## What changes were proposed in this pull request?
In the PR, I propose to replace Scala parallel collections by new methods `parmap()`. The methods use futures to transform a sequential collection by applying a lambda function to each element in parallel. The result of `parmap` is another regular (sequential) collection.
The proposed `parmap` method aims to solve the problem of impossibility to interrupt parallel Scala collection. This possibility is needed for reliable task preemption.
## How was this patch tested?
A test was added to `ThreadUtilsSuite`
Closes#21913 from MaxGekk/par-map.
Authored-by: Maxim Gekk <maxim.gekk@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
## What changes were proposed in this pull request?
Using struct types in subqueries with the `IN` clause can generate invalid plans in `RewritePredicateSubquery`. Indeed, we are not handling clearly the cases when the outer value is a struct or the output of the inner subquery is a struct.
The PR aims to make Spark's behavior the same as the one of the other RDBMS - namely Oracle and Postgres behavior were checked. So we consider valid only queries having the same number of fields in the outer value and in the subquery. This means that:
- `(a, b) IN (select c, d from ...)` is a valid query;
- `(a, b) IN (select (c, d) from ...)` throws an AnalysisException, as in the subquery we have only one field of type struct while in the outer value we have 2 fields;
- `a IN (select (c, d) from ...)` - where `a` is a struct - is a valid query.
## How was this patch tested?
Added UT
Closes#21403 from mgaido91/SPARK-24313.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
## What changes were proposed in this pull request?
Implement BarrierTaskContext.barrier(), to support global sync between all the tasks in a barrier stage.
The function set a global barrier and waits until all tasks in this stage hit this barrier. Similar to MPI_Barrier function in MPI, the barrier() function call blocks until all tasks in the same stage have reached this routine. The global sync shall finish immediately once all tasks in the same barrier stage reaches the same barrier.
This PR implements BarrierTaskContext.barrier() based on netty-based RPC client, introduces new `BarrierCoordinator` and new `BarrierCoordinatorMessage`, and new config to handle timeout issue.
## How was this patch tested?
Add `BarrierTaskContextSuite` to test `BarrierTaskContext.barrier()`
Closes#21898 from jiangxb1987/taskcontext.barrier.
Authored-by: Xingbo Jiang <xingbo.jiang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
## What changes were proposed in this pull request?
Like Uuid in SPARK-24896, Rand and Randn expressions now produce the same results for each execution in streaming query. It doesn't make too much sense for streaming queries. We should make them produce different results as Uuid.
In this change, similar to Uuid, we assign new random seeds to Rand/Randn when returning optimized plan from `IncrementalExecution`.
Note: Different to Uuid, Rand/Randn can be created with initial seed. Because we replace this initial seed at `IncrementalExecution`, it doesn't use the initial seed anymore. For now it seems to me not a big issue for streaming query. But need to confirm with others. cc zsxwing cloud-fan
## How was this patch tested?
Added test.
Closes#21980 from viirya/SPARK-25010.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
## What changes were proposed in this pull request?
This PR refactors `ArrayUnion` based on [this suggestion](https://github.com/apache/spark/pull/21103#discussion_r205668821).
1. Generate optimized code for all of the primitive types except `boolean`
1. Generate code using `ArrayBuilder` or `ArrayBuffer`
1. Leave only a generic path in the interpreted path
## How was this patch tested?
Existing tests
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#21937 from kiszk/SPARK-23914-follow.
## What changes were proposed in this pull request?
In [Linux community](https://git.wiki.kernel.org/index.php/CommitMessageConventions), `Co-authored-by` and `Signed-off-by` git trailer have been used for awhile.
Until recently, Github adopted `Co-authored-by` to include the work of co-authors in the profile contributions graph and the repository's statistics. It's a convention for recognizing multiple authors, and can encourage people to collaborate in OSS communities.
Git provides a command line tools to read the metadata to know who commits the code to upstream, but it's not as easy as having `Signed-off-by` as part of the message so developers can find who is the relevant committers who can help with certain part of the codebase easier.
For a single author PR, I purpose to use `Authored-by` and `Signed-off-by`, so the message will look like
```
Authored-by: Author's name <authorexample.com>
Signed-off-by: Committer's name <committerexample.com>
```
For a multi-author PR, I purpose to use `Lead-authored-by:` and `Co-authored-by:` for the lead author and co-authors. The message will look like
```
Lead-authored-by: Lead Author's name <leadauthorexample.com>
Co-authored-by: CoAuthor's name <coauthorexample.com>
Signed-off-by: Committer's name <committerexample.com>
```
It's also useful to include `Reviewed-by:` to give credits to the people who participate on the code reviewing. We can add this in the next iteration.
Closes#21991 from dbtsai/script.
Lead-authored-by: DB Tsai <d_tsai@apple.com>
Co-authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Co-authored-by: Brian Lindblom <blindblom@apple.com>
Co-authored-by: hyukjinkwon <gurwls223@apache.org>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
Currently the Structured Streaming sources and sinks does not have a way to report custom metrics. Providing an option to report custom metrics and making it available via Streaming Query progress can enable sources and sinks to report custom progress information (E.g. the lag metrics for Kafka source).
Similar metrics can be reported for Sinks as well, but would like to get initial feedback before proceeding further.
## How was this patch tested?
New and existing unit tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Closes#21721 from arunmahadevan/SPARK-24748.
