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* [SPARK-19550][BUILD][CORE][WIP] Remove Java 7 supportSean Owen2017-02-169-1519/+2
| | | | | | | | | | | | | | | | | | | | | | | | - Move external/java8-tests tests into core, streaming, sql and remove - Remove MaxPermGen and related options - Fix some reflection / TODOs around Java 8+ methods - Update doc references to 1.7/1.8 differences - Remove Java 7/8 related build profiles - Update some plugins for better Java 8 compatibility - Fix a few Java-related warnings For the future: - Update Java 8 examples to fully use Java 8 - Update Java tests to use lambdas for simplicity - Update Java internal implementations to use lambdas ## How was this patch tested? Existing tests Author: Sean Owen <sowen@cloudera.com> Closes #16871 from srowen/SPARK-19493.
* [SPARK-19318][SQL] Fix to treat JDBC connection properties specified by the ↵sureshthalamati2017-02-141-0/+36
| | | | | | | | | | | | | | | | | | | | user in case-sensitive manner. ## What changes were proposed in this pull request? The reason for test failure is that the property “oracle.jdbc.mapDateToTimestamp” set by the test was getting converted into all lower case. Oracle database expects this property in case-sensitive manner. This test was passing in previous releases because connection properties were sent as user specified for the test case scenario. Fixes to handle all option uniformly in case-insensitive manner, converted the JDBC connection properties also to lower case. This PR enhances CaseInsensitiveMap to keep track of input case-sensitive keys , and uses those when creating connection properties that are passed to the JDBC connection. Alternative approach PR https://github.com/apache/spark/pull/16847 is to pass original input keys to JDBC data source by adding check in the Data source class and handle case-insensitivity in the JDBC source code. ## How was this patch tested? Added new test cases to JdbcSuite , and OracleIntegrationSuite. Ran docker integration tests passed on my laptop, all tests passed successfully. Author: sureshthalamati <suresh.thalamati@gmail.com> Closes #16891 from sureshthalamati/jdbc_case_senstivity_props_fix-SPARK-19318.
* [SPARK-19564][SPARK-19559][SS][KAFKA] KafkaOffsetReader's consumers should ↵Liwei Lin2017-02-121-4/+7
| | | | | | | | | | | | | | | | | | | | not be in the same group ## What changes were proposed in this pull request? In `KafkaOffsetReader`, when error occurs, we abort the existing consumer and create a new consumer. In our current implementation, the first consumer and the second consumer would be in the same group (which leads to SPARK-19559), **_violating our intention of the two consumers not being in the same group._** The cause is that, in our current implementation, the first consumer is created before `groupId` and `nextId` are initialized in the constructor. Then even if `groupId` and `nextId` are increased during the creation of that first consumer, `groupId` and `nextId` would still be initialized to default values in the constructor for the second consumer. We should make sure that `groupId` and `nextId` are initialized before any consumer is created. ## How was this patch tested? Ran 100 times of `KafkaSourceSuite`; all passed Author: Liwei Lin <lwlin7@gmail.com> Closes #16902 from lw-lin/SPARK-19564-.
* [SPARK-18682][SS] Batch Source for KafkaTyson Condie2017-02-0712-430/+1180
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Today, you can start a stream that reads from kafka. However, given kafka's configurable retention period, it seems like sometimes you might just want to read all of the data that is available now. As such we should add a version that works with spark.read as well. The options should be the same as the streaming kafka source, with the following differences: startingOffsets should default to earliest, and should not allow latest (which would always be empty). endingOffsets should also be allowed and should default to latest. the same assign json format as startingOffsets should also be accepted. It would be really good, if things like .limit(n) were enough to prevent all the data from being read (this might just work). ## How was this patch tested? KafkaRelationSuite was added for testing batch queries via KafkaUtils. Author: Tyson Condie <tcondie@gmail.com> Closes #16686 from tcondie/SPARK-18682.
* [SPARK-18020][STREAMING][KINESIS] Checkpoint SHARD_END to finish reading ↵Takeshi YAMAMURO2017-01-255-7/+116
| | | | | | | | | | | | | | closed shards ## What changes were proposed in this pull request? This pr is to fix an issue occurred when resharding Kinesis streams; the resharding makes the KCL throw an exception because Spark does not checkpoint `SHARD_END` when finishing reading closed shards in `KinesisRecordProcessor#shutdown`. This bug finally leads to stopping subscribing new split (or merged) shards. ## How was this patch tested? Added a test in `KinesisStreamSuite` to check if it works well when splitting/merging shards. Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #16213 from maropu/SPARK-18020.
* [SPARK-14536][SQL] fix to handle null value in array type column for postgres.sureshthalamati2017-01-201-2/+10
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? JDBC read is failing with NPE due to missing null value check for array data type if the source table has null values in the array type column. For null values Resultset.getArray() returns null. This PR adds null safe check to the Resultset.getArray() value before invoking method on the Array object. ## How was this patch tested? Updated the PostgresIntegration test suite to test null values. Ran docker integration tests on my laptop. Author: sureshthalamati <suresh.thalamati@gmail.com> Closes #15192 from sureshthalamati/jdbc_array_null_fix-SPARK-14536.
