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…sianMixture. ## What changes were proposed in this pull request? #14551 fixed off-by-one bug in ```randomizeInPlace``` and some test failure caused by this fix. But for SparkR ```spark.gaussianMixture``` test case, the fix is inappropriate. It only changed the output result of native R which should be compared by SparkR, however, it did not change the R code in annotation which is used for reproducing the result in native R. It will confuse users who can not reproduce the same result in native R. This PR sends a more robust test case which can produce same result between SparkR and native R. ## How was this patch tested? Unit test update. Author: Yanbo Liang <[email protected]> Closes #14730 from yanboliang/spark-16961-followup.
… SSL
## What changes were proposed in this pull request?
`spark.ssl.enabled`=true, but failing to set `spark.ssl.protocol` will fail and throw meaningless exception. `spark.ssl.protocol` is required when `spark.ssl.enabled`.
Improvement: require `spark.ssl.protocol` when initializing SSLContext, otherwise throws an exception to indicate that.
Remove the OrElse("default").
Document this requirement in configure.md
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Manual tests:
Build document and check document
Configure `spark.ssl.enabled` only, it throws exception below:
6/08/16 16:04:37 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(mwang); groups with view permissions: Set(); users with modify permissions: Set(mwang); groups with modify permissions: Set()
Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: spark.ssl.protocol is required when enabling SSL connections.
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:285)
at org.apache.spark.deploy.master.Master$.startRpcEnvAndEndpoint(Master.scala:1026)
at org.apache.spark.deploy.master.Master$.main(Master.scala:1011)
at org.apache.spark.deploy.master.Master.main(Master.scala)
Configure `spark.ssl.protocol` and `spark.ssl.protocol`
It works fine.
Author: [email protected] <[email protected]>
Closes #14674 from wangmiao1981/ssl.
## What changes were proposed in this pull request? Ignore temp files generated by `check-cran.sh`. Author: Xiangrui Meng <[email protected]> Closes #14740 from mengxr/R-gitignore.
…ULL) OVER` correctly
## What changes were proposed in this pull request?
Currently, `NullPropagation` optimizer replaces `COUNT` on null literals in a bottom-up fashion. During that, `WindowExpression` is not covered properly. This PR adds the missing propagation logic.
**Before**
```scala
scala> sql("SELECT COUNT(1 + NULL) OVER ()").show
java.lang.UnsupportedOperationException: Cannot evaluate expression: cast(0 as bigint) windowspecdefinition(ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)
```
**After**
```scala
scala> sql("SELECT COUNT(1 + NULL) OVER ()").show
+----------------------------------------------------------------------------------------------+
|count((1 + CAST(NULL AS INT))) OVER (ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)|
+----------------------------------------------------------------------------------------------+
| 0|
+----------------------------------------------------------------------------------------------+
```
## How was this patch tested?
Pass the Jenkins test with a new test case.
Author: Dongjoon Hyun <[email protected]>
Closes #14689 from dongjoon-hyun/SPARK-17098.
…rnalCatalog ## What changes were proposed in this pull request? Spark SQL doesn't have its own meta store yet, and use hive's currently. However, hive's meta store has some limitations(e.g. columns can't be too many, not case-preserving, bad decimal type support, etc.), so we have some hacks to successfully store data source table metadata into hive meta store, i.e. put all the information in table properties. This PR moves these hacks to `HiveExternalCatalog`, tries to isolate hive specific logic in one place. changes overview: 1. **before this PR**: we need to put metadata(schema, partition columns, etc.) of data source tables to table properties before saving it to external catalog, even the external catalog doesn't use hive metastore(e.g. `InMemoryCatalog`) **after this PR**: the table properties tricks are only in `HiveExternalCatalog`, the caller side doesn't need to take care of it anymore. 2. **before this PR**: because the table properties tricks are done outside of external catalog, so we also need to revert these tricks when we read the table metadata from external catalog and use it. e.g. in `DescribeTableCommand` we will read schema and partition columns from table properties. **after this PR**: The table metadata read from external catalog is exactly the same with what we saved to it. bonus: now we can create data source table using `SessionCatalog`, if schema is specified. breaks: `schemaStringLengthThreshold` is not configurable anymore. `hive.default.rcfile.serde` is not configurable anymore. ## How was this patch tested? existing tests. Author: Wenchen Fan <[email protected]> Closes #14155 from cloud-fan/catalog-table.
