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* [SPARK-19240][SQL][TEST] add test for setting location for managed tableWenchen Fan2017-01-171-0/+28
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? SET LOCATION can also work on managed table(or table created without custom path), the behavior is a little weird, but as we have already supported it, we should add a test to explicitly show the behavior. ## How was this patch tested? N/A Author: Wenchen Fan <wenchen@databricks.com> Closes #16597 from cloud-fan/set-location.
* [MINOR][YARN] Move YarnSchedulerBackendSuite to resource-managers/yarn ↵Yanbo Liang2017-01-171-0/+0
| | | | | | | | | | | | | | directory. ## What changes were proposed in this pull request? #16092 moves YARN resource manager related code to resource-managers/yarn directory. The test case ```YarnSchedulerBackendSuite``` was added after that but with the wrong place. I move it to correct directory in this PR. ## How was this patch tested? Existing test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #16595 from yanboliang/yarn.
* [SPARK-19148][SQL] do not expose the external table concept in CatalogWenchen Fan2017-01-176-103/+211
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In https://github.com/apache/spark/pull/16296 , we reached a consensus that we should hide the external/managed table concept to users and only expose custom table path. This PR renames `Catalog.createExternalTable` to `createTable`(still keep the old versions for backward compatibility), and only set the table type to EXTERNAL if `path` is specified in options. ## How was this patch tested? new tests in `CatalogSuite` Author: Wenchen Fan <wenchen@databricks.com> Closes #16528 from cloud-fan/create-table.
* [SPARK-18905][STREAMING] Fix the issue of removing a failed jobset from ↵CodingCat2017-01-161-6/+8
| | | | | | | | | | | | | | | | | | | | | | | | | JobScheduler.jobSets ## What changes were proposed in this pull request? the current implementation of Spark streaming considers a batch is completed no matter the results of the jobs (https://github.com/apache/spark/blob/1169db44bc1d51e68feb6ba2552520b2d660c2c0/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala#L203) Let's consider the following case: A micro batch contains 2 jobs and they read from two different kafka topics respectively. One of these jobs is failed due to some problem in the user defined logic, after the other one is finished successfully. 1. The main thread in the Spark streaming application will execute the line mentioned above, 2. and another thread (checkpoint writer) will make a checkpoint file immediately after this line is executed. 3. Then due to the current error handling mechanism in Spark Streaming, StreamingContext will be closed (https://github.com/apache/spark/blob/1169db44bc1d51e68feb6ba2552520b2d660c2c0/streaming/src/main/scala/org/apache/spark/streaming/scheduler/JobScheduler.scala#L214) the user recovers from the checkpoint file, and because the JobSet containing the failed job has been removed (taken as completed) before the checkpoint is constructed, the data being processed by the failed job would never be reprocessed This PR fix it by removing jobset from JobScheduler.jobSets only when all jobs in a jobset are successfully finished ## How was this patch tested? existing tests Author: CodingCat <zhunansjtu@gmail.com> Author: Nan Zhu <zhunansjtu@gmail.com> Closes #16542 from CodingCat/SPARK-18905.
* [SPARK-18828][SPARKR] Refactor scripts for RFelix Cheung2017-01-167-52/+146
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Refactored script to remove duplications and clearer purpose for each script ## How was this patch tested? manually Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16249 from felixcheung/rscripts.
* [SPARK-19232][SPARKR] Update Spark distribution download cache location on ↵Felix Cheung2017-01-161-2/+2
| | | | | | | | | | | | | | | | | Windows ## What changes were proposed in this pull request? Windows seems to be the only place with appauthor in the path, for which we should say "Apache" (and case sensitive) Current path of `AppData\Local\spark\spark\Cache` is a bit odd. ## How was this patch tested? manual. Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16590 from felixcheung/rcachedir.
* [SPARK-19066][SPARKR] SparkR LDA doesn't set optimizer correctlywm624@hotmail.com2017-01-164-5/+42
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? spark.lda passes the optimizer "em" or "online" as a string to the backend. However, LDAWrapper doesn't set optimizer based on the value from R. Therefore, for optimizer "em", the `isDistributed` field is FALSE, which should be TRUE based on scala code. In addition, the `summary` method should bring back the results related to `DistributedLDAModel`. ## How was this patch tested? Manual tests by comparing with scala example. Modified the current unit test: fix the incorrect unit test and add necessary tests for `summary` method. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16464 from wangmiao1981/new.
* [SPARK-18801][SQL][FOLLOWUP] Alias the view with its childjiangxingbo2017-01-165-57/+214
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR is a follow-up to address the comments https://github.com/apache/spark/pull/16233/files#r95669988 and https://github.com/apache/spark/pull/16233/files#r95662299. We try to wrap the child by: 1. Generate the `queryOutput` by: 1.1. If the query column names are defined, map the column names to attributes in the child output by name; 1.2. Else set the child output attributes to `queryOutput`. 2. Map the `queryQutput` to view output by index, if the corresponding attributes don't match, try to up cast and alias the attribute in `queryOutput` to the attribute in the view output. 3. Add a Project over the child, with the new output generated by the previous steps. If the view output doesn't have the same number of columns neither with the child output, nor with the query column names, throw an AnalysisException. ## How was this patch tested? Add new test cases in `SQLViewSuite`. Author: jiangxingbo <jiangxb1987@gmail.com> Closes #16561 from jiangxb1987/alias-view.
* [SPARK-19082][SQL] Make ignoreCorruptFiles work for ParquetLiang-Chi Hsieh2017-01-165-8/+140
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? We have a config `spark.sql.files.ignoreCorruptFiles` which can be used to ignore corrupt files when reading files in SQL. Currently the `ignoreCorruptFiles` config has two issues and can't work for Parquet: 1. We only ignore corrupt files in `FileScanRDD` . Actually, we begin to read those files as early as inferring data schema from the files. For corrupt files, we can't read the schema and fail the program. A related issue reported at http://apache-spark-developers-list.1001551.n3.nabble.com/Skip-Corrupted-Parquet-blocks-footer-tc20418.html 2. In `FileScanRDD`, we assume that we only begin to read the files when starting to consume the iterator. However, it is possibly the files are read before that. In this case, `ignoreCorruptFiles` config doesn't work too. This patch targets Parquet datasource. If this direction is ok, we can address the same issue for other datasources like Orc. Two main changes in this patch: 1. Replace `ParquetFileReader.readAllFootersInParallel` by implementing the logic to read footers in multi-threaded manner We can't ignore corrupt files if we use `ParquetFileReader.readAllFootersInParallel`. So this patch implements the logic to do the similar thing in `readParquetFootersInParallel`. 2. In `FileScanRDD`, we need to ignore corrupt file too when we call `readFunction` to return iterator. One thing to notice is: We read schema from Parquet file's footer. The method to read footer `ParquetFileReader.readFooter` throws `RuntimeException`, instead of `IOException`, if it can't successfully read the footer. Please check out https://github.com/apache/parquet-mr/blob/df9d8e415436292ae33e1ca0b8da256640de9710/parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java#L470. So this patch catches `RuntimeException`. One concern is that it might also shadow other runtime exceptions other than reading corrupt files. ## How was this patch tested? Jenkins tests. Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #16474 from viirya/fix-ignorecorrupted-parquet-files.