* [SPARK-19227][SPARK-19251] remove unused imports and outdated commentsuncleGen2017-01-186-7/+5
| | | | | | | | | | | | ## What changes were proposed in this pull request? remove ununsed imports and outdated comments, and fix some minor code style issue. ## How was this patch tested? existing ut Author: uncleGen <hustyugm@gmail.com> Closes #16591 from uncleGen/SPARK-19227.
* [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-18922][SQL][CORE][STREAMING][TESTS] Fix all identified tests failed ↵hyukjinkwon2017-01-106-29/+91
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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.
* [MINOR][DOCS] Remove consecutive duplicated words/typo in Spark RepoNiranjan Padmanabhan2017-01-043-3/+3
| | | | | | | | | | | | ## What changes were proposed in this pull request? There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words. ## How was this patch tested? N/A since only docs or comments were updated. Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com> Closes #16455 from neurons/np.structure_streaming_doc.
* [SPARK-17807][CORE] split test-tags into test-JARRyan Williams2016-12-218-1/+85
| | | | | | | | | | Remove spark-tag's compile-scope dependency (and, indirectly, spark-core's compile-scope transitive-dependency) on scalatest by splitting test-oriented tags into spark-tags' test JAR. Alternative to #16303. Author: Ryan Williams <ryan.blake.williams@gmail.com> Closes #16311 from ryan-williams/tt.
* [SPARK-18588][SS][KAFKA] Create a new KafkaConsumer when error happens to ↵Shixiong Zhu2016-12-213-31/+50
| | | | | | | | | | | | | | | | | | fix the flaky test ## What changes were proposed in this pull request? When KafkaSource fails on Kafka errors, we should create a new consumer to retry rather than using the existing broken one because it's possible that the broken one will fail again. This PR also assigns a new group id to the new created consumer for a possible race condition: the broken consumer cannot talk with the Kafka cluster in `close` but the new consumer can talk to Kafka cluster. I'm not sure if this will happen or not. Just for safety to avoid that the Kafka cluster thinks there are two consumers with the same group id in a short time window. (Note: CachedKafkaConsumer doesn't need this fix since `assign` never uses the group id.) ## How was this patch tested? In https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/70370/console , it ran this flaky test 120 times and all passed. Author: Shixiong Zhu <shixiong@databricks.com> Closes #16282 from zsxwing/kafka-fix.
* [SPARK-18588][TESTS] Ignore KafkaSourceStressForDontFailOnDataLossSuiteShixiong Zhu2016-12-131-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Disable KafkaSourceStressForDontFailOnDataLossSuite for now. ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #16275 from zsxwing/ignore-flaky-test.
* [SPARK-18620][STREAMING][KINESIS] Flatten input rates in timeline for ↵Takeshi YAMAMURO2016-12-103-2/+35
| | | | | | | | | | | | | | | | | | | | | streaming + kinesis ## What changes were proposed in this pull request? This pr is to make input rates in timeline more flat for spark streaming + kinesis. Since kinesis workers fetch records and push them into block generators in bulk, timeline in web UI has many spikes when `maxRates` applied (See a Figure.1 below). This fix splits fetched input records into multiple `adRecords` calls. Figure.1 Apply `maxRates=500` in vanilla Spark <img width="1084" alt="apply_limit in_vanilla_spark" src="https://cloud.githubusercontent.com/assets/692303/20823861/4602f300-b89b-11e6-95f3-164a37061305.png"> Figure.2 Apply `maxRates=500` in Spark with my patch <img width="1056" alt="apply_limit in_spark_with_my_patch" src="https://cloud.githubusercontent.com/assets/692303/20823882/6c46352c-b89b-11e6-81ab-afd8abfe0cfe.png"> ## How was this patch tested? Add tests to check to split input records into multiple `addRecords` calls. Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #16114 from maropu/SPARK-18620.
* [SPARK-18776][SS] Make Offset for FileStreamSource corrected formatted in jsonTathagata Das2016-12-081-1/+1
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? - Changed FileStreamSource to use new FileStreamSourceOffset rather than LongOffset. The field is named as `logOffset` to make it more clear that this is a offset in the file stream log. - Fixed bug in FileStreamSourceLog, the field endId in the FileStreamSourceLog.get(startId, endId) was not being used at all. No test caught it earlier. Only my updated tests caught it. Other minor changes - Dont use batchId in the FileStreamSource, as calling it batch id is extremely miss leading. With multiple sources, it may happen that a new batch has no new data from a file source. So offset of FileStreamSource != batchId after that batch. ## How was this patch tested? Updated unit test. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #16205 from tdas/SPARK-18776.
* [SPARK-18754][SS] Rename recentProgresses to recentProgressMichael Armbrust2016-12-071-1/+1
| | | | | | | | Based on an informal survey, users find this option easier to understand / remember. Author: Michael Armbrust <michael@databricks.com> Closes #16182 from marmbrus/renameRecentProgress.