## # What changes were proposed in this pull request? From the spark of version 2.0.0 , when MemoryMode.OFF_HEAP is set , whether the architecture supports unaligned access or not is checked. If the check doesn't pass, exception is raised. We know that AArch64 also supports unaligned access , but now only i386, x86, amd64, and X86_64 are included. I think we should include aarch64 when performing the check. ## How was this patch tested? Unit test suite Author: Richael <[email protected]> Closes #14700 from yimuxi/zym_change_unsafe.
## What changes were proposed in this pull request? (Please fill in changes proposed in this fix) This is the document for previous JDBC Writer options. ## How was this patch tested? (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) Unit test has been added in previous PR. (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: GraceH <[email protected]> Closes #14683 from GraceH/jdbc_options.
## What changes were proposed in this pull request? In 2.0, we change the threshold of splitting expressions from 16K to 64K, which cause very bad performance on wide table, because the generated method can't be JIT compiled by default (above the limit of 8K bytecode). This PR will decrease it to 1K, based on the benchmark results for a wide table with 400 columns of LongType. It also fix a bug around splitting expression in whole-stage codegen (it should not split them). ## How was this patch tested? Added benchmark suite. Author: Davies Liu <[email protected]> Closes #14692 from davies/split_exprs.
…PPORTED OPERATIONS] Changes in Spark Stuctured Streaming doc in this link https://spark.apache.org/docs/2.0.0/structured-streaming-programming-guide.html#unsupported-operations Author: Jagadeesan <[email protected]> Closes #14715 from jagadeesanas2/SPARK-17085.
## What changes were proposed in this pull request? Add missing `numFeatures` and `numClasses` to the wrapped Java models in PySpark ML pipelines. Also tag `DecisionTreeClassificationModel` as Expiremental to match Scala doc. ## How was this patch tested? Extended doctests Author: Holden Karau <[email protected]> Closes #12889 from holdenk/SPARK-15113-add-missing-numFeatures-numClasses.
## What changes were proposed in this pull request? This PR tries to fix the scheme of local cache folder in Windows. The name of the environment variable should be `LOCALAPPDATA` rather than `%LOCALAPPDATA%`. ## How was this patch tested? Manual test in Windows 7. Author: Junyang Qian <[email protected]> Closes #14743 from junyangq/SPARKR-FixWindowsInstall.
## What changes were proposed in this pull request? Collect GC discussion in one section, and documenting findings about G1 GC heap region size. ## How was this patch tested? Jekyll doc build Author: Sean Owen <[email protected]> Closes #14732 from srowen/SPARK-16320.
…ation in test ## What changes were proposed in this pull request? refactor, cleanup, reformat, fix deprecation in test ## How was this patch tested? unit tests, manual tests Author: Felix Cheung <[email protected]> Closes #14735 from felixcheung/rmllibutil.
## What changes were proposed in this pull request? This change adds Xiangrui Meng and Felix Cheung to the maintainers field in the package description. ## How was this patch tested? (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: Shivaram Venkataraman <[email protected]> Closes #14758 from shivaram/sparkr-maintainers.
## What changes were proposed in this pull request? Fix some typos in comments and test hints ## How was this patch tested? N/A. Author: Sean Zhong <[email protected]> Closes #14755 from clockfly/fix_minor_typo.
## What changes were proposed in this pull request? The range operator previously didn't support SQL generation, which made it not possible to use in views. ## How was this patch tested? Unit tests. cc hvanhovell Author: Eric Liang <[email protected]> Closes #14724 from ericl/spark-17162.