* [SPARK-19120] Refresh Metadata Cache After Loading Hive Tablesgatorsmile2017-01-153-14/+75
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ### What changes were proposed in this pull request? ```Scala sql("CREATE TABLE tab (a STRING) STORED AS PARQUET") // This table fetch is to fill the cache with zero leaf files spark.table("tab").show() sql( s""" |LOAD DATA LOCAL INPATH '$newPartitionDir' OVERWRITE |INTO TABLE tab """.stripMargin) spark.table("tab").show() ``` In the above example, the returned result is empty after table loading. The metadata cache could be out of dated after loading new data into the table, because loading/inserting does not update the cache. So far, the metadata cache is only used for data source tables. Thus, for Hive serde tables, only `parquet` and `orc` formats are facing such issues, because the Hive serde tables in the format of parquet/orc could be converted to data source tables when `spark.sql.hive.convertMetastoreParquet`/`spark.sql.hive.convertMetastoreOrc` is on. This PR is to refresh the metadata cache after processing the `LOAD DATA` command. In addition, Spark SQL does not convert **partitioned** Hive tables (orc/parquet) to data source tables in the write path, but the read path is using the metadata cache for both **partitioned** and non-partitioned Hive tables (orc/parquet). That means, writing the partitioned parquet/orc tables still use `InsertIntoHiveTable`, instead of `InsertIntoHadoopFsRelationCommand`. To avoid reading the out-of-dated cache, `InsertIntoHiveTable` needs to refresh the metadata cache for partitioned tables. Note, it does not need to refresh the cache for non-partitioned parquet/orc tables, because it does not call `InsertIntoHiveTable` at all. Based on the comments, this PR will keep the existing logics unchanged. That means, we always refresh the table no matter whether the table is partitioned or not. ### How was this patch tested? Added test cases in parquetSuites.scala Author: gatorsmile <gatorsmile@gmail.com> Closes #16500 from gatorsmile/refreshInsertIntoHiveTable.
* [SPARK-19206][DOC][DSTREAM] Fix outdated parameter descriptions in kafka010uncleGen2017-01-153-25/+16
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fix outdated parameter descriptions in kafka010 ## How was this patch tested? cc koeninger zsxwing Author: uncleGen <hustyugm@gmail.com> Closes #16569 from uncleGen/SPARK-19206.
* [SPARK-18971][CORE] Upgrade Netty to 4.0.43.FinalShixiong Zhu2017-01-156-6/+6
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Upgrade Netty to `4.0.43.Final` to add the fix for https://github.com/netty/netty/issues/6153 ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #16568 from zsxwing/SPARK-18971.
* [MINOR][DOC] Document local[*,F] master modesMaurus Cuelenaere2017-01-151-0/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? core/src/main/scala/org/apache/spark/SparkContext.scala contains LOCAL_N_FAILURES_REGEX master mode, but this was never documented, so do so. ## How was this patch tested? By using the Github Markdown preview feature. Author: Maurus Cuelenaere <mcuelenaere@gmail.com> Closes #16562 from mcuelenaere/patch-1.
* [SPARK-19042] spark executor can't download the jars when uber jar's http ↵xiaojian.fxj2017-01-151-2/+2
| | | | | | | | | | url contains any query strings If the uber jars' https contains any query strings, the Executor.updateDependencies method can't can't download the jars correctly. This is because the "localName = name.split("/").last" won't get the expected jar's url. The bug fix is the same as [SPARK-17855] Author: xiaojian.fxj <xiaojian.fxj@alibaba-inc.com> Closes #16509 from hustfxj/bug.
* [SPARK-19207][SQL] LocalSparkSession should use Slf4JLoggerFactory.INSTANCETsuyoshi Ozawa2017-01-151-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Using Slf4JLoggerFactory.INSTANCE instead of creating Slf4JLoggerFactory's object with constructor. It's deprecated. ## How was this patch tested? With running StateStoreRDDSuite. Author: Tsuyoshi Ozawa <ozawa@apache.org> Closes #16570 from oza/SPARK-19207.
* [SPARK-19151][SQL] DataFrameWriter.saveAsTable support hive overwritewindpiger2017-01-143-14/+34
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? After [SPARK-19107](https://issues.apache.org/jira/browse/SPARK-19107), we now can treat hive as a data source and create hive tables with DataFrameWriter and Catalog. However, the support is not completed, there are still some cases we do not support. This PR implement: DataFrameWriter.saveAsTable work with hive format with overwrite mode ## How was this patch tested? unit test added Author: windpiger <songjun@outlook.com> Closes #16549 from windpiger/saveAsTableWithHiveOverwrite.
* [SPARK-19221][PROJECT INFRA][R] Add winutils binaries to the path in ↵hyukjinkwon2017-01-141-0/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | AppVeyor tests for Hadoop libraries to call native codes properly ## What changes were proposed in this pull request? It seems Hadoop libraries need winutils binaries for native libraries in the path. It is not a problem in tests for now because we are only testing SparkR on Windows via AppVeyor but it can be a problem if we run Scala tests via AppVeyor as below: ``` - SPARK-18220: read Hive orc table with varchar column *** FAILED *** (3 seconds, 937 milliseconds) org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625) at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:609) at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$withHiveState$1.apply(HiveClientImpl.scala:283) ... ``` This PR proposes to add it to the `Path` for AppVeyor tests. ## How was this patch tested? Manually via AppVeyor. **Before** https://ci.appveyor.com/project/spark-test/spark/build/549-windows-complete/job/gc8a1pjua2bc4i8m **After** https://ci.appveyor.com/project/spark-test/spark/build/572-windows-complete/job/c4vrysr5uvj2hgu7 Author: hyukjinkwon <gurwls223@gmail.com> Closes #16584 from HyukjinKwon/set-path-appveyor.
* [SPARK-19180] [SQL] the offset of short should be 2 in OffHeapColumnYucai Yu2017-01-132-1/+64
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? the offset of short is 4 in OffHeapColumnVector's putShorts, but actually it should be 2. ## How was this patch tested? unit test Author: Yucai Yu <yucai.yu@intel.com> Closes #16555 from yucai/offheap_short.
