check https://github.com/apache/spark/pull/27024 has already been fixed in the master.
Closes#27024
### Why are the changes needed?
For test coverage.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Added tests.
Closes#28604 from maropu/SPARK-29854.
Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
### What changes were proposed in this pull request?
This patch adds the new method `getLatestBatchId()` in CompactibleFileStreamLog in complement of getLatest() which doesn't read the content of the latest batch metadata log file, and apply to both FileStreamSource and FileStreamSink to avoid unnecessary latency on reading log file.
### Why are the changes needed?
Once compacted metadata log file becomes huge, writing outputs for the compact + 1 batch is also affected due to unnecessarily reading the compacted metadata log file. This unnecessary latency can be simply avoided.
### Does this PR introduce any user-facing change?
No.
### How was this patch tested?
New UT. Also manually tested under query which has huge metadata log on file stream sink:
> before applying the patch
> after applying the patch
Peaks are compact batches - please compare the next batch after compact batches, especially the area of "light brown".
Closes#27664 from HeartSaVioR/SPARK-30915.
Authored-by: Jungtaek Lim (HeartSaVioR) <kabhwan.opensource@gmail.com>
Signed-off-by: Shixiong Zhu <zsxwing@gmail.com>
### What changes were proposed in this pull request?
Add and register three new functions: `TIMESTAMP_SECONDS`, `TIMESTAMP_MILLIS` and `TIMESTAMP_MICROS`
A test is added.
Reference: [BigQuery](https://cloud.google.com/bigquery/docs/reference/standard-sql/timestamp_functions?hl=en#timestamp_seconds)
### Why are the changes needed?
People will have convenient way to get timestamps from seconds,milliseconds and microseconds.
### Does this PR introduce _any_ user-facing change?
Yes, people will have the following ways to get timestamp:
```scala
sql("select TIMESTAMP_SECONDS(t.a) as timestamp from values(1230219000),(-1230219000) as t(a)").show(false)
```
```
+-------------------------+
|timestamp |
+-------------------------+
|2008-12-25 23:30:00|
|1931-01-07 16:30:00|
+-------------------------+
```
```scala
sql("select TIMESTAMP_MILLIS(t.a) as timestamp from values(1230219000123),(-1230219000123) as t(a)").show(false)
```
```
+-------------------------------+
|timestamp |
+-------------------------------+
|2008-12-25 23:30:00.123|
|1931-01-07 16:29:59.877|
+-------------------------------+
```
```scala
sql("select TIMESTAMP_MICROS(t.a) as timestamp from values(1230219000123123),(-1230219000123123) as t(a)").show(false)
```
```
+------------------------------------+
|timestamp |
+------------------------------------+
|2008-12-25 23:30:00.123123|
|1931-01-07 16:29:59.876877|
+------------------------------------+
```
### How was this patch tested?
Unit test.
Closes#28534 from TJX2014/master-SPARK-31710.
Authored-by: TJX2014 <xiaoxingstack@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR mainly adds two things.
1. Real headless browser support for UI test
2. A test suite using headless Chrome as one instance of those browsers.
Also, for environment where Chrome and Chrome driver is not installed, `ChromeUITest` tag is added to filter out the test suite.
### Why are the changes needed?
In the current master, there are two problems for UI test.
1. Lots of tests especially JavaScript related ones are done manually.
Appearance is better to be confirmed by our eyes but logic should be tested by test cases ideally.
2. Compared to the real web browsers, HtmlUnit doesn't seem to support JavaScript enough.
I added a JavaScript related test before for SPARK-31534 using HtmlUnit which is simple library based headless browser for test.
The test I added works somehow but some JavaScript related error is shown in unit-tests.log.