## What changes were proposed in this pull request?
replace ``` ` ``` in code doc with `\code{thing}`
remove added `...` for drop(DataFrame)
fix remaining CRAN check warnings
## How was this patch tested?
create doc with knitr
junyangq
Author: Felix Cheung <[email protected]>
Closes #14734 from felixcheung/rdoccleanup.
…in block manager replication ## What changes were proposed in this pull request? This is a straightforward clone of JoshRosen 's original patch. I have follow-up changes to fix block replication for repl-defined classes as well, but those appear to be flaking tests so I'm going to leave that for SPARK-17042 ## How was this patch tested? End-to-end test in ReplSuite (also more tests in DistributedSuite from the original patch). Author: Eric Liang <[email protected]> Closes #14311 from ericl/spark-16550.
## What changes were proposed in this pull request? `CreateHiveTableAsSelectLogicalPlan` is a dead code after refactoring. ## How was this patch tested? N/A Author: gatorsmile <[email protected]> Closes #14707 from gatorsmile/removeCreateHiveTable.
…CodeGen ## What changes were proposed in this pull request? Add expert param support to SharedParamsCodeGen where aggregationDepth a expert param is added. Author: hqzizania <[email protected]> Closes #14738 from hqzizania/SPARK-17090-minor.
## What changes were proposed in this pull request? (Please fill in changes proposed in this fix) ## How was this patch tested? This change adds CRAN documentation checks to be run as a part of `R/run-tests.sh` . As this script is also used by Jenkins this means that we will get documentation checks on every PR going forward. (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: Shivaram Venkataraman <[email protected]> Closes #14759 from shivaram/sparkr-cran-jenkins.
## What changes were proposed in this pull request? This PR marks the abstract class `Collect` as non-deterministic since the results of `CollectList` and `CollectSet` depend on the actual order of input rows. ## How was this patch tested? Existing test cases should be enough. Author: Cheng Lian <[email protected]> Closes #14749 from liancheng/spark-17182-non-deterministic-collect.
## What changes were proposed in this pull request? Update DESCRIPTION ## How was this patch tested? Run install and CRAN tests Author: Felix Cheung <[email protected]> Closes #14764 from felixcheung/rpackagedescription.
…for implementing percentile_approx ## What changes were proposed in this pull request? This is a sub-task of [SPARK-16283](https://issues.apache.org/jira/browse/SPARK-16283) (Implement percentile_approx SQL function), which moves class QuantileSummaries to project catalyst so that it can be reused when implementing aggregation function `percentile_approx`. ## How was this patch tested? This PR only does class relocation, class implementation is not changed. Author: Sean Zhong <[email protected]> Closes #14754 from clockfly/move_QuantileSummaries_to_catalyst.
## What changes were proposed in this pull request? Use `CatalystConf.resolver` consistently for case-sensitivity comparison (removed dups). ## How was this patch tested? Local build. Waiting for Jenkins to ensure clean build and test. Author: Jacek Laskowski <[email protected]> Closes #14771 from jaceklaskowski/17199-catalystconf-resolver.
## What changes were proposed in this pull request? In Latex, it is common to find "}}}" when closing several expressions at once. [SPARK-16822](https://issues.apache.org/jira/browse/SPARK-16822) added Mathjax to render Latex equations in scaladoc. However, when scala doc sees "}}}" or "{{{" it treats it as a special character for code block. This results in some very strange output. Author: Jagadeesan <[email protected]> Closes #14688 from jagadeesanas2/SPARK-17095.
## What changes were proposed in this pull request? Some JDBC driver (for example PostgreSQL) does not use the underlying exception as cause, but have another APIs (getNextException) to access that, so it it's included in the error logging, making us hard to find the root cause, especially in batch mode. This PR will pull out the next exception and add it as cause (if it's different) or suppressed (if there is another different cause). ## How was this patch tested? Can't reproduce this on the default JDBC driver, so did not add a regression test. Author: Davies Liu <[email protected]> Closes #14722 from davies/keep_cause.