* [SPARK-18335][SPARKR] createDataFrame to support numPartitions parameterFelix Cheung2017-01-134-14/+72
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? To allow specifying number of partitions when the DataFrame is created ## How was this patch tested? manual, unit tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16512 from felixcheung/rnumpart.
* [SPARK-18687][PYSPARK][SQL] Backward compatibility - creating a Dataframe on ↵Vinayak2017-01-132-2/+7
| | | | | | | | | | | | | | | | | a new SQLContext object fails with a Derby error Change is for SQLContext to reuse the active SparkSession during construction if the sparkContext supplied is the same as the currently active SparkContext. Without this change, a new SparkSession is instantiated that results in a Derby error when attempting to create a dataframe using a new SQLContext object even though the SparkContext supplied to the new SQLContext is same as the currently active one. Refer https://issues.apache.org/jira/browse/SPARK-18687 for details on the error and a repro. Existing unit tests and a new unit test added to pyspark-sql: /python/run-tests --python-executables=python --modules=pyspark-sql Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Vinayak <vijoshi5@in.ibm.com> Author: Vinayak Joshi <vijoshi@users.noreply.github.com> Closes #16119 from vijoshi/SPARK-18687_master.
* Fix missing close-parens for In filter's toStringAndrew Ash2017-01-121-1/+1
| | | | | | | | | | Otherwise the open parentheses isn't closed in query plan descriptions of batch scans. PushedFilters: [In(COL_A, [1,2,4,6,10,16,219,815], IsNotNull(COL_B), ... Author: Andrew Ash <andrew@andrewash.com> Closes #16558 from ash211/patch-9.
* [SPARK-19178][SQL] convert string of large numbers to int should return nullWenchen Fan2017-01-125-25/+414
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When we convert a string to integral, we will convert that string to `decimal(20, 0)` first, so that we can turn a string with decimal format to truncated integral, e.g. `CAST('1.2' AS int)` will return `1`. However, this brings problems when we convert a string with large numbers to integral, e.g. `CAST('1234567890123' AS int)` will return `1912276171`, while Hive returns null as we expected. This is a long standing bug(seems it was there the first day Spark SQL was created), this PR fixes this bug by adding the native support to convert `UTF8String` to integral. ## How was this patch tested? new regression tests Author: Wenchen Fan <wenchen@databricks.com> Closes #16550 from cloud-fan/string-to-int.
* [SPARK-19142][SPARKR] spark.kmeans should take seed, initSteps, and tol as ↵wm624@hotmail.com2017-01-123-3/+39
| | | | | | | | | | | | | | | parameters ## What changes were proposed in this pull request? spark.kmeans doesn't have interface to set initSteps, seed and tol. As Spark Kmeans algorithm doesn't take the same set of parameters as R kmeans, we should maintain a different interface in spark.kmeans. Add missing parameters and corresponding document. Modified existing unit tests to take additional parameters. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16523 from wangmiao1981/kmeans.
* [SPARK-19092][SQL] Save() API of DataFrameWriter should not scan all the ↵gatorsmile2017-01-133-97/+106
| | | | | | | | | | | | | | | | saved files ### What changes were proposed in this pull request? `DataFrameWriter`'s [save() API](https://github.com/gatorsmile/spark/blob/5d38f09f47a767a342a0a8219c63efa2943b5d1f/sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala#L207) is performing a unnecessary full filesystem scan for the saved files. The save() API is the most basic/core API in `DataFrameWriter`. We should avoid it. The related PR: https://github.com/apache/spark/pull/16090 ### How was this patch tested? Updated the existing test cases. Author: gatorsmile <gatorsmile@gmail.com> Closes #16481 from gatorsmile/saveFileScan.
* [SPARK-19110][MLLIB][FOLLOWUP] Add a unit test for testing logPrior and ↵wm624@hotmail.com2017-01-121-0/+2
| | | | | | | | | | | | | | logLikelihood of DistributedLDAModel in MLLIB ## What changes were proposed in this pull request? #16491 added the fix to mllib and a unit test to ml. This followup PR, add unit tests to mllib suite. ## How was this patch tested? Unit tests. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #16524 from wangmiao1981/ldabug.
* [SPARK-17237][SQL] Remove backticks in a pivot result schemaTakeshi YAMAMURO2017-01-123-2/+10
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Pivoting adds backticks (e.g. 3_count(\`c\`)) in column names and, in some cases, thes causes analysis exceptions like; ``` scala> val df = Seq((2, 3, 4), (3, 4, 5)).toDF("a", "x", "y") scala> df.groupBy("a").pivot("x").agg(count("y"), avg("y")).na.fill(0) org.apache.spark.sql.AnalysisException: syntax error in attribute name: `3_count(`y`)`; at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute$.e$1(unresolved.scala:134) at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute$.parseAttributeName(unresolved.scala:144) ... ``` So, this pr proposes to remove these backticks from column names. ## How was this patch tested? Added a test in `DataFrameAggregateSuite`. Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #14812 from maropu/SPARK-17237.
* [SPARK-12757][CORE] lower "block locks were not released" log to info levelFelix Cheung2017-01-121-1/+1
| | | | | | | | | | ## What changes were proposed in this pull request? lower "block locks were not released" log to info level, as it is generating a lot of warnings in running ML, graph calls, as pointed out in the JIRA. Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16513 from felixcheung/blocklockswarn.
* [SPARK-19055][SQL][PYSPARK] Fix SparkSession initialization when ↵Liang-Chi Hsieh2017-01-122-6/+33
| | | | | | | | | | | | | | | | | | | | | | SparkContext is stopped ## What changes were proposed in this pull request? In SparkSession initialization, we store created the instance of SparkSession into a class variable _instantiatedContext. Next time we can use SparkSession.builder.getOrCreate() to retrieve the existing SparkSession instance. However, when the active SparkContext is stopped and we create another new SparkContext to use, the existing SparkSession is still associated with the stopped SparkContext. So the operations with this existing SparkSession will be failed. We need to detect such case in SparkSession and renew the class variable _instantiatedContext if needed. ## How was this patch tested? New test added in PySpark. Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #16454 from viirya/fix-pyspark-sparksession.
* [SPARK-18969][SQL] Support grouping by nondeterministic expressionsWenchen Fan2017-01-123-17/+86
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently nondeterministic expressions are allowed in `Aggregate`(see the [comment](https://github.com/apache/spark/blob/v2.0.2/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala#L249-L251)), but the `PullOutNondeterministic` analyzer rule failed to handle `Aggregate`, this PR fixes it. close https://github.com/apache/spark/pull/16379 There is still one remaining issue: `SELECT a + rand() FROM t GROUP BY a + rand()` is not allowed, because the 2 `rand()` are different(we generate random seed as the default seed for `rand()`). https://issues.apache.org/jira/browse/SPARK-19035 is tracking this issue. ## How was this patch tested? a new test suite Author: Wenchen Fan <wenchen@databricks.com> Closes #16404 from cloud-fan/groupby.