```
======= EXCEPTION START ========
Exception class=[net.sourceforge.htmlunit.corejs.javascript.JavaScriptException]
com.gargoylesoftware.htmlunit.ScriptException: Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)". (http://192.168.1.209:60724/static/jquery-3.4.1.min.js#2)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$HtmlUnitContextAction.run(JavaScriptEngine.java:904)
at net.sourceforge.htmlunit.corejs.javascript.Context.call(Context.java:628)
at net.sourceforge.htmlunit.corejs.javascript.ContextFactory.call(ContextFactory.java:515)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine.callFunction(JavaScriptEngine.java:835)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine.callFunction(JavaScriptEngine.java:807)
at com.gargoylesoftware.htmlunit.InteractivePage.executeJavaScriptFunctionIfPossible(InteractivePage.java:216)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptFunctionJob.runJavaScript(JavaScriptFunctionJob.java:52)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptExecutionJob.run(JavaScriptExecutionJob.java:102)
at com.gargoylesoftware.htmlunit.javascript.background.JavaScriptJobManagerImpl.runSingleJob(JavaScriptJobManagerImpl.java:426)
at com.gargoylesoftware.htmlunit.javascript.background.DefaultJavaScriptExecutor.run(DefaultJavaScriptExecutor.java:157)
at java.lang.Thread.run(Thread.java:748)
Caused by: net.sourceforge.htmlunit.corejs.javascript.JavaScriptException: Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)". (http://192.168.1.209:60724/static/jquery-3.4.1.min.js#2)
at net.sourceforge.htmlunit.corejs.javascript.Interpreter.interpretLoop(Interpreter.java:1009)
at net.sourceforge.htmlunit.corejs.javascript.Interpreter.interpret(Interpreter.java:800)
at net.sourceforge.htmlunit.corejs.javascript.InterpretedFunction.call(InterpretedFunction.java:105)
at net.sourceforge.htmlunit.corejs.javascript.ContextFactory.doTopCall(ContextFactory.java:413)
at com.gargoylesoftware.htmlunit.javascript.HtmlUnitContextFactory.doTopCall(HtmlUnitContextFactory.java:252)
at net.sourceforge.htmlunit.corejs.javascript.ScriptRuntime.doTopCall(ScriptRuntime.java:3264)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$4.doRun(JavaScriptEngine.java:828)
at com.gargoylesoftware.htmlunit.javascript.JavaScriptEngine$HtmlUnitContextAction.run(JavaScriptEngine.java:889)
... 10 more
JavaScriptException value = Error: TOOLTIP: Option "sanitizeFn" provided type "window" but expected type "(null|function)".
== CALLING JAVASCRIPT ==
function () {
throw e;
}
======= EXCEPTION END ========
```
I tried to upgrade HtmlUnit to 2.40.0 but what is worse, the test become not working even though it works on real browsers like Chrome, Safari and Firefox without error.
```
[info] UISeleniumSuite:
[info] - SPARK-31534: text for tooltip should be escaped *** FAILED *** (17 seconds, 745 milliseconds)
[info] The code passed to eventually never returned normally. Attempted 2 times over 12.910785232 seconds. Last failure message: com.gargoylesoftware.htmlunit.ScriptException: ReferenceError: Assignment to undefined "regeneratorRuntime" in strict mode (http://192.168.1.209:62132/static/vis-timeline-graph2d.min.js#52(Function)#1)
```
To resolve those problems, it's better to support headless browser for UI test.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
I tested with following patterns. Both Chrome and Chrome driver should be installed to test.
1. sbt / with chromedriver / include tag (expect to succeed)
`build/sbt -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite"`
2. sbt / with chromedriver / exclude tag (expect to be ignored)
`build/sbt -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver "testOnly org.apache.spark.ui.ChromeUISeleniumSuite -l org.apache.spark.tags.ChromeUITest"`
3. sbt / without chromedriver / include tag (expect to be failed)
`build/sbt "testOnly org.apache.spark.ui.ChromeUISeleniumSuite"`
4. sbt / without chromedriver / exclude tag (expect to be skipped)
`build/sbt -Dtest.exclude.tags=org.apache.spark.tags.ChromeUITest "testOnly org.apache.spark.ui.ChromeUISeleniumSuite"`
5. Maven / wth chromedriver / include tag (expect to succeed)
`build/mvn -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
6. Maven / with chromedriver / exclude tag (expect to be skipped)
`build/mvn -Dtest.exclude.tags="org.apache.spark.tags.ChromeUITest" -Dspark.test.webdriver.chrome.driver=/path/to/chromedriver -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
7. Maven / without chromedriver / include tag (expect to be failed)
`build/mvn -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
8. Maven / without chromedriver / exclude tag (expect to be skipped)
`build/mvn -Dtest.exclude.tags=org.apache.spark.tags.ChromeUITest -Dtest=none -DwildcardSuites=org.apache.spark.ui.ChromeUISeleniumSuite test`
Closes#28578 from sarutak/real-headless-browser-support.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
add docs for sql migration-guide
### Why are the changes needed?
let user know more about the cast scenarios in which Hive and Spark generate different results
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
no need to test
Closes#28605 from GuoPhilipse/spark-docs.
Lead-authored-by: GuoPhilipse <guofei_ok@126.com>
Co-authored-by: GuoPhilipse <46367746+GuoPhilipse@users.noreply.github.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR allows missing hour fields when parsing date/timestamp string, with 0 as the default value.