Authored-by: Arun Mahadevan <arunm@apache.org>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
The patch adds metrics regarding state and watermark to dropwizard metrics, so that watermark and state rows/size can be tracked via time-series manner.
## How was this patch tested?
Manually tested with CSV metric sink.
Closes#21622 from HeartSaVioR/SPARK-24637.
Authored-by: Jungtaek Lim <kabhwan@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
Fix a grammatical error in the comment of SortShuffleManager.
## How was this patch tested?
N/A
Closes#21956 from deshanxiao/master.
Authored-by: deshanxiao <42019462+deshanxiao@users.noreply.github.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
The PR refactors the aggregate expressions which were not using DSL in order to simplify them.
## How was this patch tested?
NA
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#21970 from mgaido91/SPARK-24996.
## What changes were proposed in this pull request?
This PR fixes a comparison of `ExprValue.isNull` with `String`. `ExprValue.isNull` should be compared with `LiteralTrue` or `LiteralFalse`.
This causes the following compilation error using scala-2.12 with sbt. In addition, this code may also generate incorrect code in Spark 2.3.
```
/home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:94: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely always compare unequal
[error] [warn] if (eval.isNull != "true") {
[error] [warn]
[error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:126: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely never compare equal
[error] [warn] if (eval.isNull == "true") {
[error] [warn]
[error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala:133: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely never compare equal
[error] [warn] if (eval.isNull == "true") {
[error] [warn]
[error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/GenerateUnsafeProjection.scala:90: org.apache.spark.sql.catalyst.expressions.codegen.ExprValue and String are unrelated: they will most likely never compare equal
[error] [warn] if (inputs.map(_.isNull).forall(_ == "false")) {
[error] [warn]
```
## How was this patch tested?
Existing UTs
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#22012 from kiszk/SPARK-25036a.
## What changes were proposed in this pull request?
Currently, debug package has a implicit class "DebugQuery" which matches Dataset to provide debug features on Dataset class. It doesn't work with structured streaming: it requires query is already started, and the information can be retrieved from StreamingQuery, not Dataset. I guess that's why "explain" had to be placed to StreamingQuery whereas it already exists on Dataset.
This patch adds a new implicit class "DebugStreamQuery" which matches StreamingQuery to provide similar debug features on StreamingQuery class.
## How was this patch tested?
Added relevant unit tests.
Author: Jungtaek Lim <kabhwan@gmail.com>
Closes#21222 from HeartSaVioR/SPARK-24161.
## What changes were proposed in this pull request?
In `SparkHadoopUtil. checkAccessPermission`, we consider only basic permissions in order to check wether a user can access a file or not. This is not a complete check, as it ignores ACLs and other policies a file system may apply in its internal. So this can result in returning wrongly that a user cannot access a file (despite he actually can).
The PR proposes to delegate to the filesystem the check whether a file is accessible or not, in order to return the right result. A caching layer is added for performance reasons.
## How was this patch tested?
modified UTs
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#21895 from mgaido91/SPARK-24948.
## What changes were proposed in this pull request?
During upgrading Apache ORC to 1.5.2 ([SPARK-24576](https://issues.apache.org/jira/browse/SPARK-24576)), `sql/core` module overrides the exclusion rules of parent pom file and it causes published `spark-sql_2.1X` artifacts have incomplete exclusion rules ([SPARK-25019](https://issues.apache.org/jira/browse/SPARK-25019)). This PR fixes it by moving the newly added exclusion rule to the parent pom. This also fixes the sbt build hack introduced at that time.
## How was this patch tested?
Pass the existing dependency check and the tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes#22003 from dongjoon-hyun/SPARK-25019.
**Description: [SPARK-24992](https://issues.apache.org/jira/browse/SPARK-24992)**
Utils.getLocalDir is used to get path of a temporary directory. However, it always returns the the same directory, which is the first element in the array localRootDirs. When running on YARN, this might causes the case that we always write to one disk, which makes it busy while other disks are free. We should randomize the selection to spread out the loads.
**What changes were proposed in this pull request?**
This PR randomized the selection of local directory inside the method Utils.getLocalDir. This change affects the Utils.fetchFile method since it based on the fact that Utils.getLocalDir always return the same directory to cache file. Therefore, a new variable cachedLocalDir is used to cache the first localDirectory that it gets from Utils.getLocalDir. Also, when getting the configured local directories (inside Utils. getConfiguredLocalDirs), in case we are in yarn mode, the array of directories are also randomized before return.
Author: Hieu Huynh <“Hieu.huynh@oath.com”>
Closes#21953 from hthuynh2/SPARK_24992.
## What changes were proposed in this pull request?
The PR adds the SQL function `array_intersect`. The behavior of the function is based on Presto's one.
This function returns returns an array of the elements in the intersection of array1 and array2.
Note: The order of elements in the result is not defined.
## How was this patch tested?
Added UTs
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#21102 from kiszk/SPARK-23913.
**Description**
The issue is described in [SPARK-24981](https://issues.apache.org/jira/browse/SPARK-24981).
**How does this PR fix the issue?**
This PR catch the Exception that is thrown while the Sparkcontext.stop() is running (when it is called by the ShutdownHookManager).
**How was this patch tested?**
I manually tested it by adding delay (60s) inside the stop(). This make the shutdownHookManger interrupt the thread that is running stop(). The Interrupted Exception was catched and the job succeed.