* [SPARK-18588][TESTS] Fix flaky test: KafkaSourceStressForDontFailOnDataLossSuiteShixiong Zhu2016-12-074-37/+90
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fixed the following failures: ``` org.scalatest.exceptions.TestFailedDueToTimeoutException: The code passed to eventually never returned normally. Attempted 3745 times over 1.0000790851666665 minutes. Last failure message: assertion failed: failOnDataLoss-0 not deleted after timeout. ``` ``` sbt.ForkMain$ForkError: org.apache.spark.sql.streaming.StreamingQueryException: Query query-66 terminated with exception: null at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runBatches(StreamExecution.scala:252) at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:146) Caused by: sbt.ForkMain$ForkError: java.lang.NullPointerException: null at java.util.ArrayList.addAll(ArrayList.java:577) at org.apache.kafka.clients.Metadata.getClusterForCurrentTopics(Metadata.java:257) at org.apache.kafka.clients.Metadata.update(Metadata.java:177) at org.apache.kafka.clients.NetworkClient$DefaultMetadataUpdater.handleResponse(NetworkClient.java:605) at org.apache.kafka.clients.NetworkClient$DefaultMetadataUpdater.maybeHandleCompletedReceive(NetworkClient.java:582) at org.apache.kafka.clients.NetworkClient.handleCompletedReceives(NetworkClient.java:450) at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:269) at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.clientPoll(ConsumerNetworkClient.java:360) at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:224) at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:192) at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.awaitPendingRequests(ConsumerNetworkClient.java:260) at org.apache.kafka.clients.consumer.internals.AbstractCoordinator.ensureActiveGroup(AbstractCoordinator.java:222) at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.ensurePartitionAssignment(ConsumerCoordinator.java:366) at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:978) at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:938) at ... ``` ## How was this patch tested? Tested in #16048 by running many times. Author: Shixiong Zhu <shixiong@databricks.com> Closes #16109 from zsxwing/fix-kafka-flaky-test.
* [SPARK-18671][SS][TEST-MAVEN] Follow up PR to fix test for MavenTathagata Das2016-12-062-1/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Maven compilation seem to not allow resource is sql/test to be easily referred to in kafka-0-10-sql tests. So moved the kafka-source-offset-version-2.1.0 from sql test resources to kafka-0-10-sql test resources. ## How was this patch tested? Manually ran maven test Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #16183 from tdas/SPARK-18671-1.
* [SPARK-18671][SS][TEST] Added tests to ensure stability of that all ↵Tathagata Das2016-12-062-1/+20
| | | | | | | | | | | | | | | Structured Streaming log formats ## What changes were proposed in this pull request? To be able to restart StreamingQueries across Spark version, we have already made the logs (offset log, file source log, file sink log) use json. We should added tests with actual json files in the Spark such that any incompatible changes in reading the logs is immediately caught. This PR add tests for FileStreamSourceLog, FileStreamSinkLog, and OffsetSeqLog. ## How was this patch tested? new unit tests Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #16128 from tdas/SPARK-18671.
* [SPARK-18695] Bump master branch version to 2.2.0-SNAPSHOTReynold Xin2016-12-0213-13/+13
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch bumps master branch version to 2.2.0-SNAPSHOT. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #16126 from rxin/SPARK-18695.
* [SPARK-18516][SQL] Split state and progress in streamingTathagata Das2016-11-291-3/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR separates the status of a `StreamingQuery` into two separate APIs: - `status` - describes the status of a `StreamingQuery` at this moment, including what phase of processing is currently happening and if data is available. - `recentProgress` - an array of statistics about the most recent microbatches that have executed. A recent progress contains the following information: ``` { "id" : "2be8670a-fce1-4859-a530-748f29553bb6", "name" : "query-29", "timestamp" : 1479705392724, "inputRowsPerSecond" : 230.76923076923077, "processedRowsPerSecond" : 10.869565217391303, "durationMs" : { "triggerExecution" : 276, "queryPlanning" : 3, "getBatch" : 5, "getOffset" : 3, "addBatch" : 234, "walCommit" : 30 }, "currentWatermark" : 0, "stateOperators" : [ ], "sources" : [ { "description" : "KafkaSource[Subscribe[topic-14]]", "startOffset" : { "topic-14" : { "2" : 0, "4" : 1, "1" : 0, "3" : 0, "0" : 0 } }, "endOffset" : { "topic-14" : { "2" : 1, "4" : 2, "1" : 0, "3" : 0, "0" : 1 } }, "numRecords" : 3, "inputRowsPerSecond" : 230.76923076923077, "processedRowsPerSecond" : 10.869565217391303 } ] } ``` Additionally, in order to make it possible to correlate progress updates across restarts, we change the `id` field from an integer that is unique with in the JVM to a `UUID` that is globally unique. Author: Tathagata Das <tathagata.das1565@gmail.com> Author: Michael Armbrust <michael@databricks.com> Closes #15954 from marmbrus/queryProgress.