* [SPARK-19183][SQL] Add deleteWithJob hook to internal commit protocol APIEric Liang2017-01-129-110/+149
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently in SQL we implement overwrites by calling fs.delete() directly on the original data. This is not ideal since we the original files end up deleted even if the job aborts. We should extend the commit protocol to allow file overwrites to be managed as well. ## How was this patch tested? Existing tests. I also fixed a bunch of tests that were depending on the commit protocol implementation being set to the legacy mapreduce one. cc rxin cloud-fan Author: Eric Liang <ekl@databricks.com> Author: Eric Liang <ekhliang@gmail.com> Closes #16554 from ericl/add-delete-protocol.
* [SPARK-19164][PYTHON][SQL] Remove unused UserDefinedFunction._broadcastzero3232017-01-121-6/+0
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Removes `UserDefinedFunction._broadcast` and `UserDefinedFunction.__del__` method. ## How was this patch tested? Existing unit tests. Author: zero323 <zero323@users.noreply.github.com> Closes #16538 from zero323/SPARK-19164.
* [SPARK-19158][SPARKR][EXAMPLES] Fix ml.R example fails due to lack of e1071 ↵Yanbo Liang2017-01-121-8/+7
| | | | | | | | | | | | | | package. ## What changes were proposed in this pull request? ```ml.R``` example depends on ```e1071``` package, if it's not available in users' environment, it will fail. I think the example should not depends on third-party packages, so I update it to remove the dependency. ## How was this patch tested? Manual test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #16548 from yanboliang/spark-19158.
* [SPARK-16848][SQL] Check schema validation for user-specified schema in jdbc ↵hyukjinkwon2017-01-113-3/+38
| | | | | | | | | | | | | | | | | | | | | | | | | | | | and table APIs ## What changes were proposed in this pull request? This PR proposes to throw an exception for both jdbc APIs when user specified schemas are not allowed or useless. **DataFrameReader.jdbc(...)** ``` scala spark.read.schema(StructType(Nil)).jdbc(...) ``` **DataFrameReader.table(...)** ```scala spark.read.schema(StructType(Nil)).table("usrdb.test") ``` ## How was this patch tested? Unit test in `JDBCSuite` and `DataFrameReaderWriterSuite`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #14451 from HyukjinKwon/SPARK-16848.
* [SPARK-19132][SQL] Add test cases for row size estimation and aggregate ↵wangzhenhua2017-01-117-160/+248
| | | | | | | | | | | | | | | | estimation ## What changes were proposed in this pull request? In this pr, we add more test cases for project and aggregate estimation. ## How was this patch tested? Add test cases. Author: wangzhenhua <wangzhenhua@huawei.com> Closes #16551 from wzhfy/addTests.
* [SPARK-19149][SQL] Follow-up: simplify cache implementation.Reynold Xin2017-01-111-8/+13
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch simplifies slightly the logical plan statistics cache implementation, as discussed in https://github.com/apache/spark/pull/16529 ## How was this patch tested? N/A - this has no behavior change. Author: Reynold Xin <rxin@databricks.com> Closes #16544 from rxin/SPARK-19149.
* [SPARK-18801][SQL] Support resolve a nested viewjiangxingbo2017-01-1116-69/+516
| | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? We should be able to resolve a nested view. The main advantage is that if you update an underlying view, the current view also gets updated. The new approach should be compatible with older versions of SPARK/HIVE, that means: 1. The new approach should be able to resolve the views that created by older versions of SPARK/HIVE; 2. The new approach should be able to resolve the views that are currently supported by SPARK SQL. The new approach mainly brings in the following changes: 1. Add a new operator called `View` to keep track of the CatalogTable that describes the view, and the output attributes as well as the child of the view; 2. Update the `ResolveRelations` rule to resolve the relations and views, note that a nested view should be resolved correctly; 3. Add `viewDefaultDatabase` variable to `CatalogTable` to keep track of the default database name used to resolve a view, if the `CatalogTable` is not a view, then the variable should be `None`; 4. Add `AnalysisContext` to enable us to still support a view created with CTE/Windows query; 5. Enables the view support without enabling Hive support (i.e., enableHiveSupport); 6. Fix a weird behavior: the result of a view query may have different schema if the referenced table has been changed. After this PR, we try to cast the child output attributes to that from the view schema, throw an AnalysisException if cast is not allowed. Note this is compatible with the views defined by older versions of Spark(before 2.2), which have empty `defaultDatabase` and all the relations in `viewText` have database part defined. ## How was this patch tested? 1. Add new tests in `SessionCatalogSuite` to test the function `lookupRelation`; 2. Add new test case in `SQLViewSuite` to test resolve a nested view. Author: jiangxingbo <jiangxb1987@gmail.com> Closes #16233 from jiangxb1987/resolve-view.
* [SPARK-17568][CORE][DEPLOY] Add spark-submit option to override ivy settings ↵Bryan Cutler2017-01-114-74/+206
| | | | | | | | | | | | | | | | | | used to resolve packages/artifacts ## What changes were proposed in this pull request? Adding option in spark-submit to allow overriding the default IvySettings used to resolve artifacts as part of the Spark Packages functionality. This will allow all artifact resolution to go through a central managed repository, such as Nexus or Artifactory, where site admins can better approve and control what is used with Spark apps. This change restructures the creation of the IvySettings object in two distinct ways. First, if the `spark.ivy.settings` option is not defined then `buildIvySettings` will create a default settings instance, as before, with defined repositories (Maven Central) included. Second, if the option is defined, the ivy settings file will be loaded from the given path and only repositories defined within will be used for artifact resolution. ## How was this patch tested? Existing tests for default behaviour, Manual tests that load a ivysettings.xml file with local and Nexus repositories defined. Added new test to load a simple Ivy settings file with a local filesystem resolver. Author: Bryan Cutler <cutlerb@gmail.com> Author: Ian Hummel <ian@themodernlife.net> Closes #15119 from BryanCutler/spark-custom-IvySettings.
* [SPARK-19130][SPARKR] Support setting literal value as column implicitlyFelix Cheung2017-01-113-5/+39
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? ``` df$foo <- 1 ``` instead of ``` df$foo <- lit(1) ``` ## How was this patch tested? unit tests Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16510 from felixcheung/rlitcol.
