#2 #1

ArturLakizo · 2018-07-10T20:10:57Z

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)
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Please review http://spark.apache.org/contributing.html before opening a pull request.

… values ## What changes were proposed in this pull request? This PR adds several unit tests along the `cols NOT IN (subquery)` pathway. There are a scattering of tests here and there which cover this codepath, but there doesn't seem to be a unified unit test of the correctness of null-aware anti joins anywhere. I have also added a brief explanation of how this expression behaves in SubquerySuite. Lastly, I made some clarifying changes in the NOT IN pathway in RewritePredicateSubquery. ## How was this patch tested? Added unit tests! There should be no behavioral change in this PR. Author: Miles Yucht <[email protected]> Closes #21425 from mgyucht/spark-24381.

…shutdown of Arrow memory allocator ## What changes were proposed in this pull request? There is a race condition of closing Arrow VectorSchemaRoot and Allocator in the writer thread of ArrowPythonRunner. The race results in memory leak exception when closing the allocator. This patch removes the closing routine from the TaskCompletionListener and make the writer thread responsible for cleaning up the Arrow memory. This issue be reproduced by this test: ``` def test_memory_leak(self): from pyspark.sql.functions import pandas_udf, col, PandasUDFType, array, lit, explode # Have all data in a single executor thread so it can trigger the race condition easier with self.sql_conf({'spark.sql.shuffle.partitions': 1}): df = self.spark.range(0, 1000) df = df.withColumn('id', array([lit(i) for i in range(0, 300)])) \ .withColumn('id', explode(col('id'))) \ .withColumn('v', array([lit(i) for i in range(0, 1000)])) pandas_udf(df.schema, PandasUDFType.GROUPED_MAP) def foo(pdf): xxx return pdf result = df.groupby('id').apply(foo) with QuietTest(self.sc): with self.assertRaises(py4j.protocol.Py4JJavaError) as context: result.count() self.assertTrue('Memory leaked' not in str(context.exception)) ``` Note: Because of the race condition, the test case cannot reproduce the issue reliably so it's not added to test cases. ## How was this patch tested? Because of the race condition, the bug cannot be unit test easily. So far it has only happens on large amount of data. This is currently tested manually. Author: Li Jin <[email protected]> Closes #21397 from icexelloss/SPARK-24334-arrow-memory-leak.

…and KeyValueGroupedDataset's child ## What changes were proposed in this pull request? When we create a `RelationalGroupedDataset` or a `KeyValueGroupedDataset` we set its child to the `logicalPlan` of the `DataFrame` we need to aggregate. Since the `logicalPlan` is already analyzed, we should not analyze it again. But this happens when the new plan of the aggregate is analyzed. The current behavior in most of the cases is likely to produce no harm, but in other cases re-analyzing an analyzed plan can change it, since the analysis is not idempotent. This can cause issues like the one described in the JIRA (missing to find a cached plan). The PR adds an `AnalysisBarrier` to the `logicalPlan` which is used as child of `RelationalGroupedDataset` or a `KeyValueGroupedDataset`. ## How was this patch tested? added UT Author: Marco Gaido <[email protected]> Closes #21432 from mgaido91/SPARK-24373.

## What changes were proposed in this pull request? The pandas_udf functionality was introduced in 2.3.0, but is not completely stable and still evolving. This adds a label to indicate it is still an experimental API. ## How was this patch tested? NA Author: Bryan Cutler <[email protected]> Closes #21435 from BryanCutler/arrow-pandas_udf-experimental-SPARK-24392.

…amePrefix ## What changes were proposed in this pull request? `Random.nextString` is good for generating random string data, but it's not proper for directory name prefix in `Utils.createDirectory(tempDir, Random.nextString(10))`. This PR uses more safe directory namePrefix. ```scala scala> scala.util.Random.nextString(10) res0: String = 馨쭔ᎰႻ穚䃈兩㻞藑並 ``` ```scala StateStoreRDDSuite: - versioning and immutability - recovering from files - usage with iterators - only gets and only puts - preferred locations using StateStoreCoordinator *** FAILED *** java.io.IOException: Failed to create a temp directory (under /.../spark/sql/core/target/tmp/StateStoreRDDSuite8712796397908632676) after 10 attempts! at org.apache.spark.util.Utils$.createDirectory(Utils.scala:295) at org.apache.spark.sql.execution.streaming.state.StateStoreRDDSuite$$anonfun$13$$anonfun$apply$6.apply(StateStoreRDDSuite.scala:152) at org.apache.spark.sql.execution.streaming.state.StateStoreRDDSuite$$anonfun$13$$anonfun$apply$6.apply(StateStoreRDDSuite.scala:149) at org.apache.spark.sql.catalyst.util.package$.quietly(package.scala:42) at org.apache.spark.sql.execution.streaming.state.StateStoreRDDSuite$$anonfun$13.apply(StateStoreRDDSuite.scala:149) at org.apache.spark.sql.execution.streaming.state.StateStoreRDDSuite$$anonfun$13.apply(StateStoreRDDSuite.scala:149) ... - distributed test *** FAILED *** java.io.IOException: Failed to create a temp directory (under /.../spark/sql/core/target/tmp/StateStoreRDDSuite8712796397908632676) after 10 attempts! at org.apache.spark.util.Utils$.createDirectory(Utils.scala:295) ``` ## How was this patch tested? Pass the existing tests.StateStoreRDDSuite: Author: Dongjoon Hyun <[email protected]> Closes #21446 from dongjoon-hyun/SPARK-19613.