* [SPARK-3359][DOCS] Make javadoc8 working for unidoc/genjavadoc compatibility ↵hyukjinkwon2016-11-295-16/+28
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | in Java API documentation ## What changes were proposed in this pull request? This PR make `sbt unidoc` complete with Java 8. This PR roughly includes several fixes as below: - Fix unrecognisable class and method links in javadoc by changing it from `[[..]]` to `` `...` `` ```diff - * A column that will be computed based on the data in a [[DataFrame]]. + * A column that will be computed based on the data in a `DataFrame`. ``` - Fix throws annotations so that they are recognisable in javadoc - Fix URL links to `<a href="http..."></a>`. ```diff - * [[http://en.wikipedia.org/wiki/Decision_tree_learning Decision tree]] model for regression. + * <a href="http://en.wikipedia.org/wiki/Decision_tree_learning"> + * Decision tree (Wikipedia)</a> model for regression. ``` ```diff - * see http://en.wikipedia.org/wiki/Receiver_operating_characteristic + * see <a href="http://en.wikipedia.org/wiki/Receiver_operating_characteristic"> + * Receiver operating characteristic (Wikipedia)</a> ``` - Fix < to > to - `greater than`/`greater than or equal to` or `less than`/`less than or equal to` where applicable. - Wrap it with `{{{...}}}` to print them in javadoc or use `{code ...}` or `{literal ..}`. Please refer https://github.com/apache/spark/pull/16013#discussion_r89665558 - Fix `</p>` complaint ## How was this patch tested? Manually tested by `jekyll build` with Java 7 and 8 ``` java version "1.7.0_80" Java(TM) SE Runtime Environment (build 1.7.0_80-b15) Java HotSpot(TM) 64-Bit Server VM (build 24.80-b11, mixed mode) ``` ``` java version "1.8.0_45" Java(TM) SE Runtime Environment (build 1.8.0_45-b14) Java HotSpot(TM) 64-Bit Server VM (build 25.45-b02, mixed mode) ``` Author: hyukjinkwon <gurwls223@gmail.com> Closes #16013 from HyukjinKwon/SPARK-3359-errors-more.
* [SPARK-18588][SS][KAFKA] Ignore the flaky kafka testShixiong Zhu2016-11-281-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Ignore the flaky test to unblock other PRs while I'm debugging it. ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #16051 from zsxwing/ignore-flaky-kafka-test.
* [SPARK-18530][SS][KAFKA] Change Kafka timestamp column type to TimestampTypeShixiong Zhu2016-11-222-4/+93
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Changed Kafka timestamp column type to TimestampType. ## How was this patch tested? `test("Kafka column types")`. Author: Shixiong Zhu <shixiong@databricks.com> Closes #15969 from zsxwing/SPARK-18530.
* [SPARK-18373][SPARK-18529][SS][KAFKA] Make failOnDataLoss=false work with ↵Shixiong Zhu2016-11-225-95/+523
| | | | | | | | | | | | | | | | | | | | Spark jobs ## What changes were proposed in this pull request? This PR adds `CachedKafkaConsumer.getAndIgnoreLostData` to handle corner cases of `failOnDataLoss=false`. It also resolves [SPARK-18529](https://issues.apache.org/jira/browse/SPARK-18529) after refactoring codes: Timeout will throw a TimeoutException. ## How was this patch tested? Because I cannot find any way to manually control the Kafka server to clean up logs, it's impossible to write unit tests for each corner case. Therefore, I just created `test("stress test for failOnDataLoss=false")` which should cover most of corner cases. I also modified some existing tests to test for both `failOnDataLoss=false` and `failOnDataLoss=true` to make sure it doesn't break existing logic. Author: Shixiong Zhu <shixiong@databricks.com> Closes #15820 from zsxwing/failOnDataLoss.
* [SPARK-18445][BUILD][DOCS] Fix the markdown for `Note:`/`NOTE:`/`Note ↵hyukjinkwon2016-11-194-38/+34
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | that`/`'''Note:'''` across Scala/Java API documentation ## What changes were proposed in this pull request? It seems in Scala/Java, - `Note:` - `NOTE:` - `Note that` - `'''Note:'''` - `note` This PR proposes to fix those to `note` to be consistent. **Before** - Scala ![2016-11-17 6 16 39](https://cloud.githubusercontent.com/assets/6477701/20383180/1a7aed8c-acf2-11e6-9611-5eaf6d52c2e0.png) - Java ![2016-11-17 6 14 41](https://cloud.githubusercontent.com/assets/6477701/20383096/c8ffc680-acf1-11e6-914a-33460bf1401d.png) **After** - Scala ![2016-11-17 6 16 44](https://cloud.githubusercontent.com/assets/6477701/20383167/09940490-acf2-11e6-937a-0d5e1dc2cadf.png) - Java ![2016-11-17 6 13 39](https://cloud.githubusercontent.com/assets/6477701/20383132/e7c2a57e-acf1-11e6-9c47-b849674d4d88.png) ## How was this patch tested? The notes were found via ```bash grep -r "NOTE: " . | \ # Note:|NOTE:|Note that|'''Note:''' grep -v "// NOTE: " | \ # starting with // does not appear in API documentation. grep -E '.scala|.java' | \ # java/scala files grep -v Suite | \ # exclude tests grep -v Test | \ # exclude tests grep -e 'org.apache.spark.api.java' \ # packages appear in API documenation -e 'org.apache.spark.api.java.function' \ # note that this is a regular expression. So actual matches were mostly `org/apache/spark/api/java/functions ...