If the year field is missing, this PR still fail the query by default, but provides a new legacy config to allow it and use 1970 as the default value. It's not a good default value, as it is not a leap year, which means that it would never parse Feb 29. We just pick it for backward compatibility.
### Why are the changes needed?
To keep backward compatibility with Spark 2.4.
### Does this PR introduce _any_ user-facing change?
Yes.
Spark 2.4:
```
scala> sql("select to_timestamp('16', 'dd')").show
+------------------------+
|to_timestamp('16', 'dd')|
+------------------------+
| 1970-01-16 00:00:00|
+------------------------+
scala> sql("select to_date('16', 'dd')").show
+-------------------+
|to_date('16', 'dd')|
+-------------------+
| 1970-01-16|
+-------------------+
scala> sql("select to_timestamp('2019 40', 'yyyy mm')").show
+----------------------------------+
|to_timestamp('2019 40', 'yyyy mm')|
+----------------------------------+
| 2019-01-01 00:40:00|
+----------------------------------+
scala> sql("select to_timestamp('2019 10:10:10', 'yyyy hh:mm:ss')").show
+----------------------------------------------+
|to_timestamp('2019 10:10:10', 'yyyy hh:mm:ss')|
+----------------------------------------------+
| 2019-01-01 10:10:10|
+----------------------------------------------+
```
in branch 3.0
```
scala> sql("select to_timestamp('16', 'dd')").show
+--------------------+
|to_timestamp(16, dd)|
+--------------------+
| null|
+--------------------+
scala> sql("select to_date('16', 'dd')").show
+---------------+
|to_date(16, dd)|
+---------------+
| null|
+---------------+
scala> sql("select to_timestamp('2019 40', 'yyyy mm')").show
+------------------------------+
|to_timestamp(2019 40, yyyy mm)|
+------------------------------+
| 2019-01-01 00:00:00|
+------------------------------+
scala> sql("select to_timestamp('2019 10:10:10', 'yyyy hh:mm:ss')").show
+------------------------------------------+
|to_timestamp(2019 10:10:10, yyyy hh:mm:ss)|
+------------------------------------------+
| 2019-01-01 00:00:00|
+------------------------------------------+
```
After this PR, the behavior becomes the same as 2.4, if the legacy config is enabled.
### How was this patch tested?
new tests
Closes#28576 from cloud-fan/bug.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
The function `HistoryServerDiskManager`.`updateAccessTime()` would recompute the application store directory size every time it's triggered, this effort could be avoided because we already computed the new size outside the function call.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing test cases.
Closes#28579 from jiangxb1987/updateInfo.
Authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
Change from `messages.toList.iterator` to `Iterator.single(messages.toList)`.
### Why are the changes needed?
In this test, the expected result of `rdd2.collect().head` should actually be `List("0", "1", "2", "3")` but is `"0"` now.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated test.
Thanks WeichenXu123 reported this problem.
Closes#28596 from Ngone51/fix_allgather_test.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
Add `withAllParquetReaders` to `ParquetTest`. The function allow to run a block of code for all available Parquet readers.
### Why are the changes needed?
1. It simplifies tests
2. Allow to test all parquet readers that could be available in projects based on Apache Spark.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running affected test suites.
Closes#28598 from MaxGekk/add-withAllParquetReaders.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
This reverts commit 92877c4ef2.
Closes#28602 from gengliangwang/revertSPARK-31765.
Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This PR upgrades HtmlUnit.
Selenium and Jetty also upgraded because of dependency.
### Why are the changes needed?
Recently, a security issue which affects HtmlUnit is reported.
https://nvd.nist.gov/vuln/detail/CVE-2020-5529
According to the report, arbitrary code can be run by malicious users.
HtmlUnit is used for test so the impact might not be large but it's better to upgrade it just in case.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing testcases.
Closes#28585 from sarutak/upgrade-htmlunit.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
### What changes were proposed in this pull request?
This adds UI updates to support stage level scheduling and ResourceProfiles. 3 main things have been added. ResourceProfile id added to the Stage page, the Executors page now has an optional selectable column to show the ResourceProfile Id of each executor, and the Environment page now has a section with the ResourceProfile ids. Along with this the rest api for environment page was updated to include the Resource profile information.
I debating on splitting the resource profile information into its own page but I wasn't sure it called for a completely separate page. Open to peoples thoughts on this.
Screen shots:
### Why are the changes needed?
For user to be able to know what resource profile was used with which stage and executors. The resource profile information is also available so user debugging can see exactly what resources were requested with that profile.