Author: Hieu Huynh <“Hieu.huynh@oath.com”>
Author: Hieu Tri Huynh <hthieu96@gmail.com>
Closes#21936 from hthuynh2/SPARK_24981.
## What changes were proposed in this pull request?
Having the default value of isAll in the logical plan nodes INTERSECT/EXCEPT could introduce bugs when the callers are not aware of it. This PR removes the default value and makes caller explicitly specify them.
## How was this patch tested?
This is a refactoring change. Existing tests test the functionality already.
Author: Dilip Biswal <dbiswal@us.ibm.com>
Closes#22000 from dilipbiswal/SPARK-25025.
## What changes were proposed in this pull request?
Follow up to fix an unmerged review comment.
## How was this patch tested?
Unit test ResolveHintsSuite.
Author: John Zhuge <jzhuge@apache.org>
Closes#21998 from jzhuge/SPARK-24940.
## What changes were proposed in this pull request?
The `dropFieldIfAllNull` parameter of the `json` method wasn't set as an option. This PR fixes that.
## How was this patch tested?
I added a test to `sql/test.py`
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#22002 from MaxGekk/drop-field-if-all-null.
## What changes were proposed in this pull request?
A follow up of #21118
Since we use `InternalRow` in the read API of data source v2, we should do the same thing for the write API.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#21948 from cloud-fan/row-write.
## What changes were proposed in this pull request?
This pr adds `aggregate` function which applies a binary operator to an initial state and all elements in the array, and reduces this to a single state. The final state is converted into the final result by applying a finish function.
```sql
> SELECT aggregate(array(1, 2, 3), (acc, x) -> acc + x);
6
> SELECT aggregate(array(1, 2, 3), (acc, x) -> acc + x, acc -> acc * 10);
60
```
## How was this patch tested?
Added tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#21982 from ueshin/issues/SPARK-23911/aggregate.
## What changes were proposed in this pull request?
Update Hadoop 2.7 to 2.7.7 to pull in bug and security fixes.
## How was this patch tested?
Existing tests.
Author: Sean Owen <srowen@gmail.com>
Closes#21987 from srowen/SPARK-25015.
## What changes were proposed in this pull request?
This small fix adds a `consumer.release()` call to `KafkaSourceRDD` in the case where we've retrieved offsets from Kafka, but the `fromOffset` is equal to the `lastOffset`, meaning there is no new data to read for a particular topic partition. Up until now, we'd just return an empty iterator without closing the consumer which would cause a FD leak.
If accepted, this pull request should be merged into master as well.
## How was this patch tested?
Haven't ran any specific tests, would love help on how to test methods running inside `RDD.compute`.
Author: Yuval Itzchakov <yuval.itzchakov@clicktale.com>
Closes#21997 from YuvalItzchakov/master.
## What changes were proposed in this pull request?
There are many warnings in the current build (for instance see https://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.7/4734/console).
**common**:
```
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/kvstore/src/main/java/org/apache/spark/util/kvstore/LevelDB.java:237: warning: [rawtypes] found raw type: LevelDBIterator
[warn] void closeIterator(LevelDBIterator it) throws IOException {
[warn] ^
[warn] missing type arguments for generic class LevelDBIterator<T>
[warn] where T is a type-variable:
[warn] T extends Object declared in class LevelDBIterator
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportServer.java:151: warning: [deprecation] group() in AbstractBootstrap has been deprecated
[warn] if (bootstrap != null && bootstrap.group() != null) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportServer.java:152: warning: [deprecation] group() in AbstractBootstrap has been deprecated
[warn] bootstrap.group().shutdownGracefully();
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportServer.java:154: warning: [deprecation] childGroup() in ServerBootstrap has been deprecated
[warn] if (bootstrap != null && bootstrap.childGroup() != null) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportServer.java:155: warning: [deprecation] childGroup() in ServerBootstrap has been deprecated
[warn] bootstrap.childGroup().shutdownGracefully();
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/util/NettyUtils.java:112: warning: [deprecation] PooledByteBufAllocator(boolean,int,int,int,int,int,int,int) in PooledByteBufAllocator has been deprecated
[warn] return new PooledByteBufAllocator(
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/client/TransportClient.java:321: warning: [rawtypes] found raw type: Future
[warn] public void operationComplete(Future future) throws Exception {
[warn] ^
[warn] missing type arguments for generic class Future<V>
[warn] where V is a type-variable:
[warn] V extends Object declared in interface Future
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/client/TransportResponseHandler.java:215: warning: [rawtypes] found raw type: StreamInterceptor
[warn] StreamInterceptor interceptor = new StreamInterceptor(this, resp.streamId, resp.byteCount,
[warn] ^
[warn] missing type arguments for generic class StreamInterceptor<T>
[warn] where T is a type-variable:
[warn] T extends Message declared in class StreamInterceptor
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/client/TransportResponseHandler.java:215: warning: [rawtypes] found raw type: StreamInterceptor
[warn] StreamInterceptor interceptor = new StreamInterceptor(this, resp.streamId, resp.byteCount,
[warn] ^
[warn] missing type arguments for generic class StreamInterceptor<T>
[warn] where T is a type-variable:
[warn] T extends Message declared in class StreamInterceptor
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/client/TransportResponseHandler.java:215: warning: [unchecked] unchecked call to StreamInterceptor(MessageHandler<T>,String,long,StreamCallback) as a member of the raw type StreamInterceptor