…cation ## What changes were proposed in this pull request? For some Spark applications, though they're a java program, they require not only jar dependencies, but also python dependencies. One example is Livy remote SparkContext application, this application is actually an embedded REPL for Scala/Python/R, it will not only load in jar dependencies, but also python and R deps, so we should specify not only "--jars", but also "--py-files". Currently for a Spark application, --py-files can only be worked for a pyspark application, so it will not be worked in the above case. So here propose to remove such restriction. Also we tested that "spark.submit.pyFiles" only supports quite limited scenario (client mode with local deps), so here also expand the usage of "spark.submit.pyFiles" to be alternative of --py-files. ## How was this patch tested? UT added. Author: jerryshao <[email protected]> Closes #21420 from jerryshao/SPARK-24377.

## What changes were proposed in this pull request? We should not stop users from calling `getActiveSession` and `getDefaultSession` in executors. To not break the existing behaviors, we should simply return None. ## How was this patch tested? N/A Author: Xiao Li <[email protected]> Closes #21436 from gatorsmile/followUpSPARK-24250.

…eBlocksToBatch When blocks tried to get allocated to a batch and WAL write fails then the blocks will be removed from the received block queue. This fact simply produces data loss because the next allocation will not find the mentioned blocks in the queue. In this PR blocks will be removed from the received queue only if WAL write succeded. Additional unit test. Author: Gabor Somogyi <[email protected]> Closes #21430 from gaborgsomogyi/SPARK-23991. Change-Id: I5ead84f0233f0c95e6d9f2854ac2ff6906f6b341

## What changes were proposed in this pull request? Add Data Source write benchmark. So that it would be easier to measure the writer performance. Author: Gengliang Wang <[email protected]> Closes #21409 from gengliangwang/parquetWriteBenchmark.

…ntries to SparkR ## What changes were proposed in this pull request? The PR adds functions `arrays_overlap`, `array_repeat`, `map_entries` to SparkR. ## How was this patch tested? Tests added into R/pkg/tests/fulltests/test_sparkSQL.R ## Examples ### arrays_overlap ``` df <- createDataFrame(list(list(list(1L, 2L), list(3L, 1L)), list(list(1L, 2L), list(3L, 4L)), list(list(1L, NA), list(3L, 4L)))) collect(select(df, arrays_overlap(df[[1]], df[[2]]))) ``` ``` arrays_overlap(_1, _2) 1 TRUE 2 FALSE 3 NA ``` ### array_repeat ``` df <- createDataFrame(list(list("a", 3L), list("b", 2L))) collect(select(df, array_repeat(df[[1]], df[[2]]))) ``` ``` array_repeat(_1, _2) 1 a, a, a 2 b, b ``` ``` collect(select(df, array_repeat(df[[1]], 2L))) ``` ``` array_repeat(_1, 2) 1 a, a 2 b, b ``` ### map_entries ``` df <- createDataFrame(list(list(map = as.environment(list(x = 1, y = 2))))) collect(select(df, map_entries(df$map))) ``` ``` map_entries(map) 1 x, 1, y, 2 ``` Author: Marek Novotny <[email protected]> Closes #21434 from mn-mikke/SPARK-24331.

## What changes were proposed in this pull request? Make sure that `StopIteration`s raised in users' code do not silently interrupt processing by spark, but are raised as exceptions to the users. The users' functions are wrapped in `safe_iter` (in `shuffle.py`), which re-raises `StopIteration`s as `RuntimeError`s ## How was this patch tested? Unit tests, making sure that the exceptions are indeed raised. I am not sure how to check whether a `Py4JJavaError` contains my exception, so I simply looked for the exception message in the java exception's `toString`. Can you propose a better way? ## License This is my original work, licensed in the same way as spark Author: e-dorigatti <[email protected]> Author: edorigatti <[email protected]> Closes #21383 from e-dorigatti/fix_spark_23754.

## What changes were proposed in this pull request? Upgrade SBT to 0.13.17 with Scala 2.10.7 for JDK9+ ## How was this patch tested? Existing tests Author: DB Tsai <[email protected]> Closes #21458 from dbtsai/sbt.

…s having the same argument set ## What changes were proposed in this pull request? This pr fixed an issue when having multiple distinct aggregations having the same argument set, e.g., ``` scala>: paste val df = sql( s"""SELECT corr(DISTINCT x, y), corr(DISTINCT y, x), count(*) | FROM (VALUES (1, 1), (2, 2), (2, 2)) t(x, y) """.stripMargin) java.lang.RuntimeException You hit a query analyzer bug. Please report your query to Spark user mailing list. ``` The root cause is that `RewriteDistinctAggregates` can't detect multiple distinct aggregations if they have the same argument set. This pr modified code so that `RewriteDistinctAggregates` could count the number of aggregate expressions with `isDistinct=true`. ## How was this patch tested? Added tests in `DataFrameAggregateSuite`. Author: Takeshi Yamamuro <[email protected]> Closes #21443 from maropu/SPARK-24369.