### Does this PR introduce any user-facing change?
Yes, UI updates.
### How was this patch tested?
Unit tests and tested on yarn both active applications and with the history server.
Closes#28094 from tgravescs/SPARK-29303-pr.
Lead-authored-by: Thomas Graves <tgraves@nvidia.com>
Co-authored-by: Thomas Graves <tgraves@apache.org>
Signed-off-by: Thomas Graves <tgraves@apache.org>
### What changes were proposed in this pull request?
Currently while implementing pagination using the existing pagination framework, a lot of code is being copied as pointed out [here](https://github.com/apache/spark/pull/28485#pullrequestreview-408881656).
I introduced some changes in `PagedTable` which is the main trait for implementing the pagination.
* Added function for getting table parameters.
* Added a function for table header row. This will help in maintaining consistency across the tables. All the header rows across tables will be consistent now.
### Why are the changes needed?
* A lot of code is copied every time pagination is implemented for any table.
* Code readability is not great as lot of HTML is embedded.
* Paginating other tables will be a lot easier now.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually. This is mainly refactoring work, no new functionality introduced. Existing test cases should pass.
Closes#28512 from iRakson/refactorPaginationFramework.
Authored-by: iRakson <raksonrakesh@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
## What changes were proposed in this pull request?
This change was made as a result of the conversation on https://issues.apache.org/jira/browse/SPARK-31354 and is intended to continue work from that ticket here.
This change fixes a memory leak where SparkSession listeners are never cleared off of the SparkContext listener bus.
Before running this PR, the following code:
```
SparkSession.builder().master("local").getOrCreate()
SparkSession.clearActiveSession()
SparkSession.clearDefaultSession()
SparkSession.builder().master("local").getOrCreate()
SparkSession.clearActiveSession()
SparkSession.clearDefaultSession()
```
would result in a SparkContext with the following listeners on the listener bus:
```
[org.apache.spark.status.AppStatusListener5f610071,
org.apache.spark.HeartbeatReceiverd400c17,
org.apache.spark.sql.SparkSession$$anon$125849aeb, <-First instance
org.apache.spark.sql.SparkSession$$anon$1fadb9a0] <- Second instance
```
After this PR, the execution of the same code above results in SparkContext with the following listeners on the listener bus:
```
[org.apache.spark.status.AppStatusListener5f610071,
org.apache.spark.HeartbeatReceiverd400c17,
org.apache.spark.sql.SparkSession$$anon$125849aeb] <-One instance
```
## How was this patch tested?
* Unit test included as a part of the PR
Closes#28128 from vinooganesh/vinooganesh/SPARK-27958.
Lead-authored-by: Vinoo Ganesh <vinoo.ganesh@gmail.com>
Co-authored-by: Vinoo Ganesh <vganesh@palantir.com>
Co-authored-by: Vinoo Ganesh <vinoo@safegraph.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
1. Add new methods that accept date-time Java types to the DateFormatter and TimestampFormatter traits. The methods format input date-time instances to strings:
- TimestampFormatter:
- `def format(ts: Timestamp): String`
- `def format(instant: Instant): String`
- DateFormatter:
- `def format(date: Date): String`
- `def format(localDate: LocalDate): String`
2. Re-use the added methods from `HiveResult.toHiveString`
3. Borrow the code for formatting of `java.sql.Timestamp` from Spark 2.4 `DateTimeUtils.timestampToString` to `FractionTimestampFormatter` because legacy formatters don't support variable length patterns for seconds fractions.
### Why are the changes needed?
To avoid unnecessary overhead of converting Java date-time types to micros/days before formatting. Also formatters have to convert input micros/days back to Java types to pass instances to standard library API.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By existing tests for toHiveString and new tests in `TimestampFormatterSuite`.
Closes#28582 from MaxGekk/opt-format-old-types.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR aims to skip R image building and one R test during integration tests by using `--exclude-tags r`.
### Why are the changes needed?
We have only one R integration test case, `Run SparkR on simple dataframe.R example`, for submission test coverage. Since this is rarely changed, we can skip this and save the efforts required for building the whole R image and running the single test.
```
KubernetesSuite:
...
- Run SparkR on simple dataframe.R example
Run completed in 10 minutes, 20 seconds.
Total number of tests run: 20
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the K8S integration test and do the following manually. (Note that R test is skipped)
```
$ resource-managers/kubernetes/integration-tests/dev/dev-run-integration-tests.sh --deploy-mode docker-for-desktop --exclude-tags r --spark-tgz $PWD/spark-*.tgz
...