…variables ## What changes were proposed in this pull request? The PR removes reference link in the doc for environment variables for common Windows folders. The cran check gave code 503: service unavailable on the original link. ## How was this patch tested? Manual check. Author: Junyang Qian <[email protected]> Closes #14767 from junyangq/SPARKR-RemoveLink.
…Mac in structured streaming programming guides ## What changes were proposed in this pull request? This PR fixes curly quotes (`“` and `”` ) to standard quotes (`"`). This will be a actual problem when users copy and paste the examples. This would not work. This seems only happening in `structured-streaming-programming-guide.md`. ## How was this patch tested? Manually built. This will change some examples to be correctly marked down as below:  to  Author: hyukjinkwon <[email protected]> Closes #14770 from HyukjinKwon/minor-quotes.
## What changes were proposed in this pull request? Fix a typo ## How was this patch tested? no tests Author: Zheng RuiFeng <[email protected]> Closes #14772 from zhengruifeng/minor_numClasses.
…ecause of calculation error ## What changes were proposed in this pull request? In StagePage, executor-computing-time is calculated but calculation error can occur potentially because it's calculated by subtraction of floating numbers. Following capture is an example. <img width="949" alt="capture-timeline" src="https://cloud.githubusercontent.com/assets/4736016/18152359/43f07a28-7030-11e6-8cbd-8e73bf4c4c67.png"> ## How was this patch tested? Manual tests. Author: Kousuke Saruta <[email protected]> Closes #14908 from sarutak/SPARK-17352.
### What changes were proposed in this pull request? Function-related `HiveExternalCatalog` APIs do not have enough verification logics. After the PR, `HiveExternalCatalog` and `InMemoryCatalog` become consistent in the error handling. For example, below is the exception we got when calling `renameFunction`. ``` 15:13:40.369 WARN org.apache.hadoop.hive.metastore.ObjectStore: Failed to get database db1, returning NoSuchObjectException 15:13:40.377 WARN org.apache.hadoop.hive.metastore.ObjectStore: Failed to get database db2, returning NoSuchObjectException 15:13:40.739 ERROR DataNucleus.Datastore.Persist: Update of object "org.apache.hadoop.hive.metastore.model.MFunction205629e9" using statement "UPDATE FUNCS SET FUNC_NAME=? WHERE FUNC_ID=?" failed : org.apache.derby.shared.common.error.DerbySQLIntegrityConstraintViolationException: The statement was aborted because it would have caused a duplicate key value in a unique or primary key constraint or unique index identified by 'UNIQUEFUNCTION' defined on 'FUNCS'. at org.apache.derby.impl.jdbc.SQLExceptionFactory.getSQLException(Unknown Source) at org.apache.derby.impl.jdbc.Util.generateCsSQLException(Unknown Source) at org.apache.derby.impl.jdbc.TransactionResourceImpl.wrapInSQLException(Unknown Source) at org.apache.derby.impl.jdbc.TransactionResourceImpl.handleException(Unknown Source) ``` ### How was this patch tested? Improved the existing test cases to check whether the messages are right. Author: gatorsmile <[email protected]> Closes #14521 from gatorsmile/functionChecking.
…tition doesn't have… ## What changes were proposed in this pull request? Try increase number of partitions to try so we don't revert to all. ## How was this patch tested? Empirically. This is common case optimization. Author: Robert Kruszewski <[email protected]> Closes #14573 from robert3005/robertk/execute-take-backoff.
…y methods
This patch refactors the internals of the JDBC data source in order to allow some of its code to be re-used in an automated comparison testing harness. Here are the key changes:
- Move the JDBC `ResultSetMetadata` to `StructType` conversion logic from `JDBCRDD.resolveTable()` to the `JdbcUtils` object (as a new `getSchema(ResultSet, JdbcDialect)` method), allowing it to be applied on `ResultSet`s that are created elsewhere.
- Move the `ResultSet` to `InternalRow` conversion methods from `JDBCRDD` to `JdbcUtils`:
- It makes sense to move the `JDBCValueGetter` type and `makeGetter` functions here given that their write-path counterparts (`JDBCValueSetter`) are already in `JdbcUtils`.