` -e 'org.apache.spark.api.r' \ ... ``` ```bash grep -r "Note that " . | \ # Note:|NOTE:|Note that|'''Note:''' grep -v "// Note that " | \ # starting with // does not appear in API documentation. grep -E '.scala|.java' | \ # java/scala files grep -v Suite | \ # exclude tests grep -v Test | \ # exclude tests grep -e 'org.apache.spark.api.java' \ # packages appear in API documenation -e 'org.apache.spark.api.java.function' \ -e 'org.apache.spark.api.r' \ ... ``` ```bash grep -r "Note: " . | \ # Note:|NOTE:|Note that|'''Note:''' grep -v "// Note: " | \ # starting with // does not appear in API documentation. grep -E '.scala|.java' | \ # java/scala files grep -v Suite | \ # exclude tests grep -v Test | \ # exclude tests grep -e 'org.apache.spark.api.java' \ # packages appear in API documenation -e 'org.apache.spark.api.java.function' \ -e 'org.apache.spark.api.r' \ ... ``` ```bash grep -r "'''Note:'''" . | \ # Note:|NOTE:|Note that|'''Note:''' grep -v "// '''Note:''' " | \ # starting with // does not appear in API documentation. grep -E '.scala|.java' | \ # java/scala files grep -v Suite | \ # exclude tests grep -v Test | \ # exclude tests grep -e 'org.apache.spark.api.java' \ # packages appear in API documenation -e 'org.apache.spark.api.java.function' \ -e 'org.apache.spark.api.r' \ ... ``` And then fixed one by one comparing with API documentation/access modifiers. After that, manually tested via `jekyll build`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #15889 from HyukjinKwon/SPARK-18437.
* [SPARK-18400][STREAMING] NPE when resharding Kinesis StreamSean Owen2016-11-161-19/+23
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Avoid NPE in KinesisRecordProcessor when shutdown happens without successful init ## How was this patch tested? Existing tests Author: Sean Owen <sowen@cloudera.com> Closes #15882 from srowen/SPARK-18400.
* [SPARK-17510][STREAMING][KAFKA] config max rate on a per-partition basiscody koeninger2016-11-145-18/+131
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Allow configuration of max rate on a per-topicpartition basis. ## How was this patch tested? Unit tests. The reporter (Jeff Nadler) said he could test on his workload, so let's wait on that report. Author: cody koeninger <cody@koeninger.org> Closes #15132 from koeninger/SPARK-17510.
* [SPARK-14914][CORE] Fix Resource not closed after using, for unit tests and ↵wm624@hotmail.com2016-11-103-0/+5
| | | | | | | | | | | | | | | | | | | example ## What changes were proposed in this pull request? This is a follow-up work of #15618. Close file source; For any newly created streaming context outside the withContext, explicitly close the context. ## How was this patch tested? Existing unit tests. Author: wm624@hotmail.com <wm624@hotmail.com> Closes #15818 from wangmiao1981/rtest.
* [SPARK-17829][SQL] Stable format for offset logTyson Condie2016-11-094-8/+82
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently we use java serialization for the WAL that stores the offsets contained in each batch. This has two main issues: It can break across spark releases (though this is not the only thing preventing us from upgrading a running query) It is unnecessarily opaque to the user. I'd propose we require offsets to provide a user readable serialization and use that instead. JSON is probably a good option. ## How was this patch tested? Tests were added for KafkaSourceOffset in [KafkaSourceOffsetSuite](external/kafka-0-10-sql/src/test/scala/org/apache/spark/sql/kafka010/KafkaSourceOffsetSuite.scala) and for LongOffset in [OffsetSuite](sql/core/src/test/scala/org/apache/spark/sql/streaming/OffsetSuite.scala) Please review https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark before opening a pull request. zsxwing marmbrus Author: Tyson Condie <tcondie@gmail.com> Author: Tyson Condie <tcondie@clash.local> Closes #15626 from tcondie/spark-8360.
* [SPARK-18283][STRUCTURED STREAMING][KAFKA] Added test to check whether ↵Tathagata Das2016-11-071-0/+24
| | | | | | | | | | | | | | | default starting offset in latest ## What changes were proposed in this pull request? Added test to check whether default starting offset in latest ## How was this patch tested? new unit test Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #15778 from tdas/SPARK-18283.
* [SPARK-18212][SS][KAFKA] increase executor poll timeoutcody koeninger2016-11-032-2/+6
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Increase poll timeout to try and address flaky test ## How was this patch tested? Ran existing unit tests Author: cody koeninger <cody@koeninger.org> Closes #15737 from koeninger/SPARK-18212.
* [SPARK-17813][SQL][KAFKA] Maximum data per triggercody koeninger2016-10-272-27/+151
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? maxOffsetsPerTrigger option for rate limiting, proportionally based on volume of different topicpartitions. ## How was this patch tested? Added unit test Author: cody koeninger <cody@koeninger.org> Closes #15527 from koeninger/SPARK-17813.
* [SPARK-17812][SQL][KAFKA] Assign and specific startingOffsets for structured ↵cody koeninger2016-10-217-45/+369
| | | | | | | | | | | | | | | | | | stream ## What changes were proposed in this pull request? startingOffsets takes specific per-topicpartition offsets as a json argument, usable with any consumer strategy assign with specific topicpartitions as a consumer strategy ## How was this patch tested? Unit tests Author: cody koeninger <cody@koeninger.org> Closes #15504 from koeninger/SPARK-17812.