* [SPARK-19021][YARN] Generailize HDFSCredentialProvider to support non HDFS ↵jerryshao2017-01-116-45/+54
| | | | | | | | | | | | | | security filesystems Currently Spark can only get token renewal interval from security HDFS (hdfs://), if Spark runs with other security file systems like webHDFS (webhdfs://), wasb (wasb://), ADLS, it will ignore these tokens and not get token renewal intervals from these tokens. These will make Spark unable to work with these security clusters. So instead of only checking HDFS token, we should generalize to support different DelegationTokenIdentifier. ## How was this patch tested? Manually verified in security cluster. Author: jerryshao <sshao@hortonworks.com> Closes #16432 from jerryshao/SPARK-19021.
* [SPARK-19149][SQL] Unify two sets of statistics in LogicalPlanwangzhenhua2017-01-1036-146/+161
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently we have two sets of statistics in LogicalPlan: a simple stats and a stats estimated by cbo, but the computing logic and naming are quite confusing, we need to unify these two sets of stats. ## How was this patch tested? Just modify existing tests. Author: wangzhenhua <wangzhenhua@huawei.com> Author: Zhenhua Wang <wzh_zju@163.com> Closes #16529 from wzhfy/unifyStats.
* [SPARK-19157][SQL] should be able to change spark.sql.runSQLOnFiles at runtimeWenchen Fan2017-01-104-11/+37
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The analyzer rule that supports to query files directly will be added to `Analyzer.extendedResolutionRules` when SparkSession is created, according to the `spark.sql.runSQLOnFiles` flag. If the flag is off when we create `SparkSession`, this rule is not added and we can not query files directly even we turn on the flag later. This PR fixes this bug by always adding that rule to `Analyzer.extendedResolutionRules`. ## How was this patch tested? new regression test Author: Wenchen Fan <wenchen@databricks.com> Closes #16531 from cloud-fan/sql-on-files.
* [SPARK-19140][SS] Allow update mode for non-aggregation streaming queriesShixiong Zhu2017-01-108-52/+72
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR allow update mode for non-aggregation streaming queries. It will be same as the append mode if a query has no aggregations. ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #16520 from zsxwing/update-without-agg.
* [SPARK-18997][CORE] Recommended upgrade libthrift to 0.9.3Sean Owen2017-01-106-11/+11
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Updates to libthrift 0.9.3 to address a CVE. ## How was this patch tested? Existing tests. Author: Sean Owen <sowen@cloudera.com> Closes #16530 from srowen/SPARK-18997.
* [SPARK-19133][SPARKR][ML] fix glm for Gamma, clarify glm family supportedFelix Cheung2017-01-103-11/+24
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? R family is a longer list than what Spark supports. ## How was this patch tested? manual Author: Felix Cheung <felixcheung_m@hotmail.com> Closes #16511 from felixcheung/rdocglmfamily.
* [SPARK-19137][SQL] Fix `withSQLConf` to reset `OptionalConfigEntry` correctlyDongjoon Hyun2017-01-101-1/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? `DataStreamReaderWriterSuite` makes test files in source folder like the followings. Interestingly, the root cause is `withSQLConf` fails to reset `OptionalConfigEntry` correctly. In other words, it resets the config into `Some(undefined)`. ```bash $ git status Untracked files: (use "git add <file>..." to include in what will be committed) sql/core/%253Cundefined%253E/ sql/core/%3Cundefined%3E/ ``` ## How was this patch tested? Manual. ``` build/sbt "project sql" test git status ``` Author: Dongjoon Hyun <dongjoon@apache.org> Closes #16522 from dongjoon-hyun/SPARK-19137.
* [SPARK-19113][SS][TESTS] Set UncaughtExceptionHandler in onQueryStarted to ↵Shixiong Zhu2017-01-102-9/+26
| | | | | | | | | | | | | | | | ensure catching fatal errors during query initialization ## What changes were proposed in this pull request? StreamTest sets `UncaughtExceptionHandler` after starting the query now. It may not be able to catch fatal errors during query initialization. This PR uses `onQueryStarted` callback to fix it. ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #16492 from zsxwing/SPARK-19113.
* [SPARK-18857][SQL] Don't use `Iterator.duplicate` for `incrementalCollect` ↵Dongjoon Hyun2017-01-102-11/+26
| | | | | | | | | | | | | | | | | | | | | in Thrift Server ## What changes were proposed in this pull request? To support `FETCH_FIRST`, SPARK-16563 used Scala `Iterator.duplicate`. However, Scala `Iterator.duplicate` uses a **queue to buffer all items between both iterators**, this causes GC and hangs for queries with large number of rows. We should not use this, especially for `spark.sql.thriftServer.incrementalCollect`. https://github.com/scala/scala/blob/2.12.x/src/library/scala/collection/Iterator.scala#L1262-L1300 ## How was this patch tested? Pass the existing tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #16440 from dongjoon-hyun/SPARK-18857.