- Add an internal `resultSetToSparkInternalRows` method which takes a `ResultSet` and schema and returns an `Iterator[InternalRow]`. This effectively extracts the main loop of `JDBCRDD` into its own method.
- Add a public `resultSetToRows` method to `JdbcUtils`, which wraps the minimal machinery around `resultSetToSparkInternalRows` in order to allow it to be called from outside of a Spark job.
- Make `JdbcDialect.get` into a `DeveloperApi` (`JdbcDialect` itself is already a `DeveloperApi`).
Put together, these changes enable the following testing pattern:
```scala
val jdbResultSet: ResultSet = conn.prepareStatement(query).executeQuery()
val resultSchema: StructType = JdbcUtils.getSchema(jdbResultSet, JdbcDialects.get("jdbc:postgresql"))
val jdbcRows: Seq[Row] = JdbcUtils.resultSetToRows(jdbResultSet, schema).toSeq
checkAnswer(sparkResult, jdbcRows) // in a test case
```
Author: Josh Rosen <[email protected]>
Closes #14907 from JoshRosen/modularize-jdbc-internals.
…ext in Spark 2.0 throws "Java.lang.illegalStateException: Cannot call methods on a stopped sparkContext"
## What changes were proposed in this pull request?
Set SparkSession._instantiatedContext as None so that we can recreate SparkSession again.
## How was this patch tested?
Tested manually using the following command in pyspark shell
```
spark.stop()
spark = SparkSession.builder.enableHiveSupport().getOrCreate()
spark.sql("show databases").show()
```
Author: Jeff Zhang <[email protected]>
Closes #14857 from zjffdu/SPARK-17261.
## What changes were proposed in this pull request? Add sparkR.version() API. ``` > sparkR.version() [1] "2.1.0-SNAPSHOT" ``` ## How was this patch tested? manual, unit tests Author: Felix Cheung <[email protected]> Closes #14935 from felixcheung/rsparksessionversion.
…when match fails ## What changes were proposed in this pull request? Doc change - see https://issues.apache.org/jira/browse/SPARK-16324 ## How was this patch tested? manual check Author: Felix Cheung <[email protected]> Closes #14934 from felixcheung/regexpextractdoc.
…ling upgrade The Spark Yarn Shuffle Service doesn't re-initialize the application credentials early enough which causes any other spark executors trying to fetch from that node during a rolling upgrade to fail with "java.lang.NullPointerException: Password cannot be null if SASL is enabled". Right now the spark shuffle service relies on the Yarn nodemanager to re-register the applications, unfortunately this is after we open the port for other executors to connect. If other executors connected before the re-register they get a null pointer exception which isn't a re-tryable exception and cause them to fail pretty quickly. To solve this I added another leveldb file so that it can save and re-initialize all the applications before opening the port for other executors to connect to it. Adding another leveldb was simpler from the code structure point of view. Most of the code changes are moving things to common util class. Patch was tested manually on a Yarn cluster with rolling upgrade was happing while spark job was running. Without the patch I consistently get the NullPointerException, with the patch the job gets a few Connection refused exceptions but the retries kick in and the it succeeds. Author: Thomas Graves <[email protected]> Closes #14718 from tgravescs/SPARK-16711.
## What changes were proposed in this pull request? change since version in doc ## How was this patch tested? manual Author: Felix Cheung <[email protected]> Closes #14939 from felixcheung/rsparkversion2.
…on in DataFrameWriter ## What changes were proposed in this pull request? Some analyzer rules have assumptions on logical plans, optimizer may break these assumption, we should not pass an optimized query plan into QueryExecution (will be analyzed again), otherwise we may some weird bugs. For example, we have a rule for decimal calculation to promote the precision before binary operations, use PromotePrecision as placeholder to indicate that this rule should not apply twice. But a Optimizer rule will remove this placeholder, that break the assumption, then the rule applied twice, cause wrong result. Ideally, we should make all the analyzer rules all idempotent, that may require lots of effort to double checking them one by one (may be not easy). An easier approach could be never feed a optimized plan into Analyzer, this PR fix the case for RunnableComand, they will be optimized, during execution, the passed `query` will also be passed into QueryExecution again. This PR make these `query` not part of the children, so they will not be optimized and analyzed again. Right now, we did not know a logical plan is optimized or not, we could introduce a flag for that, and make sure a optimized logical plan will not be analyzed again. ## How was this patch tested? Added regression tests. Author: Davies Liu <[email protected]> Closes #14797 from davies/fix_writer.