* [SPARK-17999][KAFKA][SQL] Add getPreferredLocations for KafkaSourceRDDjerryshao2016-10-201-0/+5
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The newly implemented Structured Streaming `KafkaSource` did calculate the preferred locations for each topic partition, but didn't offer this information through RDD's `getPreferredLocations` method. So here propose to add this method in `KafkaSourceRDD`. ## How was this patch tested? Manual verification. Author: jerryshao <sshao@hortonworks.com> Closes #15545 from jerryshao/SPARK-17999.
* [SPARK-17841][STREAMING][KAFKA] drain commitQueuecody koeninger2016-10-181-3/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Actually drain commit queue rather than just iterating it. iterator() on a concurrent linked queue won't remove items from the queue, poll() will. ## How was this patch tested? Unit tests Author: cody koeninger <cody@koeninger.org> Closes #15407 from koeninger/SPARK-17841.
* [SPARK-17731][SQL][STREAMING] Metrics for structured streamingTathagata Das2016-10-131-0/+27
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Metrics are needed for monitoring structured streaming apps. Here is the design doc for implementing the necessary metrics. https://docs.google.com/document/d/1NIdcGuR1B3WIe8t7VxLrt58TJB4DtipWEbj5I_mzJys/edit?usp=sharing Specifically, this PR adds the following public APIs changes. ### New APIs - `StreamingQuery.status` returns a `StreamingQueryStatus` object (renamed from `StreamingQueryInfo`, see later) - `StreamingQueryStatus` has the following important fields - inputRate - Current rate (rows/sec) at which data is being generated by all the sources - processingRate - Current rate (rows/sec) at which the query is processing data from all the sources - ~~outputRate~~ - *Does not work with wholestage codegen* - latency - Current average latency between the data being available in source and the sink writing the corresponding output - sourceStatuses: Array[SourceStatus] - Current statuses of the sources - sinkStatus: SinkStatus - Current status of the sink - triggerStatus - Low-level detailed status of the last completed/currently active trigger - latencies - getOffset, getBatch, full trigger, wal writes - timestamps - trigger start, finish, after getOffset, after getBatch - numRows - input, output, state total/updated rows for aggregations - `SourceStatus` has the following important fields - inputRate - Current rate (rows/sec) at which data is being generated by the source - processingRate - Current rate (rows/sec) at which the query is processing data from the source - triggerStatus - Low-level detailed status of the last completed/currently active trigger - Python API for `StreamingQuery.status()` ### Breaking changes to existing APIs **Existing direct public facing APIs** - Deprecated direct public-facing APIs `StreamingQuery.sourceStatuses` and `StreamingQuery.sinkStatus` in favour of `StreamingQuery.status.sourceStatuses/sinkStatus`. - Branch 2.0 should have it deprecated, master should have it removed. **Existing advanced listener APIs** - `StreamingQueryInfo` renamed to `StreamingQueryStatus` for consistency with `SourceStatus`, `SinkStatus` - Earlier StreamingQueryInfo was used only in the advanced listener API, but now it is used in direct public-facing API (StreamingQuery.status) - Field `queryInfo` in listener events `QueryStarted`, `QueryProgress`, `QueryTerminated` changed have name `queryStatus` and return type `StreamingQueryStatus`. - Field `offsetDesc` in `SourceStatus` was Option[String], converted it to `String`. - For `SourceStatus` and `SinkStatus` made constructor private instead of private[sql] to make them more java-safe. Instead added `private[sql] object SourceStatus/SinkStatus.apply()` which are harder to accidentally use in Java. ## How was this patch tested? Old and new unit tests. - Rate calculation and other internal logic of StreamMetrics tested by StreamMetricsSuite. - New info in statuses returned through StreamingQueryListener is tested in StreamingQueryListenerSuite. - New and old info returned through StreamingQuery.status is tested in StreamingQuerySuite. - Source-specific tests for making sure input rows are counted are is source-specific test suites. - Additional tests to test minor additions in LocalTableScanExec, StateStore, etc. Metrics also manually tested using Ganglia sink Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #15307 from tdas/SPARK-17731.
* [SPARK-17834][SQL] Fetch the earliest offsets manually in KafkaSource ↵Shixiong Zhu2016-10-132-26/+48
| | | | | | | | | | | | | | | | instead of counting on KafkaConsumer ## What changes were proposed in this pull request? Because `KafkaConsumer.poll(0)` may update the partition offsets, this PR just calls `seekToBeginning` to manually set the earliest offsets for the KafkaSource initial offsets. ## How was this patch tested? Existing tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #15397 from zsxwing/SPARK-17834.
* [SPARK-17782][STREAMING][KAFKA] alternative eliminate race condition of poll ↵cody koeninger2016-10-123-7/+32
| | | | | | | | | | | | twice ## What changes were proposed in this pull request? Alternative approach to https://github.com/apache/spark/pull/15387 Author: cody koeninger <cody@koeninger.org> Closes #15401 from koeninger/SPARK-17782-alt.