…onRunner in submit with client mode in spark-submit ## What changes were proposed in this pull request? In client side before context initialization specifically, .py file doesn't work in client side before context initialization when the application is a Python file. See below: ``` $ cat /home/spark/tmp.py def testtest(): return 1 ``` This works: ``` $ cat app.py import pyspark pyspark.sql.SparkSession.builder.getOrCreate() import tmp print("************************%s" % tmp.testtest()) $ ./bin/spark-submit --master yarn --deploy-mode client --py-files /home/spark/tmp.py app.py ... ************************1 ``` but this doesn't: ``` $ cat app.py import pyspark import tmp pyspark.sql.SparkSession.builder.getOrCreate() print("************************%s" % tmp.testtest()) $ ./bin/spark-submit --master yarn --deploy-mode client --py-files /home/spark/tmp.py app.py Traceback (most recent call last): File "/home/spark/spark/app.py", line 2, in <module> import tmp ImportError: No module named tmp ``` ### How did it happen? In client mode specifically, the paths are being added into PythonRunner as are: https://github.com/apache/spark/blob/628c7b517969c4a7ccb26ea67ab3dd61266073ca/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L430 https://github.com/apache/spark/blob/628c7b517969c4a7ccb26ea67ab3dd61266073ca/core/src/main/scala/org/apache/spark/deploy/PythonRunner.scala#L49-L88 The problem here is, .py file shouldn't be added as are since `PYTHONPATH` expects a directory or an archive like zip or egg. ### How does this PR fix? We shouldn't simply just add its parent directory because other files in the parent directory could also be added into the `PYTHONPATH` in client mode before context initialization. Therefore, we copy .py files into a temp directory for .py files and add it to `PYTHONPATH`. ## How was this patch tested? Unit tests are added and manually tested in both standalond and yarn client modes with submit. Author: hyukjinkwon <[email protected]> Closes #21426 from HyukjinKwon/SPARK-24384.

## What changes were proposed in this pull request? Add featureSubsetStrategy in GBTClassifier and GBTRegressor. Also make GBTClassificationModel inherit from JavaClassificationModel instead of prediction model so it will have numClasses. ## How was this patch tested? Add tests in doctest Author: Huaxin Gao <[email protected]> Closes #21413 from huaxingao/spark-23161.

## What changes were proposed in this pull request? The PR adds the masking function as they are described in Hive's documentation: https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-DataMaskingFunctions. This means that only `string`s are accepted as parameter for the masking functions. ## How was this patch tested? added UTs Author: Marco Gaido <[email protected]> Closes #21246 from mgaido91/SPARK-23901.

… equality ## What changes were proposed in this pull request? When two `In` operators are created with the same list of values, but different order, we are considering them as semantically different. This is wrong, since they have the same semantic meaning. The PR adds a canonicalization rule which orders the literals in the `In` operator so the semantic equality works properly. ## How was this patch tested? added UT Author: Marco Gaido <[email protected]> Closes #21331 from mgaido91/SPARK-24276.

## What changes were proposed in this pull request? Improve the exception messages when retrieving Spark conf values to include the key name when the value is invalid. ## How was this patch tested? Unit tests for all get* operations in SparkConf that require a specific value format Author: William Sheu <[email protected]> Closes #21454 from PenguinToast/SPARK-24337-spark-config-errors.

…ing - PrefixSpan: Python API ## What changes were proposed in this pull request? spark.ml parity for sequential pattern mining - PrefixSpan: Python API ## How was this patch tested? doctests Author: WeichenXu <[email protected]> Closes #21265 from WeichenXu123/prefix_span_py.

As discussed separately, this avoids the possibility of XSS on certain request param keys. CC vanzin Author: Sean Owen <[email protected]> Closes #21464 from srowen/XSS2.

This change takes into account all non-pending tasks when calculating the number of tasks to be shown. This also means that when the stage is pending, the task table (or, in fact, most of the data in the stage page) will not be rendered. I also fixed the label when the known number of tasks is larger than the recorded number of tasks (it was inverted). Author: Marcelo Vanzin <[email protected]> Closes #21457 from vanzin/SPARK-24414.

## What changes were proposed in this pull request? This adds a new API `TaskContext.getLocalProperty(key)` to the Python TaskContext. It mirrors the Java TaskContext API of returning a string value if the key exists, or None if the key does not exist. ## How was this patch tested? New test added. Author: Tathagata Das <[email protected]> Closes #21437 from tdas/SPARK-24397.