KubernetesSuite:
- Run SparkPi with no resources
- Run SparkPi with a very long application name.
- Use SparkLauncher.NO_RESOURCE
- Run SparkPi with a master URL without a scheme.
- Run SparkPi with an argument.
- Run SparkPi with custom labels, annotations, and environment variables.
- All pods have the same service account by default
- Run extraJVMOptions check on driver
- Run SparkRemoteFileTest using a remote data file
- Run SparkPi with env and mount secrets.
- Run PySpark on simple pi.py example
- Run PySpark with Python2 to test a pyfiles example
- Run PySpark with Python3 to test a pyfiles example
- Run PySpark with memory customization
- Run in client mode.
- Start pod creation from template
- PVs with local storage
- Launcher client dependencies
- Test basic decommissioning
Run completed in 10 minutes, 23 seconds.
Total number of tests run: 19
Suites: completed 2, aborted 0
Tests: succeeded 19, failed 0, canceled 0, ignored 0, pending 0
All tests passed.
```
Closes#28594 from dongjoon-hyun/SPARK-31780.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
Added `since 3.0.0` for `ResourceDiscoveryScriptPlugin` and `ResourceInformation`.
### Why are the changes needed?
It's required for exposed APIs(https://github.com/apache/spark/pull/27689#discussion_r426488851).
### Does this PR introduce _any_ user-facing change?
Yes, they can easily know when does Spark introduces the API.
### How was this patch tested?
Pass Jenkins.
Closes#28591 from Ngone51/followup-30689.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This is a recreation of #28155, which was reverted due to causing test failures.
The update methods in HiveThriftServer2Listener now check if the parameter operation/session ID actually exist in the `sessionList` and `executionList` respectively. This prevents NullPointerExceptions if the operation or session ID is unknown. Instead, a warning is written to the log.
To improve robustness, we also make the following changes in HiveSessionImpl.close():
- Catch any exception thrown by `operationManager.closeOperation`. If for any reason this throws an exception, other operations are not prevented from being closed.
- Handle not being able to access the scratch directory. When closing, all `.pipeout` files are removed from the scratch directory, which would have resulted in an NPE if the directory does not exist.
### Why are the changes needed?
The listener's update methods would throw an exception if the operation or session ID is unknown. In Spark 2, where the listener is called directly, this changes the caller's control flow. In Spark 3, the exception is caught by the ListenerBus but results in an uninformative NullPointerException.
In HiveSessionImpl.close(), if an exception is thrown when closing an operation, all following operations are not closed.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
Unit tests
Closes#28544 from alismess-db/hive-thriftserver-listener-update-safer-2.
Authored-by: Ali Smesseim <ali.smesseim@databricks.com>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
in `spark-daemon.sh`, `spark_rotate_log()` accepts `$2` as a custom setting for the number of maximum rotate log files, but this part of code is actually never used.
This PR adds `SPARK_LOG_MAX_FILES` environment variable to represent the maximum log files of Spark daemons can rotate to.
### Why are the changes needed?
the logs files that all spark daemons are hardcoded as 5, but it supposed to be configurable
### Does this PR introduce _any_ user-facing change?
yes, SPARK_LOG_MAX_FILES is added to represent the maximum log files of Spark daemons can rotate to.
### How was this patch tested?
verify locally for the added shell script:
```shell
kentyaohulk ~ SPARK_LOG_MAX_FILES=1 sh test.sh
1
kentyaohulk ~ SPARK_LOG_MAX_FILES=a sh test.sh
Error: SPARK_LOG_MAX_FILES must be a postive number
✘ kentyaohulk ~ SPARK_LOG_MAX_FILES=b sh test.sh
Error: SPARK_LOG_MAX_FILES must be a postive number
✘ kentyaohulk ~ SPARK_LOG_MAX_FILES=-1 sh test.sh
Error: SPARK_LOG_MAX_FILES must be a postive number
✘ kentyaohulk ~ sh test.sh
5
✘ kentyaohulk ~ cat test.sh
#!/bin/bash
if [[ -z ${SPARK_LOG_MAX_FILES} ]] ; then
num=5
elif [[ ${SPARK_LOG_MAX_FILES} -gt 0 ]]; then
num=${SPARK_LOG_MAX_FILES}
else
echo "Error: SPARK_LOG_MAX_FILES must be a postive number"
exit -1
fi
```
Closes#28580 from yaooqinn/SPARK-31759.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Added MDC support in all thread pools.
ThreaddUtils create new pools that pass over MDC.
### Why are the changes needed?
In many cases, it is very hard to understand from which actions the logs in the executor come from.
when you are doing multi-thread work in the driver and send actions in parallel.