[warn] StreamInterceptor interceptor = new StreamInterceptor(this, resp.streamId, resp.byteCount,
[warn] ^
[warn] where T is a type-variable:
[warn] T extends Message declared in class StreamInterceptor
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:255: warning: [rawtypes] found raw type: StreamInterceptor
[warn] StreamInterceptor interceptor = new StreamInterceptor(this, wrappedCallback.getID(),
[warn] ^
[warn] missing type arguments for generic class StreamInterceptor<T>
[warn] where T is a type-variable:
[warn] T extends Message declared in class StreamInterceptor
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:255: warning: [rawtypes] found raw type: StreamInterceptor
[warn] StreamInterceptor interceptor = new StreamInterceptor(this, wrappedCallback.getID(),
[warn] ^
[warn] missing type arguments for generic class StreamInterceptor<T>
[warn] where T is a type-variable:
[warn] T extends Message declared in class StreamInterceptor
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:255: warning: [unchecked] unchecked call to StreamInterceptor(MessageHandler<T>,String,long,StreamCallback) as a member of the raw type StreamInterceptor
[warn] StreamInterceptor interceptor = new StreamInterceptor(this, wrappedCallback.getID(),
[warn] ^
[warn] where T is a type-variable:
[warn] T extends Message declared in class StreamInterceptor
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/crypto/TransportCipher.java:270: warning: [deprecation] transfered() in FileRegion has been deprecated
[warn] region.transferTo(byteRawChannel, region.transfered());
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/main/java/org/apache/spark/network/sasl/SaslEncryption.java:304: warning: [deprecation] transfered() in FileRegion has been deprecated
[warn] region.transferTo(byteChannel, region.transfered());
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/test/java/org/apache/spark/network/ProtocolSuite.java:119: warning: [deprecation] transfered() in FileRegion has been deprecated
[warn] while (in.transfered() < in.count()) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/network-common/src/test/java/org/apache/spark/network/ProtocolSuite.java:120: warning: [deprecation] transfered() in FileRegion has been deprecated
[warn] in.transferTo(channel, in.transfered());
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/unsafe/src/test/java/org/apache/spark/unsafe/hash/Murmur3_x86_32Suite.java:80: warning: [static] static method should be qualified by type name, Murmur3_x86_32, instead of by an expression
[warn] Assert.assertEquals(-300363099, hasher.hashUnsafeWords(bytes, offset, 16, 42));
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/unsafe/src/test/java/org/apache/spark/unsafe/hash/Murmur3_x86_32Suite.java:84: warning: [static] static method should be qualified by type name, Murmur3_x86_32, instead of by an expression
[warn] Assert.assertEquals(-1210324667, hasher.hashUnsafeWords(bytes, offset, 16, 42));
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/common/unsafe/src/test/java/org/apache/spark/unsafe/hash/Murmur3_x86_32Suite.java:88: warning: [static] static method should be qualified by type name, Murmur3_x86_32, instead of by an expression
[warn] Assert.assertEquals(-634919701, hasher.hashUnsafeWords(bytes, offset, 16, 42));
[warn] ^
```
**launcher**:
```
[warn] Pruning sources from previous analysis, due to incompatible CompileSetup.
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/launcher/src/main/java/org/apache/spark/launcher/AbstractLauncher.java:31: warning: [rawtypes] found raw type: AbstractLauncher
[warn] public abstract class AbstractLauncher<T extends AbstractLauncher> {
[warn] ^
[warn] missing type arguments for generic class AbstractLauncher<T>
[warn] where T is a type-variable:
[warn] T extends AbstractLauncher declared in class AbstractLauncher
```
**core**:
```
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/main/scala/org/apache/spark/api/r/RBackend.scala:99: method group in class AbstractBootstrap is deprecated: see corresponding Javadoc for more information.
[warn] if (bootstrap != null && bootstrap.group() != null) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/main/scala/org/apache/spark/api/r/RBackend.scala💯 method group in class AbstractBootstrap is deprecated: see corresponding Javadoc for more information.
[warn] bootstrap.group().shutdownGracefully()
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/main/scala/org/apache/spark/api/r/RBackend.scala:102: method childGroup in class ServerBootstrap is deprecated: see corresponding Javadoc for more information.
[warn] if (bootstrap != null && bootstrap.childGroup() != null) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/main/scala/org/apache/spark/api/r/RBackend.scala:103: method childGroup in class ServerBootstrap is deprecated: see corresponding Javadoc for more information.
[warn] bootstrap.childGroup().shutdownGracefully()
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala:151: reflective access of structural type member method getData should be enabled
[warn] by making the implicit value scala.language.reflectiveCalls visible.
[warn] This can be achieved by adding the import clause 'import scala.language.reflectiveCalls'
[warn] or by setting the compiler option -language:reflectiveCalls.
[warn] See the Scaladoc for value scala.language.reflectiveCalls for a discussion
[warn] why the feature should be explicitly enabled.
[warn] val rdd = sc.parallelize(1 to 1).map(concreteObject.getData)
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala:175: reflective access of structural type member value innerObject2 should be enabled
[warn] by making the implicit value scala.language.reflectiveCalls visible.
[warn] val rdd = sc.parallelize(1 to 1).map(concreteObject.innerObject2.getData)
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/util/ClosureCleanerSuite.scala:175: reflective access of structural type member method getData should be enabled
[warn] by making the implicit value scala.language.reflectiveCalls visible.