… row groups shouldn't throw an error ## What changes were proposed in this pull request? This patch fixes a bug in the vectorized parquet reader that's caused by re-using the same dictionary column vector while reading consecutive row groups. Specifically, this issue manifests for a certain distribution of dictionary/plain encoded data while we read/populate the underlying bit packed dictionary data into a column-vector based data structure. ## How was this patch tested? Manually tested on datasets provided by the community. Thanks to Chris Perluss and Keith Kraus for their invaluable help in tracking down this issue! Author: Sameer Agarwal <[email protected]> Closes #14941 from sameeragarwal/parquet-exception-2.
## What changes were proposed in this pull request? Require the use of CROSS join syntax in SQL (and a new crossJoin DataFrame API) to specify explicit cartesian products between relations. By cartesian product we mean a join between relations R and S where there is no join condition involving columns from both R and S. If a cartesian product is detected in the absence of an explicit CROSS join, an error must be thrown. Turning on the "spark.sql.crossJoin.enabled" configuration flag will disable this check and allow cartesian products without an explicit CROSS join. The new crossJoin DataFrame API must be used to specify explicit cross joins. The existing join(DataFrame) method will produce a INNER join that will require a subsequent join condition. That is df1.join(df2) is equivalent to select * from df1, df2. ## How was this patch tested? Added cross-join.sql to the SQLQueryTestSuite to test the check for cartesian products. Added a couple of tests to the DataFrameJoinSuite to test the crossJoin API. Modified various other test suites to explicitly specify a cross join where an INNER join or a comma-separated list was previously used. Author: Srinath Shankar <[email protected]> Closes #14866 from srinathshankar/crossjoin.
## What changes were proposed in this pull request? This PR tries to add some more explanation to `sparkR.session`. It also modifies doc for `count` so when grouped in one doc, the description doesn't confuse users. ## How was this patch tested? Manual test.  Author: Junyang Qian <[email protected]> Closes #14942 from junyangq/fixSparkRSessionDoc.
## What changes were proposed in this pull request? fix `MultivariantOnlineSummerizer.numNonZeros` method, return `nnz` array, instead of `weightSum` array ## How was this patch tested? Existing test. Author: WeichenXu <[email protected]> Closes #14923 from WeichenXu123/fix_MultivariantOnlineSummerizer_numNonZeros.
… type ## What changes were proposed in this pull request? We propose to fix the Encoder type in the Dataset example ## How was this patch tested? The PR will be tested with the current unit test cases Author: CodingCat <[email protected]> Closes #14901 from CodingCat/SPARK-17347.
## What changes were proposed in this pull request? was not dropping table `parquet_t3` ## How was this patch tested? tested `LogicalPlanToSQLSuite` locally Author: Sandeep Singh <[email protected]> Closes #13767 from techaddict/minor-8.
## What changes were proposed in this pull request? the `catalogString` for `ArrayType` and `MapType` currently calls the `simpleString` method on its children. This is a problem when the child is a struct, the `struct.simpleString` implementation truncates the number of fields it shows (25 at max). This breaks the generation of a proper `catalogString`, and has shown to cause errors while writing to Hive. This PR fixes this by providing proper `catalogString` implementations for `ArrayData` or `MapData`. ## How was this patch tested? Added testing for `catalogString` to `DataTypeSuite`. Author: Herman van Hovell <[email protected]> Closes #14938 from hvanhovell/SPARK-17335.