* [SPARK-17346][SQL][TESTS] Fix the flaky topic deletion in KafkaSourceStressSuiteShixiong Zhu2016-10-111-8/+1
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? A follow up Pr for SPARK-17346 to fix flaky `org.apache.spark.sql.kafka010.KafkaSourceStressSuite`. Test log: https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.4/1855/testReport/junit/org.apache.spark.sql.kafka010/KafkaSourceStressSuite/_It_is_not_a_test_/ Looks like deleting the Kafka internal topic `__consumer_offsets` is flaky. This PR just simply ignores internal topics. ## How was this patch tested? Existing tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #15384 from zsxwing/SPARK-17346-flaky-test.
* [SPARK-17803][TESTS] Upgrade docker-client dependencyChristian Kadner2016-10-061-0/+1
| | | | | | | | | | | | | | | | | | | | | | | | [SPARK-17803: Docker integration tests don't run with "Docker for Mac"](https://issues.apache.org/jira/browse/SPARK-17803) ## What changes were proposed in this pull request? This PR upgrades the [docker-client](https://mvnrepository.com/artifact/com.spotify/docker-client) dependency from [3.6.6](https://mvnrepository.com/artifact/com.spotify/docker-client/3.6.6) to [5.0.2](https://mvnrepository.com/artifact/com.spotify/docker-client/5.0.2) to enable _Docker for Mac_ users to run the `docker-integration-tests` out of the box. The very latest docker-client version is [6.0.0](https://mvnrepository.com/artifact/com.spotify/docker-client/6.0.0) but that has one additional dependency and no usage yet. ## How was this patch tested? The code change was tested on Mac OS X Yosemite with both _Docker Toolbox_ as well as _Docker for Mac_ and on Linux Ubuntu 14.04. ``` $ build/mvn -Pyarn -Phadoop-2.6 -Dhadoop.version=2.6.0 -Phive -Phive-thriftserver -DskipTests clean package $ build/mvn -Pdocker-integration-tests -Pscala-2.11 -pl :spark-docker-integration-tests_2.11 clean compile test ``` Author: Christian Kadner <ckadner@us.ibm.com> Closes #15378 from ckadner/SPARK-17803_Docker_for_Mac.
* [SPARK-17346][SQL][TEST-MAVEN] Generate the sql test jar to fix the maven buildShixiong Zhu2016-10-052-0/+15
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Generate the sql test jar to fix the maven build ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #15368 from zsxwing/sql-test-jar.
* [SPARK-17346][SQL] Add Kafka source for Structured StreamingShixiong Zhu2016-10-0512-0/+1969
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR adds a new project ` external/kafka-0-10-sql` for Structured Streaming Kafka source. It's based on the design doc: https://docs.google.com/document/d/19t2rWe51x7tq2e5AOfrsM9qb8_m7BRuv9fel9i0PqR8/edit?usp=sharing tdas did most of work and part of them was inspired by koeninger's work. ### Introduction The Kafka source is a structured streaming data source to poll data from Kafka. The schema of reading data is as follows: Column | Type ---- | ---- key | binary value | binary topic | string partition | int offset | long timestamp | long timestampType | int The source can deal with deleting topics. However, the user should make sure there is no Spark job processing the data when deleting a topic. ### Configuration The user can use `DataStreamReader.option` to set the following configurations. Kafka Source's options | value | default | meaning ------ | ------- | ------ | ----- startingOffset | ["earliest", "latest"] | "latest" | The start point when a query is started, either "earliest" which is from the earliest offset, or "latest" which is just from the latest offset. Note: This only applies when a new Streaming query is started, and that resuming will always pick up from where the query left off. failOnDataLost | [true, false] | true | Whether to fail the query when it's possible that data is lost (e.g., topics are deleted, or offsets are out of range). This may be a false alarm. You can disable it when it doesn't work as you expected. subscribe | A comma-separated list of topics | (none) | The topic list to subscribe. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source. subscribePattern | Java regex string | (none) | The pattern used to subscribe the topic. Only one of "subscribe" and "subscribeParttern" options can be specified for Kafka source. kafka.consumer.poll.timeoutMs | long | 512 | The timeout in milliseconds to poll data from Kafka in executors fetchOffset.numRetries | int | 3 | Number of times to retry before giving up fatch Kafka latest offsets. fetchOffset.retryIntervalMs | long | 10 | milliseconds to wait before retrying to fetch Kafka offsets Kafka's own configurations can be set via `DataStreamReader.option` with `kafka.` prefix, e.g, `stream.option("kafka.bootstrap.servers", "host:port")` ### Usage * Subscribe to 1 topic ```Scala spark .readStream .format("kafka") .option("kafka.bootstrap.servers", "host:port") .option("subscribe", "topic1") .load() ``` * Subscribe to multiple topics ```Scala spark .readStream .format("kafka") .option("kafka.bootstrap.servers", "host:port") .option("subscribe", "topic1,topic2") .load() ``` * Subscribe to a pattern ```Scala spark .readStream .format("kafka") .option("kafka.bootstrap.servers", "host:port") .option("subscribePattern", "topic.*") .load() ``` ## How was this patch tested? The new unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Author: Tathagata Das <tathagata.das1565@gmail.com> Author: Shixiong Zhu <zsxwing@gmail.com> Author: cody koeninger <cody@koeninger.org> Closes #15102 from zsxwing/kafka-source.