…ment ## What changes were proposed in this pull request? `format_number` support user specifed format as argument. For example: ```sql spark-sql> SELECT format_number(12332.123456, '##################.###'); 12332.123 ``` ## How was this patch tested? unit test Author: Yuming Wang <[email protected]> Closes #21010 from wangyum/SPARK-23900.

## What changes were proposed in this pull request? * Allows to refer a secret as an env var. * Introduces new config properties in the form: spark.kubernetes{driver,executor}.secretKeyRef.ENV_NAME=name:key ENV_NAME is case sensitive. * Updates docs. * Adds required unit tests. ## How was this patch tested? Manually tested and confirmed that the secrets exist in driver's and executor's container env. Also job finished successfully. First created a secret with the following yaml: ``` apiVersion: v1 kind: Secret metadata: name: test-secret data: username: c3RhdnJvcwo= password: Mzk1MjgkdmRnN0pi ------- $ echo -n 'stavros' | base64 c3RhdnJvcw== $ echo -n '39528$vdg7Jb' | base64 MWYyZDFlMmU2N2Rm ``` Run a job as follows: ```./bin/spark-submit \ --master k8s://http://localhost:9000 \ --deploy-mode cluster \ --name spark-pi \ --class org.apache.spark.examples.SparkPi \ --conf spark.executor.instances=1 \ --conf spark.kubernetes.container.image=skonto/spark:k8envs3 \ --conf spark.kubernetes.driver.secretKeyRef.MY_USERNAME=test-secret:username \ --conf spark.kubernetes.driver.secretKeyRef.My_password=test-secret:password \ --conf spark.kubernetes.executor.secretKeyRef.MY_USERNAME=test-secret:username \ --conf spark.kubernetes.executor.secretKeyRef.My_password=test-secret:password \ local:///opt/spark/examples/jars/spark-examples_2.11-2.4.0-SNAPSHOT.jar 10000 ``` Secret loaded correctly at the driver container: ![image](https://user-images.githubusercontent.com/7945591/40174346-7fee70c8-59dd-11e8-8705-995a5472716f.png) Also if I log into the exec container: kubectl exec -it spark-pi-1526555613156-exec-1 bash bash-4.4# env > SPARK_EXECUTOR_MEMORY=1g > SPARK_EXECUTOR_CORES=1 > LANG=C.UTF-8 > HOSTNAME=spark-pi-1526555613156-exec-1 > SPARK_APPLICATION_ID=spark-application-1526555618626 > **MY_USERNAME=stavros** > > JAVA_HOME=/usr/lib/jvm/java-1.8-openjdk > KUBERNETES_PORT_443_TCP_PROTO=tcp > KUBERNETES_PORT_443_TCP_ADDR=10.100.0.1 > JAVA_VERSION=8u151 > KUBERNETES_PORT=tcp://10.100.0.1:443 > PWD=/opt/spark/work-dir > HOME=/root > SPARK_LOCAL_DIRS=/var/data/spark-b569b0ae-b7ef-4f91-bcd5-0f55535d3564 > KUBERNETES_SERVICE_PORT_HTTPS=443 > KUBERNETES_PORT_443_TCP_PORT=443 > SPARK_HOME=/opt/spark > SPARK_DRIVER_URL=spark://CoarseGrainedSchedulerspark-pi-1526555613156-driver-svc.default.svc:7078 > KUBERNETES_PORT_443_TCP=tcp://10.100.0.1:443 > SPARK_EXECUTOR_POD_IP=9.0.9.77 > TERM=xterm > SPARK_EXECUTOR_ID=1 > SHLVL=1 > KUBERNETES_SERVICE_PORT=443 > SPARK_CONF_DIR=/opt/spark/conf > PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/lib/jvm/java-1.8-openjdk/jre/bin:/usr/lib/jvm/java-1.8-openjdk/bin > JAVA_ALPINE_VERSION=8.151.12-r0 > KUBERNETES_SERVICE_HOST=10.100.0.1 > **My_password=39528$vdg7Jb** > _=/usr/bin/env > Author: Stavros Kontopoulos <[email protected]> Closes #21317 from skonto/k8s-fix-env-secrets.

… message This PR adds a debugging log for YARN-specific credential providers which is loaded by service loader mechanism. It took me a while to debug if it's actually loaded or not. I had to explicitly set the deprecated configuration and check if that's actually being loaded. The change scope is manually tested. Logs are like: ``` Using the following builtin delegation token providers: hadoopfs, hive, hbase. Using the following YARN-specific credential providers: yarn-test. ``` Author: hyukjinkwon <[email protected]> Closes #21466 from HyukjinKwon/minor-log. Change-Id: I18e2fb8eeb3289b148f24c47bb3130a560a881cf