### Does this PR introduce any user-facing change?
No
### How was this patch tested?
No test added because no new functionality added it is thread pull change and all current tests pass.
Closes#26624 from igreenfield/master.
Authored-by: Izek Greenfield <igreenfield@axiomsl.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR aims to add Spark version prefix during generating test image tag for K8s integration testing.
### Why are the changes needed?
This helps to distinguish the images by version.
**BEFORE**
```
$ docker images | grep kubespark
kubespark/spark-py F7188CBD-AE08-4705-9C8A-D0DD3DC8B86F ...
kubespark/spark F7188CBD-AE08-4705-9C8A-D0DD3DC8B86F ...
```
**AFTER**
```
$ docker images | grep kubespark
kubespark/spark-py 3.1.0-SNAPSHOT_F7188CBD-AE08-4705-9C8A-D0DD3DC8B86F ...
kubespark/spark 3.1.0-SNAPSHOT_F7188CBD-AE08-4705-9C8A-D0DD3DC8B86F ...
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the K8s integration test.
```
...
Successfully tagged kubespark/spark:3.1.0-SNAPSHOT_688b46c8-c119-404d-aadb-d05a14262db7
...
Successfully tagged kubespark/spark-py:3.1.0-SNAPSHOT_688b46c8-c119-404d-aadb-d05a14262db7
...
Successfully tagged kubespark/spark-r:3.1.0-SNAPSHOT_688b46c8-c119-404d-aadb-d05a14262db7
```
Closes#28587 from dongjoon-hyun/SPARK-31766.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR proposes to only allow the import of `ResourceInformation` as below:
```
pyspark.resource.ResourceInformation
```
instead of
```
pyspark.ResourceInformation
pyspark.resource.ResourceInformation
```
because `pyspark.resource` is a separate module, and it is documented so.
The constructor of `ResourceInformation` isn't supposed to directly call anyway.
### Why are the changes needed?
To keep the code structure coherent.
### Does this PR introduce _any_ user-facing change?
No, it will be in the unreleased branches.
### How was this patch tested?
Manually tested via importing:
Before:
```python
>>> import pyspark
>>> pyspark.ResourceInformation
<class 'pyspark.resource.information.ResourceInformation'>
>>> pyspark.resource.ResourceInformation
<class 'pyspark.resource.information.ResourceInformation'>
```
After:
```python
>>> import pyspark
>>> pyspark.ResourceInformation
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: module 'pyspark' has no attribute 'ResourceInformation'
>>> pyspark.resource.ResourceInformation
<class 'pyspark.resource.information.ResourceInformation'>
```
Also tested via
```bash
cd python
./run-tests --python-executables=python3 --modules=pyspark-core,pyspark-resource
```
Jenkins will test and existing tests should cover.
Closes#28589 from HyukjinKwon/SPARK-31767.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
This PR adds a private `WriteBuilder` mixin trait: `SupportsStreamingUpdate`, so that the builtin v2 streaming sinks can still support the update mode.
Note: it's private because we don't have a proper design yet. I didn't take the proposal in https://github.com/apache/spark/pull/23702#discussion_r258593059 because we may want something more general, like updating by an expression `key1 = key2 + 10`.
### Why are the changes needed?
In Spark 2.4, all builtin v2 streaming sinks support all streaming output modes, and v2 sinks are enabled by default, see https://issues.apache.org/jira/browse/SPARK-22911
It's too risky for 3.0 to go back to v1 sinks, so I propose to add a private trait to fix builtin v2 sinks, to keep backward compatibility.
### Does this PR introduce _any_ user-facing change?
Yes, now all the builtin v2 streaming sinks support all streaming output modes, which is the same as 2.4
### How was this patch tested?
existing tests.
Closes#28523 from cloud-fan/update.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Eliminate the `UpCast` if it's child data type is already decimal type.
### Why are the changes needed?
While deserializing internal `Decimal` value to external `BigDecimal`(Java/Scala) value, Spark should also respect `Decimal`'s precision and scale, otherwise it will cause precision lost and look weird in some cases, e.g.:
```
sql("select cast(11111111111111111111111111111111111111 as decimal(38, 0)) as d")
.write.mode("overwrite")
.parquet(f.getAbsolutePath)
// can fail
spark.read.parquet(f.getAbsolutePath).as[BigDecimal]
```
```
[info] org.apache.spark.sql.AnalysisException: Cannot up cast `d` from decimal(38,0) to decimal(38,18).