[warn] val rdd = sc.parallelize(1 to 1).map(concreteObject.innerObject2.getData)
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/LocalSparkContext.scala:32: constructor Slf4JLoggerFactory in class Slf4JLoggerFactory is deprecated: see corresponding Javadoc for more information.
[warn] InternalLoggerFactory.setDefaultFactory(new Slf4JLoggerFactory())
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:218: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] assert(wrapper.stageAttemptId === stages.head.attemptId)
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:261: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] stageAttemptId = stages.head.attemptId))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:287: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] stageAttemptId = stages.head.attemptId))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:471: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] stageAttemptId = stages.last.attemptId))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:966: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] listener.onTaskStart(SparkListenerTaskStart(dropped.stageId, dropped.attemptId, task))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:972: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] listener.onTaskEnd(SparkListenerTaskEnd(dropped.stageId, dropped.attemptId,
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:976: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] .taskSummary(dropped.stageId, dropped.attemptId, Array(0.25d, 0.50d, 0.75d))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:1146: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] SparkListenerTaskEnd(stage1.stageId, stage1.attemptId, "taskType", Success, tasks(1), null))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/status/AppStatusListenerSuite.scala:1150: value attemptId in class StageInfo is deprecated: Use attemptNumber instead
[warn] SparkListenerTaskEnd(stage1.stageId, stage1.attemptId, "taskType", Success, tasks(0), null))
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/storage/DiskStoreSuite.scala:197: method transfered in trait FileRegion is deprecated: see corresponding Javadoc for more information.
[warn] while (region.transfered() < region.count()) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/core/src/test/scala/org/apache/spark/storage/DiskStoreSuite.scala:198: method transfered in trait FileRegion is deprecated: see corresponding Javadoc for more information.
[warn] region.transferTo(byteChannel, region.transfered())
[warn] ^
```
**sql**:
```
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala:534: abstract type T is unchecked since it is eliminated by erasure
[warn] assert(partitioning.isInstanceOf[T])
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/AnalysisSuite.scala:534: abstract type T is unchecked since it is eliminated by erasure
[warn] assert(partitioning.isInstanceOf[T])
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ObjectExpressionsSuite.scala:323: inferred existential type Option[Class[_$1]]( forSome { type _$1 }), which cannot be expressed by wildcards, should be enabled
[warn] by making the implicit value scala.language.existentials visible.
[warn] This can be achieved by adding the import clause 'import scala.language.existentials'
[warn] or by setting the compiler option -language:existentials.
[warn] See the Scaladoc for value scala.language.existentials for a discussion
[warn] why the feature should be explicitly enabled.
[warn] val optClass = Option(collectionCls)
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java:226: warning: [deprecation] ParquetFileReader(Configuration,FileMetaData,Path,List<BlockMetaData>,List<ColumnDescriptor>) in ParquetFileReader has been deprecated
[warn] this.reader = new ParquetFileReader(
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:178: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] (descriptor.getType() == PrimitiveType.PrimitiveTypeName.INT32 ||
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:179: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] (descriptor.getType() == PrimitiveType.PrimitiveTypeName.INT64 &&
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:181: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] descriptor.getType() == PrimitiveType.PrimitiveTypeName.FLOAT ||
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:182: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] descriptor.getType() == PrimitiveType.PrimitiveTypeName.DOUBLE ||
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:183: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] descriptor.getType() == PrimitiveType.PrimitiveTypeName.BINARY))) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:198: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] switch (descriptor.getType()) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:221: warning: [deprecation] getTypeLength() in ColumnDescriptor has been deprecated
[warn] readFixedLenByteArrayBatch(rowId, num, column, descriptor.getTypeLength());
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:224: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] throw new IOException("Unsupported type: " + descriptor.getType());
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:246: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] descriptor.getType().toString(),
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:258: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] switch (descriptor.getType()) {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedColumnReader.java:384: warning: [deprecation] getType() in ColumnDescriptor has been deprecated
[warn] throw new UnsupportedOperationException("Unsupported type: " + descriptor.getType());
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/vectorized/ArrowColumnVector.java:458: warning: [static] static variable should be qualified by type name, BaseRepeatedValueVector, instead of by an expression
[warn] int index = rowId * accessor.OFFSET_WIDTH;
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/main/java/org/apache/spark/sql/vectorized/ArrowColumnVector.java:460: warning: [static] static variable should be qualified by type name, BaseRepeatedValueVector, instead of by an expression
[warn] int end = offsets.getInt(index + accessor.OFFSET_WIDTH);
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/test/scala/org/apache/spark/sql/BenchmarkQueryTest.scala:57: a pure expression does nothing in statement position; you may be omitting necessary parentheses
[warn] case s => s
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetInteroperabilitySuite.scala:182: inferred existential type org.apache.parquet.column.statistics.Statistics[?0]( forSome { type ?0 <: Comparable[?0] }), which cannot be expressed by wildcards, should be enabled
[warn] by making the implicit value scala.language.existentials visible.
[warn] This can be achieved by adding the import clause 'import scala.language.existentials'
[warn] or by setting the compiler option -language:existentials.
[warn] See the Scaladoc for value scala.language.existentials for a discussion
[warn] why the feature should be explicitly enabled.