…ng files ## What changes were proposed in this pull request? 1. Refactor ExecuteWriteTask in FileFormatWriter to reduce common logic and improve readability. After the change, callers only need to call `commit()` or `abort` at the end of task. Also there is less code in `SingleDirectoryWriteTask` and `DynamicPartitionWriteTask`. Definitions of related classes are moved to a new file, and `ExecuteWriteTask` is renamed to `FileFormatDataWriter`. 2. As per code style guide: https://github.com/databricks/scala-style-guide#traversal-and-zipwithindex , we avoid using `for` for looping in [FileFormatWriter](https://github.com/apache/spark/pull/21381/files#diff-3b69eb0963b68c65cfe8075f8a42e850L536) , or `foreach` in [WriteToDataSourceV2Exec](https://github.com/apache/spark/pull/21381/files#diff-6fbe10db766049a395bae2e785e9d56eL119). In such critical code path, using `while` is good for performance. ## How was this patch tested? Existing unit test. I tried the microbenchmark in #21409 | Workload | Before changes(Best/Avg Time(ms)) | After changes(Best/Avg Time(ms)) | | --- | --- | -- | |Output Single Int Column| 2018 / 2043 | 2096 / 2236 | |Output Single Double Column| 1978 / 2043 | 2013 / 2018 | |Output Int and String Column| 6332 / 6706 | 6162 / 6298 | |Output Partitions| 4458 / 5094 | 3792 / 4008 | |Output Buckets| 5695 / 6102 | 5120 / 5154 | Also a microbenchmark on my laptop for general comparison among while/foreach/for : ``` class Writer { var sum = 0L def write(l: Long): Unit = sum += l } def testWhile(iterator: Iterator[Long]): Long = { val w = new Writer while (iterator.hasNext) { w.write(iterator.next()) } w.sum } def testForeach(iterator: Iterator[Long]): Long = { val w = new Writer iterator.foreach(w.write) w.sum } def testFor(iterator: Iterator[Long]): Long = { val w = new Writer for (x <- iterator) { w.write(x) } w.sum } val data = 0L to 100000000L val start = System.nanoTime (0 to 10).foreach(_ => testWhile(data.iterator)) println("benchmark while: " + (System.nanoTime - start)/1000000) val start2 = System.nanoTime (0 to 10).foreach(_ => testForeach(data.iterator)) println("benchmark foreach: " + (System.nanoTime - start2)/1000000) val start3 = System.nanoTime (0 to 10).foreach(_ => testForeach(data.iterator)) println("benchmark for: " + (System.nanoTime - start3)/1000000) ``` Benchmark result: `while`: 15401 ms `foreach`: 43034 ms `for`: 41279 ms Author: Gengliang Wang <[email protected]> Closes #21381 from gengliangwang/refactorExecuteWriteTask.

… assignment ## What changes were proposed in this pull request? Added sections to pandas_udf docs, in the grouped map section, to indicate columns are assigned by position. ## How was this patch tested? NA Author: Bryan Cutler <[email protected]> Closes #21471 from BryanCutler/arrow-doc-pandas_udf-column_by_pos-SPARK-21427.

## What changes were proposed in this pull request? * Adds support for local:// scheme like in k8s case for image based deployments where the jar is already in the image. Affects cluster mode and the mesos dispatcher. Covers also file:// scheme. Keeps the default case where jar resolution happens on the host. ## How was this patch tested? Dispatcher image with the patch, use it to start DC/OS Spark service: skonto/spark-local-disp:test Test image with my application jar located at the root folder: skonto/spark-local:test Dockerfile for that image. From mesosphere/spark:2.3.0-2.2.1-2-hadoop-2.6 COPY spark-examples_2.11-2.2.1.jar / WORKDIR /opt/spark/dist Tests: The following work as expected: * local normal example ``` dcos spark run --submit-args="--conf spark.mesos.appJar.local.resolution.mode=container --conf spark.executor.memory=1g --conf spark.mesos.executor.docker.image=skonto/spark-local:test --conf spark.executor.cores=2 --conf spark.cores.max=8 --class org.apache.spark.examples.SparkPi local:///spark-examples_2.11-2.2.1.jar" ``` * make sure the flag does not affect other uris ``` dcos spark run --submit-args="--conf spark.mesos.appJar.local.resolution.mode=container --conf spark.executor.memory=1g --conf spark.executor.cores=2 --conf spark.cores.max=8 --class org.apache.spark.examples.SparkPi https://s3-eu-west-1.amazonaws.com/fdp-stavros-test/spark-examples_2.11-2.1.1.jar" ``` * normal example no local ``` dcos spark run --submit-args="--conf spark.executor.memory=1g --conf spark.executor.cores=2 --conf spark.cores.max=8 --class org.apache.spark.examples.SparkPi https://s3-eu-west-1.amazonaws.com/fdp-stavros-test/spark-examples_2.11-2.1.1.jar" ``` The following fails * uses local with no setting, default is host. ``` dcos spark run --submit-args="--conf spark.executor.memory=1g --conf spark.mesos.executor.docker.image=skonto/spark-local:test --conf spark.executor.cores=2 --conf spark.cores.max=8 --class org.apache.spark.examples.SparkPi local:///spark-examples_2.11-2.2.1.jar" ``` ![image](https://user-images.githubusercontent.com/7945591/40283021-8d349762-5c80-11e8-9d62-2a61a4318fd5.png) Author: Stavros Kontopoulos <[email protected]> Closes #21378 from skonto/local-upstream.