* [SPARK-19117][TESTS] Skip the tests using script transformation on Windowshyukjinkwon2017-01-107-46/+78
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR proposes to skip the tests for script transformation failed on Windows due to fixed bash location. ``` SQLQuerySuite: - script *** FAILED *** (553 milliseconds) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 56.0 failed 1 times, most recent failure: Lost task 0.0 in stage 56.0 (TID 54, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - Star Expansion - script transform *** FAILED *** (2 seconds, 375 milliseconds) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 389.0 failed 1 times, most recent failure: Lost task 0.0 in stage 389.0 (TID 725, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - test script transform for stdout *** FAILED *** (2 seconds, 813 milliseconds) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 391.0 failed 1 times, most recent failure: Lost task 0.0 in stage 391.0 (TID 726, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - test script transform for stderr *** FAILED *** (2 seconds, 407 milliseconds) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 393.0 failed 1 times, most recent failure: Lost task 0.0 in stage 393.0 (TID 727, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - test script transform data type *** FAILED *** (171 milliseconds) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 395.0 failed 1 times, most recent failure: Lost task 0.0 in stage 395.0 (TID 728, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified ``` ``` HiveQuerySuite: - transform *** FAILED *** (359 milliseconds) Failed to execute query using catalyst: Error: Job aborted due to stage failure: Task 0 in stage 1347.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1347.0 (TID 2395, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - schema-less transform *** FAILED *** (344 milliseconds) Failed to execute query using catalyst: Error: Job aborted due to stage failure: Task 0 in stage 1348.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1348.0 (TID 2396, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - transform with custom field delimiter *** FAILED *** (296 milliseconds) Failed to execute query using catalyst: Error: Job aborted due to stage failure: Task 0 in stage 1349.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1349.0 (TID 2397, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - transform with custom field delimiter2 *** FAILED *** (297 milliseconds) Failed to execute query using catalyst: Error: Job aborted due to stage failure: Task 0 in stage 1350.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1350.0 (TID 2398, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - transform with custom field delimiter3 *** FAILED *** (312 milliseconds) Failed to execute query using catalyst: Error: Job aborted due to stage failure: Task 0 in stage 1351.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1351.0 (TID 2399, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - transform with SerDe2 *** FAILED *** (437 milliseconds) org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1355.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1355.0 (TID 2403, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified ``` ``` LogicalPlanToSQLSuite: - script transformation - schemaless *** FAILED *** (78 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1968.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1968.0 (TID 3932, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation - alias list *** FAILED *** (94 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1969.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1969.0 (TID 3933, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation - alias list with type *** FAILED *** (93 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1970.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1970.0 (TID 3934, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation - row format delimited clause with only one format property *** FAILED *** (78 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1971.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1971.0 (TID 3935, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation - row format delimited clause with multiple format properties *** FAILED *** (94 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1972.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1972.0 (TID 3936, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation - row format serde clauses with SERDEPROPERTIES *** FAILED *** (78 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1973.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1973.0 (TID 3937, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation - row format serde clauses without SERDEPROPERTIES *** FAILED *** (78 milliseconds) ... Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1974.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1974.0 (TID 3938, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified ``` ``` ScriptTransformationSuite: - cat without SerDe *** FAILED *** (156 milliseconds) ... Caused by: java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - cat with LazySimpleSerDe *** FAILED *** (63 milliseconds) ... org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2383.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2383.0 (TID 4819, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation should not swallow errors from upstream operators (no serde) *** FAILED *** (78 milliseconds) ... org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2384.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2384.0 (TID 4820, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - script transformation should not swallow errors from upstream operators (with serde) *** FAILED *** (47 milliseconds) ... org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2385.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2385.0 (TID 4821, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified - SPARK-14400 script transformation should fail for bad script command *** FAILED *** (47 milliseconds) "Job aborted due to stage failure: Task 0 in stage 2386.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2386.0 (TID 4822, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified ``` ## How was this patch tested? AppVeyor as below: ``` SQLQuerySuite: - script !!! CANCELED !!! (63 milliseconds) - Star Expansion - script transform !!! CANCELED !!! (0 milliseconds) - test script transform for stdout !!! CANCELED !!! (0 milliseconds) - test script transform for stderr !!! CANCELED !!! (0 milliseconds) - test script transform data type !!! CANCELED !!! (0 milliseconds) ``` ``` HiveQuerySuite: - transform !!! CANCELED !!! (31 milliseconds) - schema-less transform !!! CANCELED !!! (0 milliseconds) - transform with custom field delimiter !!! CANCELED !!! (0 milliseconds) - transform with custom field delimiter2 !!! CANCELED !!! (0 milliseconds) - transform with custom field delimiter3 !!! CANCELED !!! (0 milliseconds) - transform with SerDe2 !!! CANCELED !!! (0 milliseconds) ``` ``` LogicalPlanToSQLSuite: - script transformation - schemaless !!! CANCELED !!! (78 milliseconds) - script transformation - alias list !!! CANCELED !!! (0 milliseconds) - script transformation - alias list with type !!! CANCELED !!! (0 milliseconds) - script transformation - row format delimited clause with only one format property !!! CANCELED !!! (15 milliseconds) - script transformation - row format delimited clause with multiple format properties !!! CANCELED !!! (0 milliseconds) - script transformation - row format serde clauses with SERDEPROPERTIES !!! CANCELED !!! (0 milliseconds) - script transformation - row format serde clauses without SERDEPROPERTIES !!! CANCELED !!! (0 milliseconds) ``` ``` ScriptTransformationSuite: - cat without SerDe !!! CANCELED !!! (62 milliseconds) - cat with LazySimpleSerDe !!! CANCELED !!! (0 milliseconds) - script transformation should not swallow errors from upstream operators (no serde) !!! CANCELED !!! (0 milliseconds) - script transformation should not swallow errors from upstream operators (with serde) !!! CANCELED !!! (0 milliseconds) - SPARK-14400 script transformation should fail for bad script command !!! CANCELED !!! (0 milliseconds) ``` Jenkins tests Author: hyukjinkwon <gurwls223@gmail.com> Closes #16501 from HyukjinKwon/windows-bash.
* [SPARK-18922][SQL][CORE][STREAMING][TESTS] Fix all identified tests failed ↵hyukjinkwon2017-01-1023-96/+181