* [SPARK-17418] Prevent kinesis-asl-assembly artifacts from being publishedJosh Rosen2016-09-211-0/+15
| | | | | | | | | | This patch updates the `kinesis-asl-assembly` build to prevent that module from being published as part of Maven releases and snapshot builds. The `kinesis-asl-assembly` includes classes from the Kinesis Client Library (KCL) and Kinesis Producer Library (KPL), both of which are licensed under the Amazon Software License and are therefore prohibited from being distributed in Apache releases. Author: Josh Rosen <joshrosen@databricks.com> Closes #15167 from JoshRosen/stop-publishing-kinesis-assembly.
* [SPARK-17473][SQL] fixing docker integration tests error due to different ↵sureshthalamati2016-09-191-68/+0
| | | | | | | | | | | | | | | versions of jars. ## What changes were proposed in this pull request? Docker tests are using older version of jersey jars (1.19), which was used in older releases of spark. In 2.0 releases Spark was upgraded to use 2.x verison of Jersey. After upgrade to new versions, docker tests are failing with AbstractMethodError. Now that spark is upgraded to 2.x jersey version, using of shaded docker jars may not be required any more. Removed the exclusions/overrides of jersey related classes from pom file, and changed the docker-client to use regular jar instead of shaded one. ## How was this patch tested? Tested using existing docker-integration-tests Author: sureshthalamati <suresh.thalamati@gmail.com> Closes #15114 from sureshthalamati/docker_testfix-spark-17473.
* [SPARK-17534][TESTS] Increase timeouts for DirectKafkaStreamSuite testsAdam Roberts2016-09-161-4/+4
| | | | | | | | | | | | | | | | **## What changes were proposed in this pull request?** There are two tests in this suite that are particularly flaky on the following hardware: 2x Intel(R) Xeon(R) CPU E5-2697 v2 2.70GHz and 16 GB of RAM, 1 TB HDD This simple PR increases the timeout times and batch duration so they can reliably pass **## How was this patch tested?** Existing unit tests with the two core box where I was seeing the failures often Author: Adam Roberts <aroberts@uk.ibm.com> Closes #15094 from a-roberts/patch-6.
* [SPARK-17359][SQL][MLLIB] Use ArrayBuffer.+=(A) instead of ↵Liwei Lin2016-09-071-11/+11
| | | | | | | | | | | | | | | | ArrayBuffer.append(A) in performance critical paths ## What changes were proposed in this pull request? We should generally use `ArrayBuffer.+=(A)` rather than `ArrayBuffer.append(A)`, because `append(A)` would involve extra boxing / unboxing. ## How was this patch tested? N/A Author: Liwei Lin <lwlin7@gmail.com> Closes #14914 from lw-lin/append_to_plus_eq_v2.
* [SPARK-17229][SQL] PostgresDialect shouldn't widen float and short types ↵Josh Rosen2016-08-251-4/+18
| | | | | | | | | | | | | | | | | | during reads ## What changes were proposed in this pull request? When reading float4 and smallint columns from PostgreSQL, Spark's `PostgresDialect` widens these types to Decimal and Integer rather than using the narrower Float and Short types. According to https://www.postgresql.org/docs/7.1/static/datatype.html#DATATYPE-TABLE, Postgres maps the `smallint` type to a signed two-byte integer and the `real` / `float4` types to single precision floating point numbers. This patch fixes this by adding more special-cases to `getCatalystType`, similar to what was done for the Derby JDBC dialect. I also fixed a similar problem in the write path which causes Spark to create integer columns in Postgres for what should have been ShortType columns. ## How was this patch tested? New test cases in `PostgresIntegrationSuite` (which I ran manually because Jenkins can't run it right now). Author: Josh Rosen <joshrosen@databricks.com> Closes #14796 from JoshRosen/postgres-jdbc-type-fixes.
* [SPARK-17023][BUILD] Upgrade to Kafka 0.10.0.1 releaseLuciano Resende2016-08-131-1/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? Update Kafka streaming connector to use Kafka 0.10.0.1 release ## How was this patch tested? Tested via Spark unit and integration tests Author: Luciano Resende <lresende@apache.org> Closes #14606 from lresende/kafka-upgrade.
* [SPARK-16950] [PYSPARK] fromOffsets parameter support in ↵Mariusz Strzelecki2016-08-091-4/+4
| | | | | | | | | | | | | | | | | | KafkaUtils.createDirectStream for python3 ## What changes were proposed in this pull request? Ability to use KafkaUtils.createDirectStream with starting offsets in python 3 by using java.lang.Number instead of Long during param mapping in scala helper. This allows py4j to pass Integer or Long to the map and resolves ClassCastException problems. ## How was this patch tested? unit tests jerryshao - could you please look at this PR? Author: Mariusz Strzelecki <mariusz.strzelecki@allegrogroup.com> Closes #14540 from szczeles/kafka_pyspark.
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