… element from array ## What changes were proposed in this pull request? add array_remove to remove all elements that equal element from array ## How was this patch tested? add unit tests Author: Huaxin Gao <[email protected]> Closes #21069 from huaxingao/spark-23920.

…ivariate summary ## What changes were proposed in this pull request? Add user guide and scala/java/python examples for `ml.stat.Summarizer` ## How was this patch tested? Doc generated snapshot: ![image](https://user-images.githubusercontent.com/19235986/38987108-45646044-4401-11e8-9ba8-ae94ba96cbf9.png) ![image](https://user-images.githubusercontent.com/19235986/38987096-36dcc73c-4401-11e8-87f9-5b91e7f9e27b.png) ![image](https://user-images.githubusercontent.com/19235986/38987088-2d1c1eaa-4401-11e8-80b5-8c40d529a120.png) ![image](https://user-images.githubusercontent.com/19235986/38987077-22ce8be0-4401-11e8-8199-c3a4d8d23201.png) Author: WeichenXu <[email protected]> Closes #20446 from WeichenXu123/summ_guide.

…rogress ## What changes were proposed in this pull request? In ProgressReporter for streams, we use the `committedOffsets` as the startOffset and `availableOffsets` as the end offset when reporting the status of a trigger in `finishTrigger`. This is a bad pattern that has existed since the beginning of ProgressReporter and it is bad because its super hard to reason about when `availableOffsets` and `committedOffsets` are updated, and when they are recorded. Case in point, this bug silently existed in ContinuousExecution, since before MicroBatchExecution was refactored. The correct fix it to record the offsets explicitly. This PR adds a simple method which is explicitly called from MicroBatch/ContinuousExecition before updating the `committedOffsets`. ## How was this patch tested? Added new tests Author: Tathagata Das <[email protected]> Closes #21744 from tdas/SPARK-24697.

## What changes were proposed in this pull request? The PR simplifies the retrieval of config in `size`, as we can access them from tasks too thanks to SPARK-24250. ## How was this patch tested? existing UTs Author: Marco Gaido <[email protected]> Closes #21736 from mgaido91/SPARK-24605_followup.

## What changes were proposed in this pull request? In the PR, I propose to extend `RuntimeConfig` by new method `isModifiable()` which returns `true` if a config parameter can be modified at runtime (for current session state). For static SQL and core parameters, the method returns `false`. ## How was this patch tested? Added new test to `RuntimeConfigSuite` for checking Spark core and SQL parameters. Author: Maxim Gekk <[email protected]> Closes #21730 from MaxGekk/is-modifiable.

## What changes were proposed in this pull request? This PR enables a Java bytecode check tool [spotbugs](https://spotbugs.github.io/) to avoid possible integer overflow at multiplication. When an violation is detected, the build process is stopped. Due to the tool limitation, some other checks will be enabled. In this PR, [these patterns](http://spotbugs-in-kengo-toda.readthedocs.io/en/lqc-list-detectors/detectors.html#findpuzzlers) in `FindPuzzlers` can be detected. This check is enabled at `compile` phase. Thus, `mvn compile` or `mvn package` launches this check. ## How was this patch tested? Existing UTs Author: Kazuaki Ishizaki <[email protected]> Closes #21542 from kiszk/SPARK-24529.

## What changes were proposed in this pull request? The PR adds the SQL function `array_union`. The behavior of the function is based on Presto's one. This function returns returns an array of the elements in the union of array1 and array2. Note: The order of elements in the result is not defined. ## How was this patch tested? Added UTs Author: Kazuaki Ishizaki <[email protected]> Closes #21061 from kiszk/SPARK-23914.

…ementation ## What changes were proposed in this pull request? With #21389, data source schema is validated on driver side before launching read/write tasks. However, 1. Putting all the validations together in `DataSourceUtils` is tricky and hard to maintain. On second thought after review, I find that the `OrcFileFormat` in hive package is not matched, so that its validation wrong. 2. `DataSourceUtils.verifyWriteSchema` and `DataSourceUtils.verifyReadSchema` is not supposed to be called in every file format. We can move them to some upper entry. So, I propose we can add a new method `validateDataType` in FileFormat. File format implementation can override the method to specify its supported/non-supported data types. Although we should focus on data source V2 API, `FileFormat` should remain workable for some time. Adding this new method should be helpful. ## How was this patch tested? Unit test Author: Gengliang Wang <[email protected]> Closes #21667 from gengliangwang/refactorSchemaValidate.

… cause exception on … 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 <[email protected]> Closes #21541 from yashs360/ysharma/fix_kinesis_bug.