## What changes were proposed in this pull request? This PR tries to add Kolmogorov-Smirnov Test wrapper to SparkR. This wrapper implementation only supports one sample test against normal distribution. ## How was this patch tested? R unit test. Author: Junyang Qian <[email protected]> Closes #14881 from junyangq/SPARK-17315.
(Please fill in changes proposed in this fix)
./bin/sparkR
Launching java with spark-submit command /Users/mwang/spark_ws_0904/bin/spark-submit "sparkr-shell" /var/folders/s_/83b0sgvj2kl2kwq4stvft_pm0000gn/T//RtmpQxJGiZ/backend_porte9474603ed1e
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel).
> sc.setLogLevel("INFO")
Error: could not find function "sc.setLogLevel"
sc.setLogLevel doesn't exist.
R has a function setLogLevel.
I rename the setLogLevel function to sc.setLogLevel.
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Change unit test. Run unit tests.
Manually tested it in sparkR shell.
Author: [email protected] <[email protected]>
Closes #14433 from wangmiao1981/sc.
…eTable ### What changes were proposed in this pull request? This is another step to get rid of HiveClient from `HiveSessionState`. All the metastore interactions should be through `ExternalCatalog` interface. However, the existing implementation of `InsertIntoHiveTable ` still requires Hive clients. This PR is to remove HiveClient by moving the metastore interactions into `ExternalCatalog`. ### How was this patch tested? Existing test cases Author: gatorsmile <[email protected]> Closes #14888 from gatorsmile/removeClientFromInsertIntoHiveTable.
…atch on boolean value by if/else block. ## What changes were proposed in this pull request? Improved the code quality of spark by replacing all pattern match on boolean value by if/else block. ## How was this patch tested? By running the tests Author: Shivansh <[email protected]> Closes #14873 from shiv4nsh/SPARK-17308.
…onal long seeds in all cases ## What changes were proposed in this pull request? Related to #14524 -- just the 'fix' rather than a behavior change. - PythonMLlibAPI methods that take a seed now always take a `java.lang.Long` consistently, allowing the Python API to specify "no seed" - .mllib's Word2VecModel seemed to be an odd man out in .mllib in that it picked its own random seed. Instead it defaults to None, meaning, letting the Scala implementation pick a seed - BisectingKMeansModel arguably should not hard-code a seed for consistency with .mllib, I think. However I left it. ## How was this patch tested? Existing tests Author: Sean Owen <[email protected]> Closes #14826 from srowen/SPARK-16832.2.
## What changes were proposed in this pull request? Since we have updated breeze version to 0.12, we should remove work around for bug of breeze sparse matrix in v0.11. I checked all mllib code and found this is the only work around for breeze 0.11. ## How was this patch tested? Existing tests. Author: Yanbo Liang <[email protected]> Closes #14953 from yanboliang/matrices.
…rce Table Using Overwrite Mode
### What changes were proposed in this pull request?
When we trying to read a table and then write to the same table using the `Overwrite` save mode, we got a very confusing error message:
For example,
```Scala
Seq((1, 2)).toDF("i", "j").write.saveAsTable("tab1")
table("tab1").write.mode(SaveMode.Overwrite).saveAsTable("tab1")
```
```
Job aborted.
org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply$mcV$sp
...
Caused by: org.apache.spark.SparkException: Task failed while writing rows
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:266)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(InsertIntoHadoopFsRelationCommand.scala:143)
at org.apache.spark.sql.execution.datasources
```
After the PR, we will issue an `AnalysisException`:
```
Cannot overwrite table `tab1` that is also being read from
```
### How was this patch tested?
Added test cases.
Author: gatorsmile <[email protected]>
Closes #14954 from gatorsmile/ctasQueryAnalyze.
…me after RENAME TO ## What changes were proposed in this pull request? It's really weird that we allow users to specify database in both from table name and to table name in `ALTER TABLE RENAME TO`, while logically we can't support rename a table to a different database. Both postgres and MySQL disallow this syntax, it's reasonable to follow them and simply our code. ## How was this patch tested? new test in `DDLCommandSuite` Author: Wenchen Fan <[email protected]> Closes #14955 from cloud-fan/rename.