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | due to path and resource-not-closed problems on Windows ## What changes were proposed in this pull request? This PR proposes to fix all the test failures identified by testing with AppVeyor. **Scala - aborted tests** ``` WindowQuerySuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.execution.WindowQuerySuite *** ABORTED *** (156 milliseconds) org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive argetscala-2.11 est-classesdatafilespart_tiny.txt; OrcSourceSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.orc.OrcSourceSuite *** ABORTED *** (62 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); ParquetMetastoreSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetMetastoreSuite *** ABORTED *** (4 seconds, 703 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); ParquetSourceSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetSourceSuite *** ABORTED *** (3 seconds, 907 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-581a6575-454f-4f21-a516-a07f95266143; KafkaRDDSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaRDDSuite *** ABORTED *** (5 seconds, 212 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-4722304d-213e-4296-b556-951df1a46807 DirectKafkaStreamSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.DirectKafkaStreamSuite *** ABORTED *** (7 seconds, 127 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d0d3eba7-4215-4e10-b40e-bb797e89338e at org.apache.spark.util.Utils$.deleteRecursively(Utils.scala:1010) ReliableKafkaStreamSuite Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.ReliableKafkaStreamSuite *** ABORTED *** (5 seconds, 498 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d33e45a0-287e-4bed-acae-ca809a89d888 KafkaStreamSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaStreamSuite *** ABORTED *** (2 seconds, 892 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-59c9d169-5a56-4519-9ef0-cefdbd3f2e6c KafkaClusterSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaClusterSuite *** ABORTED *** (1 second, 690 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-3ef402b0-8689-4a60-85ae-e41e274f179d DirectKafkaStreamSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.DirectKafkaStreamSuite *** ABORTED *** (59 seconds, 626 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-426107da-68cf-4d94-b0d6-1f428f1c53f6 KafkaRDDSuite: Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.KafkaRDDSuite *** ABORTED *** (2 minutes, 6 seconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-b9ce7929-5dae-46ab-a0c4-9ef6f58fbc2 ``` **Java - failed tests** ``` Test org.apache.spark.streaming.kafka.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-1cee32f4-4390-4321-82c9-e8616b3f0fb0, took 9.61 sec Test org.apache.spark.streaming.kafka.JavaKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-f42695dd-242e-4b07-847c-f299b8e4676e, took 11.797 sec Test org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-85c0d062-78cf-459c-a2dd-7973572101ce, took 1.581 sec Test org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-49eb6b5c-8366-47a6-83f2-80c443c48280, took 17.895 sec org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-898cf826-d636-4b1c-a61a-c12a364c02e7, took 8.858 sec ``` **Scala - failed tests** ``` PartitionProviderCompatibilitySuite: - insert overwrite partition of new datasource table overwrites just partition *** FAILED *** (828 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-bb6337b9-4f99-45ab-ad2c-a787ab965c09 - SPARK-18635 special chars in partition values - partition management true *** FAILED *** (5 seconds, 360 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - SPARK-18635 special chars in partition values - partition management false *** FAILED *** (141 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); ``` ``` UtilsSuite: - reading offset bytes of a file (compressed) *** FAILED *** (0 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-ecb2b7d5-db8b-43a7-b268-1bf242b5a491 - reading offset bytes across multiple files (compressed) *** FAILED *** (0 milliseconds) java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-25cc47a8-1faa-4da5-8862-cf174df63ce0 ``` ``` StatisticsSuite: - MetastoreRelations fallback to HDFS for size estimation *** FAILED *** (110 milliseconds) org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'csv_table' not found in database 'default'; ``` ``` SQLQuerySuite: - permanent UDTF *** FAILED *** (125 milliseconds) org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count_temp'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 24 - describe functions - user defined functions *** FAILED *** (125 milliseconds) org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 7 - CTAS without serde with location *** FAILED *** (16 milliseconds) java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-ed673d73-edfc-404e-829e-2e2b9725d94e/c1 - derived from Hive query file: drop_database_removes_partition_dirs.q *** FAILED *** (47 milliseconds) java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_database_removes_partition_dirs_table - derived from Hive query file: drop_table_removes_partition_dirs.q *** FAILED *** (0 milliseconds) java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_table_removes_partition_dirs_table2 - SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH *** FAILED *** (109 milliseconds) java.nio.file.InvalidPathException: Illegal char <:> at index 2: /C:/projects/spark/sql/hive/projectsspark arget mpspark-1a122f8c-dfb3-46c4-bab1-f30764baee0e/*part-r* ``` ``` HiveDDLSuite: - drop external tables in default database *** FAILED *** (16 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - add/drop partitions - external table *** FAILED *** (16 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - create/drop database - location without pre-created directory *** FAILED *** (16 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - create/drop database - location with pre-created directory *** FAILED *** (32 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - drop database containing tables - CASCADE *** FAILED *** (94 milliseconds) CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675) - drop an empty database - CASCADE *** FAILED *** (63 milliseconds) CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675) - drop database containing tables - RESTRICT *** FAILED *** (47 milliseconds) CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675) - drop an empty database - RESTRICT *** FAILED *** (47 milliseconds) CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675) - CREATE TABLE LIKE an external data source table *** FAILED *** (140 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-c5eba16d-07ae-4186-95bb-21c5811cf888; - CREATE TABLE LIKE an external Hive serde table *** FAILED *** (16 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - desc table for data source table - no user-defined schema *** FAILED *** (125 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-e8bf5bf5-721a-4cbe-9d6 at scala.collection.immutable.List.foreach(List.scala:381)d-5543a8301c1d; ``` ``` MetastoreDataSourcesSuite - CTAS: persisted bucketed data source table *** FAILED *** (16 milliseconds) java.lang.IllegalArgumentException: Can not create a Path from an empty string ``` ``` ShowCreateTableSuite: - simple external hive table *** FAILED *** (0 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); ``` ``` PartitionedTablePerfStatsSuite: - hive table: partitioned pruned table reports only selected files *** FAILED *** (313 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: partitioned pruned table reports only selected files *** FAILED *** (219 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-311f45f8-d064-4023-a4bb-e28235bff64d; - hive table: lazy partition pruning reads only necessary partition data *** FAILED *** (203 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: lazy partition pruning reads only necessary partition data *** FAILED *** (187 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-fde874ca-66bd-4d0b-a40f-a043b65bf957; - hive table: lazy partition pruning with file status caching enabled *** FAILED *** (188 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: lazy partition pruning with file status caching enabled *** FAILED *** (187 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-e6d20183-dd68-4145-acbe-4a509849accd; - hive table: file status caching respects refresh table and refreshByPath *** FAILED *** (172 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: file status caching respects refresh table and refreshByPath *** FAILED *** (203 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-8b2c9651-2adf-4d58-874f-659007e21463; - hive table: file status cache respects size limit *** FAILED *** (219 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: file status cache respects size limit *** FAILED *** (171 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-7835ab57-cb48-4d2c-bb1d-b46d5a4c47e4; - datasource table: table setup does not scan filesystem *** FAILED *** (266 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-20598d76-c004-42a7-8061-6c56f0eda5e2; - hive table: table setup does not scan filesystem *** FAILED *** (266 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - hive table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 281 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 422 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4cfed321-4d1d-4b48-8d34-5c169afff383; - hive table: files read and cached when filesource partition management is off *** FAILED *** (234 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); - datasource table: all partition data cached in memory when partition management