## What changes were proposed in this pull request? The `WholeTextFileInputFormat` determines the `maxSplitSize` for the file/s being read using the `wholeTextFiles` method. While this works well for large files, for smaller files where the maxSplitSize is smaller than the defaults being used with configs like hive-site.xml or explicitly passed in the form of `mapreduce.input.fileinputformat.split.minsize.per.node` or `mapreduce.input.fileinputformat.split.minsize.per.rack` , it just throws up an exception. ```java java.io.IOException: Minimum split size pernode 123456 cannot be larger than maximum split size 9962 at org.apache.hadoop.mapreduce.lib.input.CombineFileInputFormat.getSplits(CombineFileInputFormat.java:200) at org.apache.spark.rdd.WholeTextFileRDD.getPartitions(WholeTextFileRDD.scala:50) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.rdd.RDD.partitions(RDD.scala:250) at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.rdd.RDD.partitions(RDD.scala:250) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2096) at org.apache.spark.rdd.RDD.count(RDD.scala:1158) ... 48 elided ` This change checks the maxSplitSize against the minSplitSizePerNode and minSplitSizePerRack and set them if `maxSplitSize < minSplitSizePerNode/Rack` ## How was this patch tested? Test manually setting the conf while launching the job and added unit test. Author: Dhruve Ashar <[email protected]> Closes #21601 from dhruve/bug/SPARK-24610.

## 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 <[email protected]> Closes #21742 from gengliangwang/export_avro.

…urces ## What changes were proposed in this pull request? The reader schema is said to be evolved (or projected) when it changed after the data is written. The followings are already supported in file-based data sources. Note that partition columns are not maintained in files. In this PR, `column` means `non-partition column`. 1. Add a column 2. Hide a column 3. Change a column position 4. Change a column type (upcast) This issue aims to guarantee users a backward-compatible read-schema test coverage on file-based data sources and to prevent future regressions by *adding read schema tests explicitly*. Here, we consider safe changes without data loss. For example, data type change should be from small types to larger types like `int`-to-`long`, not vice versa. As of today, in the master branch, file-based data sources have the following coverage. File Format | Coverage | Note ----------- | ---------- | ------------------------------------------------ TEXT | N/A | Schema consists of a single string column. CSV | 1, 2, 4 | JSON | 1, 2, 3, 4 | ORC | 1, 2, 3, 4 | Native vectorized ORC reader has the widest coverage among ORC formats. PARQUET | 1, 2, 3 | ## How was this patch tested? Pass the Jenkins with newly added test suites. Author: Dongjoon Hyun <[email protected]> Closes #20208 from dongjoon-hyun/SPARK-SCHEMA-EVOLUTION.

## What changes were proposed in this pull request? The PR is a followup to move the test cases introduced by the original PR in their proper location. ## How was this patch tested? moved UTs Author: Marco Gaido <[email protected]> Closes #21751 from mgaido91/SPARK-24208_followup.

## What changes were proposed in this pull request? Relax the check to allow complex aggregate expressions, like `ceil(sum(col1))` or `sum(col1) + 1`, which roughly means any aggregate expression that could appear in an Aggregate plan except pandas UDF (due to the fact that it is not supported in pivot yet). ## How was this patch tested? Added 2 tests in pivot.sql Author: maryannxue <[email protected]> Closes #21753 from maryannxue/pivot-relax-syntax.

…ay_distinct ## What changes were proposed in this pull request? Add array_remove / array_zip / map_from_arrays / array_distinct functions in SparkR. ## How was this patch tested? Add tests in test_sparkSQL.R Author: Huaxin Gao <[email protected]> Closes #21645 from huaxingao/spark-24537.

…ookupFunctions ## What changes were proposed in this pull request? This PR will cache the function name from external catalog, it is used by lookupFunctions in the analyzer, and it is cached for each query plan. The original problem is reported in the [ spark-19737](https://issues.apache.org/jira/browse/SPARK-19737) ## How was this patch tested? create new test file LookupFunctionsSuite and add test case in SessionCatalogSuite Author: Kevin Yu <[email protected]> Closes #20795 from kevinyu98/spark-23486.

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 <[email protected]> Author: yuanbo <[email protected]> Closes #21690 from yuanboliu/master.

…t not work ## What changes were proposed in this pull request? When we use a reference from Dataset in filter or sort, which was not used in the prior select, an AnalysisException occurs, e.g., ```scala val df = Seq(("test1", 0), ("test2", 1)).toDF("name", "id") df.select(df("name")).filter(df("id") === 0).show() ``` ```scala org.apache.spark.sql.AnalysisException: Resolved attribute(s) id#6 missing from name#5 in operator !Filter (id#6 = 0).;; !Filter (id#6 = 0) +- AnalysisBarrier +- Project [name#5] +- Project [_1#2 AS name#5, _2#3 AS id#6] +- LocalRelation [_1#2, _2#3] ``` This change updates the rule `ResolveMissingReferences` so `Filter` and `Sort` with non-empty `missingInputs` will also be transformed. ## How was this patch tested? Added tests. Author: Liang-Chi Hsieh <[email protected]> Closes #21745 from viirya/SPARK-24781.

…cated methods ## 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 <[email protected]> Closes #21760 from gengliangwang/improve_avro_test.

…ce deprecated methods" This reverts commit c1b62e4.

## What changes were proposed in this pull request? Added the number of iterations in `ClusteringSummary`. This is an helpful information in evaluating how to eventually modify the parameters in order to get a better model. ## How was this patch tested? modified existing UTs Author: Marco Gaido <[email protected]> Closes #20701 from mgaido91/SPARK-23528.