…ing into/loading from metastore
## What changes were proposed in this pull request?
1. Support generation table-level statistics for
- hive tables in HiveExternalCatalog
- data source tables in HiveExternalCatalog
- data source tables in InMemoryCatalog.
2. Add a property "catalogStats" in CatalogTable to hold statistics in Spark side.
3. Put logics of statistics transformation between Spark and Hive in HiveClientImpl.
4. Extend Statistics class by adding rowCount (will add estimatedSize when we have column stats).
## How was this patch tested?
add unit tests
Author: wangzhenhua <[email protected]>
Author: Zhenhua Wang <[email protected]>
Closes #14712 from wzhfy/tableStats.
…F execution ## What changes were proposed in this pull request? If `ScalaUDF` throws exceptions during executing user code, sometimes it's hard for users to figure out what's wrong, especially when they use Spark shell. An example ``` org.apache.spark.SparkException: Job aborted due to stage failure: Task 12 in stage 325.0 failed 4 times, most recent failure: Lost task 12.3 in stage 325.0 (TID 35622, 10.0.207.202): java.lang.NullPointerException at line8414e872fb8b42aba390efc153d1611a12.$read$$iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:40) at line8414e872fb8b42aba390efc153d1611a12.$read$$iwC$$iwC$$iwC$$iwC$$anonfun$2.apply(<console>:40) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) ... ``` We should catch these exceptions and rethrow them with better error message, to say that the exception is happened in scala udf. This PR also does some clean up for `ScalaUDF` and add a unit test suite for it. ## How was this patch tested? the new test suite Author: Wenchen Fan <[email protected]> Closes #14850 from cloud-fan/npe.
…e to missing otherCopyArgs ## What changes were proposed in this pull request? `TreeNode.toJSON` requires a subclass to explicitly override otherCopyArgs to include currying construction arguments, otherwise it reports AssertException telling that the construction argument values' count doesn't match the construction argument names' count. For class `MetastoreRelation`, it has a currying construction parameter `client: HiveClient`, but Spark forgets to add it to the list of otherCopyArgs. ## How was this patch tested? Unit tests. Author: Sean Zhong <[email protected]> Closes #14928 from clockfly/metastore_relation_toJSON.
…beelines
## What changes were proposed in this pull request?
Cached table(parquet/orc) couldn't be shard between beelines, because the `sameResult` method used by `CacheManager` always return false(`sparkSession` are different) when compare two `HadoopFsRelation` in different beelines. So we make `sparkSession` a curry parameter.
## How was this patch tested?
Beeline1
```
1: jdbc:hive2://localhost:10000> CACHE TABLE src_pqt;
+---------+--+
| Result |
+---------+--+
+---------+--+
No rows selected (5.143 seconds)
1: jdbc:hive2://localhost:10000> EXPLAIN SELECT * FROM src_pqt;
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
| plan |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
| == Physical Plan ==
InMemoryTableScan [key#49, value#50]
+- InMemoryRelation [key#49, value#50], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas), `src_pqt`
+- *FileScan parquet default.src_pqt[key#0,value#1] Batched: true, Format: ParquetFormat, InputPaths: hdfs://199.0.0.1:9000/qiyadong/src_pqt, PartitionFilters: [], PushedFilters: [], ReadSchema: struct<key:int,value:string> |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
```
Beeline2
```
0: jdbc:hive2://localhost:10000> EXPLAIN SELECT * FROM src_pqt;
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
| plan |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
| == Physical Plan ==
InMemoryTableScan [key#68, value#69]
+- InMemoryRelation [key#68, value#69], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas), `src_pqt`
+- *FileScan parquet default.src_pqt[key#0,value#1] Batched: true, Format: ParquetFormat, InputPaths: hdfs://199.0.0.1:9000/qiyadong/src_pqt, PartitionFilters: [], PushedFilters: [], ReadSchema: struct<key:int,value:string> |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--+
```
Author: Yadong Qi <[email protected]>
Closes #14913 from watermen/SPARK-17358.
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