[info] The type path of the target object is:
[info] - root class: "scala.math.BigDecimal"
[info] You can either add an explicit cast to the input data or choose a higher precision type of the field in the target object;
[info] at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveUpCast$$fail(Analyzer.scala:3060)
[info] at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$33$$anonfun$applyOrElse$174.applyOrElse(Analyzer.scala:3087)
[info] at org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$33$$anonfun$applyOrElse$174.applyOrElse(Analyzer.scala:3071)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$1(TreeNode.scala:309)
[info] at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:72)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:309)
[info] at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:314)
```
### Does this PR introduce _any_ user-facing change?
Yes, for cases(cause precision lost) mentioned above will fail before this change but run successfully after this change.
### How was this patch tested?
Added tests.
Closes#28572 from Ngone51/fix_encoder.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR is kind of a followup for SPARK-29641 and SPARK-28234. This PR proposes:
1.. Document the new `pyspark.resource` module introduced at 95aec091e4, in PySpark API docs.
2.. Move classes into fewer and simpler modules
Before:
```
pyspark
├── resource
│ ├── executorrequests.py
│ │ ├── class ExecutorResourceRequest
│ │ └── class ExecutorResourceRequests
│ ├── taskrequests.py
│ │ ├── class TaskResourceRequest
│ │ └── class TaskResourceRequests
│ ├── resourceprofilebuilder.py
│ │ └── class ResourceProfileBuilder
│ ├── resourceprofile.py
│ │ └── class ResourceProfile
└── resourceinformation
└── class ResourceInformation
```
After:
```
pyspark
└── resource
├── requests.py
│ ├── class ExecutorResourceRequest
│ ├── class ExecutorResourceRequests
│ ├── class TaskResourceRequest
│ └── class TaskResourceRequests
├── profile.py
│ ├── class ResourceProfileBuilder
│ └── class ResourceProfile
└── information.py
└── class ResourceInformation
```
3.. Minor docstring fix e.g.:
```diff
- param name the name of the resource
- param addresses an array of strings describing the addresses of the resource
+ :param name: the name of the resource
+ :param addresses: an array of strings describing the addresses of the resource
+
+ .. versionadded:: 3.0.0
```
### Why are the changes needed?
To document APIs, and move Python modules to fewer and simpler modules.
### Does this PR introduce _any_ user-facing change?
No, the changes are in unreleased branches.
### How was this patch tested?
Manually tested via:
```bash
cd python
./run-tests --python-executables=python3 --modules=pyspark-core
./run-tests --python-executables=python3 --modules=pyspark-resource
```
Closes#28569 from HyukjinKwon/SPARK-28234-SPARK-29641-followup.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
### What changes were proposed in this pull request?
With SPARK-18107, we will disable the underlying replace(overwrite) and instead do delete in spark side and only do copy in hive side to bypass the performance issue - [HIVE-11940](https://issues.apache.org/jira/browse/HIVE-11940)
Conditionally, if the table location and partition location do not belong to the same `FileSystem`, We should not disable hive overwrite. Otherwise, hive will use the `FileSystem` instance belong to the table location to copy files, which will fail in `FileSystem#checkPath`
https://github.com/apache/hive/blob/rel/release-2.3.7/ql/src/java/org/apache/hadoop/hive/ql/metadata/Hive.java#L1657
In this PR, for Hive 2.0.0 and onwards, as [HIVE-11940](https://issues.apache.org/jira/browse/HIVE-11940) has been fixed, and there is no performance issue anymore. We should leave the overwrite logic to hive to avoid failure in `FileSystem#checkPath`
**NOTE THAT** For Hive 2.2.0 and earlier, if the table and partition locations do not belong together, we will still get the same error thrown by hive encryption check due to [HIVE-14380]( https://issues.apache.org/jira/browse/HIVE-14380) which need to fix in another ticket SPARK-31675.
### Why are the changes needed?
bugfix. a logic table can be decoupled with the storage layer and may contain data from remote storage systems.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
Currently verified manually. add benchmark tests
```sql
-INSERT INTO DYNAMIC 7742 7918 248 0.0 756044.0 1.0X
-INSERT INTO HYBRID 1289 1307 26 0.0 125866.3 6.0X
-INSERT INTO STATIC 371 393 38 0.0 36219.4 20.9X
-INSERT OVERWRITE DYNAMIC 8456 8554 138 0.0 825790.3 0.9X
-INSERT OVERWRITE HYBRID 1303 1311 12 0.0 127198.4 5.9X
-INSERT OVERWRITE STATIC 434 447 13 0.0 42373.8 17.8X
+INSERT INTO DYNAMIC 7382 7456 105 0.0 720904.8 1.0X
+INSERT INTO HYBRID 1128 1129 1 0.0 110169.4 6.5X
+INSERT INTO STATIC 349 370 39 0.0 34095.4 21.1X
+INSERT OVERWRITE DYNAMIC 8149 8362 301 0.0 795821.8 0.9X
+INSERT OVERWRITE HYBRID 1317 1318 2 0.0 128616.7 5.6X
+INSERT OVERWRITE STATIC 387 408 37 0.0 37804.1 19.1X
```
+ for master
- for this PR
both using hive 2.3.7
Closes#28511 from yaooqinn/SPARK-31684.
Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
The QueryPlanningTracker in QueryExeuction reports the planning time that also includes the optimization time. This happens because the optimizedPlan in QueryExecution is lazy and only will initialize when first called. When df.queryExecution.executedPlan is called, the the tracker starts recording the planning time, and then calls the optimized plan. This causes the planning time to start before optimization and also include the planning time.
This PR fixes this behavior by introducing a method assertOptimized, similar to assertAnalyzed that explicitly initializes the optimized plan. This method is called before measuring the time for sparkPlan and executedPlan. We call it before sparkPlan because that also counts as planning time.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Unit tests
Closes#28543 from dbaliafroozeh/AddAssertOptimized.
Authored-by: Ali Afroozeh <ali.afroozeh@databricks.com>
Signed-off-by: herman <herman@databricks.com>
### What changes were proposed in this pull request?
This PR improves handling the case where different barrier sync types in a single sync:
- use `clear` instead of `cleanupBarrierStage `
- make sure all requesters are failed because of "different barrier sync types"
### Why are the changes needed?
Currently, we use `cleanupBarrierStage` to clean up a barrier stage when we detecting the case of "different barrier sync types". But this leads to a problem that we could create new a `ContextBarrierState` for the same stage again if there're on-way requests from tasks. As a result, those task will fail because of killing instead of "different barrier sync types".
Besides, we don't handle the current request which is being handling properly as it will fail due to epoch mismatch instead of "different barrier sync types".
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated a existed test.
Closes#28462 from Ngone51/impr_barrier_req.
Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Xingbo Jiang <xingbo.jiang@databricks.com>
### What changes were proposed in this pull request?
SQL Rest API exposes query execution metrics as Public API. This PR aims to apply following improvements on SQL Rest API by aligning Spark-UI.
**Proposed Improvements:**
1- Support Physical Operations and group metrics per physical operation by aligning Spark UI.
2- Support `wholeStageCodegenId` for Physical Operations
3- `nodeId` can be useful for grouping metrics and sorting physical operations (according to execution order) to differentiate same operators (if used multiple times during the same query execution) and their metrics.
4- Filter `empty` metrics by aligning with Spark UI - SQL Tab. Currently, Spark UI does not show empty metrics.
5- Remove line breakers(`\n`) from `metricValue`.
6- `planDescription` can be `optional` Http parameter to avoid network cost where there is specially complex jobs creating big-plans.
7- `metrics` attribute needs to be exposed at the bottom order as `nodes`. Specially, this can be useful for the user where `nodes` array size is high.
8- `edges` attribute is being exposed to show relationship between `nodes`.
9- Reverse order on `metricDetails` aims to match with Spark UI by supporting Physical Operators' execution order.
### Why are the changes needed?
Proposed improvements provides more useful (e.g: physical operations and metrics correlation, grouping) and clear (e.g: filtering blank metrics, removing line breakers) result for the end-user.
### Does this PR introduce any user-facing change?
Yes. Please find both current and improved versions of the results as attached for following SQL Rest Endpoint:
```
curl -X GET http://localhost:4040/api/v1/applications/$appId/sql/$executionId?details=true
```
**Current version:**
https://issues.apache.org/jira/secure/attachment/12999821/current_version.json
**Improved version:**
https://issues.apache.org/jira/secure/attachment/13000621/improved_version.json
### Backward Compatibility
SQL Rest API will be started to expose with `Spark 3.0` and `3.0.0-preview2` (released on 12/23/19) does not cover this API so if PR can catch 3.0 release, this will not have any backward compatibility issue.
### How was this patch tested?
1. New Unit tests are added.
2. Also, patch has been tested manually through both **Spark Core** and **History Server** Rest APIs.
Closes#28208 from erenavsarogullari/SPARK-31440.
Authored-by: Eren Avsarogullari <eren.avsarogullari@gmail.com>
Signed-off-by: Gengliang Wang <gengliang.wang@databricks.com>