[warn] val columnStats = oneBlockColumnMeta.getStatistics
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/sources/ForeachBatchSinkSuite.scala:146: implicit conversion method conv should be enabled
[warn] by making the implicit value scala.language.implicitConversions visible.
[warn] This can be achieved by adding the import clause 'import scala.language.implicitConversions'
[warn] or by setting the compiler option -language:implicitConversions.
[warn] See the Scaladoc for value scala.language.implicitConversions for a discussion
[warn] why the feature should be explicitly enabled.
[warn] implicit def conv(x: (Int, Long)): KV = KV(x._1, x._2)
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/test/scala/org/apache/spark/sql/streaming/continuous/shuffle/ContinuousShuffleSuite.scala:48: implicit conversion method unsafeRow should be enabled
[warn] by making the implicit value scala.language.implicitConversions visible.
[warn] private implicit def unsafeRow(value: Int) = {
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetInteroperabilitySuite.scala:178: method getType in class ColumnDescriptor is deprecated: see corresponding Javadoc for more information.
[warn] assert(oneFooter.getFileMetaData.getSchema.getColumns.get(0).getType() ===
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetTest.scala:154: method readAllFootersInParallel in object ParquetFileReader is deprecated: see corresponding Javadoc for more information.
[warn] ParquetFileReader.readAllFootersInParallel(configuration, fs.getFileStatus(path)).asScala.toSeq
[warn] ^
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/sql/hive/src/test/java/org/apache/spark/sql/hive/test/Complex.java:679: warning: [cast] redundant cast to Complex
[warn] Complex typedOther = (Complex)other;
[warn] ^
```
**mllib**:
```
[warn] Pruning sources from previous analysis, due to incompatible CompileSetup.
[warn] /home/jenkins/workspace/spark-master-test-maven-hadoop-2.7/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala:597: match may not be exhaustive.
[warn] It would fail on the following inputs: None, Some((x: Tuple2[?, ?] forSome x not in (?, ?)))
[warn] val df = dfs.find {
[warn] ^
```
This PR does not target fix all of them since some look pretty tricky to fix and there look too many warnings including false positive (like deprecated API but it's used in its test, etc.)
## How was this patch tested?
Existing tests should cover this.
Author: hyukjinkwon <gurwls223@apache.org>
Closes#21975 from HyukjinKwon/remove-build-warnings.
## What changes were proposed in this pull request?
Netty could just ignore user-provided configurations. In particular, spark.driver.cores would be ignored when considering the number of cores available to netty (which would usually just default to Runtime.availableProcessors() ). In transport configurations, the number of threads are based directly on how many cores the system believes it has available, and in yarn cluster mode this would generally overshoot the user-preferred value.
## How was this patch tested?
As this is mostly a configuration change, tests were done manually by adding spark-submit confs and verifying the number of threads started by netty was what was expected.
Passes scalastyle checks from dev/run-tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Nihar Sheth <niharrsheth@gmail.com>
Closes#21885 from NiharS/usableCores.
## What changes were proposed in this pull request?
simplify the codegen:
1. only do real codegen if the type can be specialized by the hash set
2. change the null handling. Before: track the nullElementIndex, and create a new ArrayData to insert the null in the middle. After: track the nullElementIndex, put a null placeholder in the ArrayBuilder, at the end create ArrayData from ArrayBuilder directly.
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#21966 from cloud-fan/minor2.
## What changes were proposed in this pull request?
This pr adds `filter` function which filters the input array using the given predicate.
```sql
> SELECT filter(array(1, 2, 3), x -> x % 2 == 1);
array(1, 3)
```
## How was this patch tested?
Added tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#21965 from ueshin/issues/SPARK-23909/filter.
## What changes were proposed in this pull request?
Many Spark SQL users in my company have asked for a way to control the number of output files in Spark SQL. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. We propose adding the following Hive-style Coalesce and Repartition Hint to Spark SQL:
```
... SELECT /*+ COALESCE(numPartitions) */ ...
... SELECT /*+ REPARTITION(numPartitions) */ ...
```
Multiple such hints are allowed. Multiple nodes are inserted into the logical plan, and the optimizer will pick the leftmost hint.
```
INSERT INTO s SELECT /*+ REPARTITION(100), COALESCE(500), COALESCE(10) */ * FROM t
== Logical Plan ==
'InsertIntoTable 'UnresolvedRelation `s`, false, false
+- 'UnresolvedHint REPARTITION, [100]
+- 'UnresolvedHint COALESCE, [500]
+- 'UnresolvedHint COALESCE, [10]
+- 'Project [*]
+- 'UnresolvedRelation `t`
== Optimized Logical Plan ==
InsertIntoHadoopFsRelationCommand ...
+- Repartition 100, true
+- HiveTableRelation ...
```
## How was this patch tested?
All unit tests. Manual tests using explain.
Author: John Zhuge <jzhuge@apache.org>
Closes#21911 from jzhuge/SPARK-24940.
## What changes were proposed in this pull request?
In the PR, I propose column-based API for the `pivot()` function. It allows using of any column expressions as the pivot column. Also this makes it consistent with how groupBy() works.
## How was this patch tested?
I added new tests to `DataFramePivotSuite` and updated PySpark examples for the `pivot()` function.
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#21699 from MaxGekk/pivot-column.