## What changes were proposed in this pull request? Add `org.apache.derby` to `IsolatedClientLoader`, otherwise it may throw an exception: ```scala ... [info] Cause: java.sql.SQLException: Failed to start database 'metastore_db' with class loader org.apache.spark.sql.hive.client.IsolatedClientLoader$$anon$12439ab23, see the next exception for details. [info] at org.apache.derby.impl.jdbc.SQLExceptionFactory.getSQLException(Unknown Source) [info] at org.apache.derby.impl.jdbc.SQLExceptionFactory.getSQLException(Unknown Source) [info] at org.apache.derby.impl.jdbc.Util.seeNextException(Unknown Source) [info] at org.apache.derby.impl.jdbc.EmbedConnection.bootDatabase(Unknown Source) [info] at org.apache.derby.impl.jdbc.EmbedConnection.<init>(Unknown Source) [info] at org.apache.derby.jdbc.InternalDriver$1.run(Unknown Source) ... ``` ## How was this patch tested? unit tests and manual tests Author: Yuming Wang <[email protected]> Closes #20944 from wangyum/SPARK-23831.

…netes ## What changes were proposed in this pull request? I added integration tests for PySpark ( + checking JVM options + RemoteFileTest) which wasn't properly merged in the initial integration test PR. ## How was this patch tested? I tested this with integration tests using: `dev/dev-run-integration-tests.sh --spark-tgz spark-2.4.0-SNAPSHOT-bin-2.7.3.tgz` Author: Ilan Filonenko <[email protected]> Closes #21583 from ifilonenko/master.

…quet filter ## What changes were proposed in this pull request? The original pr is: #18424 Add a new optimizer rule to convert an IN predicate to an equivalent Parquet filter and add `spark.sql.parquet.pushdown.inFilterThreshold` to control limit thresholds. Different data types have different limit thresholds, this is a copy of data for reference: Type | limit threshold -- | -- string | 370 int | 210 long | 285 double | 270 float | 220 decimal | Won't provide better performance before [SPARK-24549](https://issues.apache.org/jira/browse/SPARK-24549) ## How was this patch tested? unit tests and manual tests Author: Yuming Wang <[email protected]> Closes #21603 from wangyum/SPARK-17091.

## What changes were proposed in this pull request? Use longs in calculating min hash to avoid bias due to int overflow. ## How was this patch tested? Existing tests. Author: Sean Owen <[email protected]> Closes #21750 from srowen/SPARK-24754.

## What changes were proposed in this pull request? `Timestamp` support pushdown to parquet data source. Only `TIMESTAMP_MICROS` and `TIMESTAMP_MILLIS` support push down. ## How was this patch tested? unit tests and benchmark tests Author: Yuming Wang <[email protected]> Closes #21741 from wangyum/SPARK-24718.

…cated methods ## 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 <[email protected]> Closes #21768 from gengliangwang/improve_avro_test.

… a note ## What changes were proposed in this pull request? In the PR, I propose to output an warning if the `addFile()` or `addJar()` methods are callled more than once for the same path. Currently, overwriting of already added files is not supported. New comments and warning are reflected the existing behaviour. Author: Maxim Gekk <[email protected]> Closes #21771 from MaxGekk/warning-on-adding-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 <[email protected]> Closes #21762 from gengliangwang/avro_io.

Fixing the doc as the imputer is not a `Transformer` but an `Estimator`. https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala#L96-L97 ## What changes were proposed in this pull request? Simple documentation fix ## How was this patch tested? manual testing Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Zoltan C. Toth <[email protected]> Closes #21755 from zoltanctoth/doc-imputer-is-estimator.

mgyucht and others added 30 commits May 26, 2018 20:42

[SPARK-24419][BUILD] Upgrade SBT to 0.13.17 with Scala 2.10.7 for JDK9+

9e7bad0

## What changes were proposed in this pull request? Upgrade SBT to 0.13.17 with Scala 2.10.7 for JDK9+ ## How was this patch tested? Existing tests Author: DB Tsai <[email protected]> Closes #21458 from dbtsai/sbt.

[WEBUI] Avoid possibility of script in query param keys

698b9a0

As discussed separately, this avoids the possibility of XSS on certain request param keys. CC vanzin Author: Sean Owen <[email protected]> Closes #21464 from srowen/XSS2.

WeichenXu123 and others added 29 commits July 11, 2018 13:56

Revert "[SPARK-24776][SQL] Avro unit test: use SQLTestUtils and repla…

3bcb1b4

…ce deprecated methods" This reverts commit c1b62e4.

[SPARK-24754][ML] Minhash integer overflow

8aceb96

## What changes were proposed in this pull request? Use longs in calculating min hash to avoid bias due to int overflow. ## How was this patch tested? Existing tests. Author: Sean Owen <[email protected]> Closes #21750 from srowen/SPARK-24754.

ArturLakizo merged commit 0649e1e into ArturLakizo:master Jul 15, 2018

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