is off *** FAILED *** (203 milliseconds) org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark arget mpspark-4bcc0398-15c9-4f6a-811e-12d40f3eec12; - SPARK-18700: table loaded only once even when resolved concurrently *** FAILED *** (1 second, 266 milliseconds) org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string); ``` ``` HiveSparkSubmitSuite: - temporary Hive UDF: define a UDF and use it *** FAILED *** (2 seconds, 94 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - permanent Hive UDF: define a UDF and use it *** FAILED *** (281 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - permanent Hive UDF: use a already defined permanent function *** FAILED *** (718 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-8368: includes jars passed in through --jars *** FAILED *** (3 seconds, 521 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-8020: set sql conf in spark conf *** FAILED *** (0 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-8489: MissingRequirementError during reflection *** FAILED *** (94 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-9757 Persist Parquet relation with decimal column *** FAILED *** (16 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-11009 fix wrong result of Window function in cluster mode *** FAILED *** (16 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-14244 fix window partition size attribute binding failure *** FAILED *** (78 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - set spark.sql.warehouse.dir *** FAILED *** (16 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - set hive.metastore.warehouse.dir *** FAILED *** (15 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-16901: set javax.jdo.option.ConnectionURL *** FAILED *** (16 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified - SPARK-18360: default table path of tables in default database should depend on the location of default database *** FAILED *** (15 milliseconds) java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified ``` ``` UtilsSuite: - resolveURIs with multiple paths *** FAILED *** (0 milliseconds) ".../jar3,file:/C:/pi.py[%23]py.pi,file:/C:/path%..." did not equal ".../jar3,file:/C:/pi.py[#]py.pi,file:/C:/path%..." (UtilsSuite.scala:468) ``` ``` CheckpointSuite: - recovery with file input stream *** FAILED *** (10 seconds, 205 milliseconds) The code passed to eventually never returned normally. Attempted 660 times over 10.014272499999999 seconds. Last failure message: Unexpected internal error near index 1 \ ^. (CheckpointSuite.scala:680) ``` ## How was this patch tested? Manually via AppVeyor as below: **Scala - aborted tests** ``` WindowQuerySuite - all passed OrcSourceSuite: - SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds) org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625) ParquetMetastoreSuite - all passed ParquetSourceSuite - all passed KafkaRDDSuite - all passed DirectKafkaStreamSuite - all passed ReliableKafkaStreamSuite - all passed KafkaStreamSuite - all passed KafkaClusterSuite - all passed DirectKafkaStreamSuite - all passed KafkaRDDSuite - all passed ``` **Java - failed tests** ``` org.apache.spark.streaming.kafka.JavaKafkaRDDSuite - all passed org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite - all passed org.apache.spark.streaming.kafka.JavaKafkaStreamSuite - all passed org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite - all passed org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite - all passed ``` **Scala - failed tests** ``` PartitionProviderCompatibilitySuite: - insert overwrite partition of new datasource table overwrites just partition (1 second, 953 milliseconds) - SPARK-18635 special chars in partition values - partition management true (6 seconds, 31 milliseconds) - SPARK-18635 special chars in partition values - partition management false (4 seconds, 578 milliseconds) ``` ``` UtilsSuite: - reading offset bytes of a file (compressed) (203 milliseconds) - reading offset bytes across multiple files (compressed) (0 milliseconds) ``` ``` StatisticsSuite: - MetastoreRelations fallback to HDFS for size estimation (94 milliseconds) ``` ``` SQLQuerySuite: - permanent UDTF (407 milliseconds) - describe functions - user defined functions (441 milliseconds) - CTAS without serde with location (2 seconds, 831 milliseconds) - derived from Hive query file: drop_database_removes_partition_dirs.q (734 milliseconds) - derived from Hive query file: drop_table_removes_partition_dirs.q (563 milliseconds) - SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH (453 milliseconds) ``` ``` HiveDDLSuite: - drop external tables in default database (3 seconds, 5 milliseconds) - add/drop partitions - external table (2 seconds, 750 milliseconds) - create/drop database - location without pre-created directory (500 milliseconds) - create/drop database - location with pre-created directory (407 milliseconds) - drop database containing tables - CASCADE (453 milliseconds) - drop an empty database - CASCADE (375 milliseconds) - drop database containing tables - RESTRICT (328 milliseconds) - drop an empty database - RESTRICT (391 milliseconds) - CREATE TABLE LIKE an external data source table (953 milliseconds) - CREATE TABLE LIKE an external Hive serde table (3 seconds, 782 milliseconds) - desc table for data source table - no user-defined schema (1 second, 150 milliseconds) ``` ``` MetastoreDataSourcesSuite - CTAS: persisted bucketed data source table (875 milliseconds) ``` ``` ShowCreateTableSuite: - simple external hive table (78 milliseconds) ``` ``` PartitionedTablePerfStatsSuite: - hive table: partitioned pruned table reports only selected files (1 second, 109 milliseconds) - datasource table: partitioned pruned table reports only selected files (860 milliseconds) - hive table: lazy partition pruning reads only necessary partition data (859 milliseconds) - datasource table: lazy partition pruning reads only necessary partition data (1 second, 219 milliseconds) - hive table: lazy partition pruning with file status caching enabled (875 milliseconds) - datasource table: lazy partition pruning with file status caching enabled (890 milliseconds) - hive table: file status caching respects refresh table and refreshByPath (922 milliseconds) - datasource table: file status caching respects refresh table and refreshByPath (640 milliseconds) - hive table: file status cache respects size limit (469 milliseconds) - datasource table: file status cache respects size limit (453 milliseconds) - datasource table: table setup does not scan filesystem (328 milliseconds) - hive table: table setup does not scan filesystem (313 milliseconds) - hive table: num hive client calls does not scale with partition count (5 seconds, 431 milliseconds) - datasource table: num hive client calls does not scale with partition count (4 seconds, 79 milliseconds) - hive table: files read and cached when filesource partition management is off (656 milliseconds) - datasource table: all partition data cached in memory when partition management is off (484 milliseconds) - SPARK-18700: table loaded only once even when resolved concurrently (2 seconds, 578 milliseconds) ``` ``` HiveSparkSubmitSuite: - temporary Hive UDF: define a UDF and use it (1 second, 745 milliseconds) - permanent Hive UDF: define a UDF and use it (406 milliseconds) - permanent Hive UDF: use a already defined permanent function (375 milliseconds) - SPARK-8368: includes jars passed in through --jars (391 milliseconds) - SPARK-8020: set sql conf in spark conf (156 milliseconds) - SPARK-8489: MissingRequirementError during reflection (187 milliseconds) - SPARK-9757 Persist Parquet relation with decimal column (157 milliseconds) - SPARK-11009 fix wrong result of Window function in cluster mode (156 milliseconds) - SPARK-14244 fix window partition size attribute binding failure (156 milliseconds) - set spark.sql.warehouse.dir (172 milliseconds) - set hive.metastore.warehouse.dir (156 milliseconds) - SPARK-16901: set javax.jdo.option.ConnectionURL (157 milliseconds) - SPARK-18360: default table path of tables in default database should depend on the location of default database (172 milliseconds) ``` ``` UtilsSuite: - resolveURIs with multiple paths (0 milliseconds) ``` ``` CheckpointSuite: - recovery with file input stream (4 seconds, 452 milliseconds) ``` Note: after resolving the aborted tests, there is a test failure identified as below: ``` OrcSourceSuite: - SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds) org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625) ``` This does not look due to this problem so this PR does not fix it here. Author: hyukjinkwon <gurwls223@gmail.com> Closes #16451 from HyukjinKwon/all-path-resource-fixes.
* [SPARK-17645][MLLIB][ML][FOLLOW-UP] document minor changePeng, Meng2017-01-107-34/+96
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add FDR test case in ml/feature/ChiSqSelectorSuite. Improve some comments in the code. This is a follow-up pr for #15212. ## How was this patch tested? ut Author: Peng, Meng <peng.meng@intel.com> Closes #16434 from mpjlu/fdr_fwe_update.
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