## What changes were proposed in this pull request?
Increase ZK timeout and harmonize configs across Kafka tests to resol…ve potentially flaky test failure
## How was this patch tested?
Existing tests
Author: Sean Owen <srowen@gmail.com>
Closes#21995 from srowen/SPARK-18057.3.
## What changes were proposed in this pull request?
Fixed little typo for a comment
## How was this patch tested?
Manual test
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Onwuka Gideon <dongidomed@gmail.com>
Closes#21992 from dongido001/patch-1.
## What changes were proposed in this pull request?
We don't support run a barrier stage with dynamic resource allocation enabled, it shall lead to some confusing behaviors (eg. with dynamic resource allocation enabled, it may happen that we acquire some executors (but not enough to launch all the tasks in a barrier stage) and later release them due to executor idle time expire, and then acquire again).
We perform the check on job submit and fail fast if running a barrier stage with dynamic resource allocation enabled.
## How was this patch tested?
Added new test suite `BarrierStageOnSubmittedSuite` to cover all the fail fast cases that submitted a job containing one or more barrier stages.
Author: Xingbo Jiang <xingbo.jiang@databricks.com>
Closes#21915 from jiangxb1987/SPARK-24954.
## What changes were proposed in this pull request?
Update to kafka 2.0.0 in streaming-kafka module, and remove override for Scala 2.12. It won't compile for 2.12 otherwise.
## How was this patch tested?
Existing tests.
Author: Sean Owen <srowen@gmail.com>
Closes#21955 from srowen/SPARK-18057.2.
## What changes were proposed in this pull request?
When lindblombr at apple developed [SPARK-24855](https://github.com/apache/spark/pull/21847) to support specified schema on write, we found a performance regression in Avro writer for our dataset.
With this PR, the performance is improved, but not as good as Spark 2.3 + the old avro writer. There must be something we miss which we need to investigate further.
Spark 2.4
```
spark git:(master) ./build/mvn -DskipTests clean package
spark git:(master) bin/spark-shell --jars external/avro/target/spark-avro_2.11-2.4.0-SNAPSHOT.jar
```
Spark 2.3 + databricks avro
```
spark git:(branch-2.3) ./build/mvn -DskipTests clean package
spark git:(branch-2.3) bin/spark-shell --packages com.databricks:spark-avro_2.11:4.0.0
```
Current master:
```
+-------+--------------------+
|summary| writeTimes|
+-------+--------------------+
| count| 100|
| mean| 2.95621|
| stddev|0.030895815479469294|
| min| 2.915|
| max| 3.049|
+-------+--------------------+
+-------+--------------------+
|summary| readTimes|
+-------+--------------------+
| count| 100|
| mean| 0.31072999999999995|
| stddev|0.054139709842390006|
| min| 0.259|
| max| 0.692|
+-------+--------------------+
```
Current master with this PR:
```
+-------+--------------------+
|summary| writeTimes|
+-------+--------------------+
| count| 100|
| mean| 2.5804300000000002|
| stddev|0.011175600225672079|
| min| 2.558|
| max| 2.62|
+-------+--------------------+
+-------+--------------------+
|summary| readTimes|
+-------+--------------------+
| count| 100|
| mean| 0.29922000000000004|
| stddev|0.058261961532514166|
| min| 0.251|
| max| 0.732|
+-------+--------------------+
```
Spark 2.3 + databricks avro:
```
+-------+--------------------+
|summary| writeTimes|
+-------+--------------------+
| count| 100|
| mean| 1.7730500000000005|
| stddev|0.025199156230863575|
| min| 1.729|
| max| 1.833|
+-------+--------------------+
+-------+-------------------+
|summary| readTimes|
+-------+-------------------+
| count| 100|
| mean| 0.29715|
| stddev|0.05685643358850465|
| min| 0.258|
| max| 0.718|
+-------+-------------------+
```
The following is the test code to reproduce the result.
```scala
spark.sqlContext.setConf("spark.sql.avro.compression.codec", "uncompressed")
val sparkSession = spark
import sparkSession.implicits._
val df = spark.sparkContext.range(1, 3000).repartition(1).map { uid =>
val features = Array.fill(16000)(scala.math.random)
(uid, scala.math.random, java.util.UUID.randomUUID().toString, java.util.UUID.randomUUID().toString, features)
}.toDF("uid", "random", "uuid1", "uuid2", "features").cache()
val size = df.count()
// Write into ramdisk to rule out the disk IO impact
val tempSaveDir = s"/Volumes/ramdisk/${java.util.UUID.randomUUID()}/"
val n = 150
val writeTimes = new Array[Double](n)
var i = 0
while (i < n) {
val t1 = System.currentTimeMillis()
df.write
.format("com.databricks.spark.avro")
.mode("overwrite")
.save(tempSaveDir)
val t2 = System.currentTimeMillis()
writeTimes(i) = (t2 - t1) / 1000.0
i += 1
}
df.unpersist()
// The first 50 runs are for warm-up
val readTimes = new Array[Double](n)
i = 0
while (i < n) {
val t1 = System.currentTimeMillis()
val readDF = spark.read.format("com.databricks.spark.avro").load(tempSaveDir)
assert(readDF.count() == size)
val t2 = System.currentTimeMillis()
readTimes(i) = (t2 - t1) / 1000.0
i += 1
}
spark.sparkContext.parallelize(writeTimes.slice(50, 150)).toDF("writeTimes").describe("writeTimes").show()
spark.sparkContext.parallelize(readTimes.slice(50, 150)).toDF("readTimes").describe("readTimes").show()
```
## How was this patch tested?
Existing tests.
Author: DB Tsai <d_tsai@apple.com>
Author: Brian Lindblom <blindblom@apple.com>
Closes#21952 from dbtsai/avro-performance-fix.
## What changes were proposed in this pull request?
It seems 'doRunMain()' has been removed accidentally by other PR and due to that the application submission is not happening, this PR adds back the 'doRunMain()' for standalone cluster submission.
## How was this patch tested?
I verified it manually by submitting application in standalone cluster mode, all the applications are submitting to the Master with the change.
Author: Devaraj K <devaraj@apache.org>
Closes#21979 from devaraj-kavali/SPARK-25009.
## What changes were proposed in this pull request?
jira: https://issues.apache.org/jira/browse/SPARK-25011
add prefix to __all__ in fpm.py
## How was this patch tested?
existing unit test.
Author: Yuhao Yang <yuhao.yang@intel.com>
Closes#21981 from hhbyyh/prefixall.
## What changes were proposed in this pull request?
Enable support for MINUS ALL which was gated at AstBuilder.
## How was this patch tested?
Added tests in SQLQueryTestSuite and modify PlanParserSuite.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Dilip Biswal <dbiswal@us.ibm.com>
Closes#21963 from dilipbiswal/minus-all.
## What changes were proposed in this pull request?
In the current master, `toString` throws an exception when `RelationalGroupedDataset` has unresolved expressions;
```
scala> spark.range(0, 10).groupBy("id")
res4: org.apache.spark.sql.RelationalGroupedDataset = RelationalGroupedDataset: [grouping expressions: [id: bigint], value: [id: bigint], type: GroupBy]
scala> spark.range(0, 10).groupBy('id)
org.apache.spark.sql.catalyst.analysis.UnresolvedException: Invalid call to dataType on unresolved object, tree: 'id
at org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute.dataType(unresolved.scala:105)
at org.apache.spark.sql.RelationalGroupedDataset$$anonfun$12.apply(RelationalGroupedDataset.scala:474)
at org.apache.spark.sql.RelationalGroupedDataset$$anonfun$12.apply(RelationalGroupedDataset.scala:473)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at org.apache.spark.sql.RelationalGroupedDataset.toString(RelationalGroupedDataset.scala:473)
at scala.runtime.ScalaRunTime$.scala$runtime$ScalaRunTime$$inner$1(ScalaRunTime.scala:332)
at scala.runtime.ScalaRunTime$.stringOf(ScalaRunTime.scala:337)
at scala.runtime.ScalaRunTime$.replStringOf(ScalaRunTime.scala:345)
```
This pr fixed code to handle the unresolved case in `RelationalGroupedDataset.toString`.
Closes#21752
## How was this patch tested?
Added tests in `DataFrameAggregateSuite`.
Author: Chris Horn <chorn4033@gmail.com>
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#21964 from maropu/SPARK-24788.
## What changes were proposed in this pull request?
Currently the output namespace is starting with ".", e.g. `.topLevelRecord`
Although it is valid according to Avro spec, we should remove the starting dot in case of failures when the output Avro file is read by other lib:
https://github.com/linkedin/goavro/pull/96
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21974 from gengliangwang/avro_namespace.
## What changes were proposed in this pull request?
Currently the set operations INTERSECT, UNION and EXCEPT are assigned the same precedence. This PR fixes the problem by giving INTERSECT higher precedence than UNION and EXCEPT. UNION and EXCEPT operators are evaluated in the order in which they appear in the query from left to right.
This results in change in behavior because of the change in order of evaluations of set operators in a query. The old behavior is still preserved under a newly added config parameter.
Query `:`
```
SELECT * FROM t1
UNION
SELECT * FROM t2
EXCEPT
SELECT * FROM t3
INTERSECT
SELECT * FROM t4
```
Parsed plan before the change `:`
```
== Parsed Logical Plan ==
'Intersect false
:- 'Except false
: :- 'Distinct
: : +- 'Union
: : :- 'Project [*]
: : : +- 'UnresolvedRelation `t1`
: : +- 'Project [*]
: : +- 'UnresolvedRelation `t2`
: +- 'Project [*]
: +- 'UnresolvedRelation `t3`
+- 'Project [*]
+- 'UnresolvedRelation `t4`
```
Parsed plan after the change `:`
```
== Parsed Logical Plan ==
'Except false
:- 'Distinct
: +- 'Union
: :- 'Project [*]
: : +- 'UnresolvedRelation `t1`
: +- 'Project [*]
: +- 'UnresolvedRelation `t2`
+- 'Intersect false
:- 'Project [*]
: +- 'UnresolvedRelation `t3`
+- 'Project [*]
+- 'UnresolvedRelation `t4`
```
## How was this patch tested?
Added tests in PlanParserSuite, SQLQueryTestSuite.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Dilip Biswal <dbiswal@us.ibm.com>
Closes#21941 from dilipbiswal/SPARK-24966.
## What changes were proposed in this pull request?
Support reading/writing Avro logical timestamp type with different precisions
https://avro.apache.org/docs/1.8.2/spec.html#Timestamp+%28millisecond+precision%29
To specify the output timestamp type, use Dataframe option `outputTimestampType` or SQL config `spark.sql.avro.outputTimestampType`. The supported values are
* `TIMESTAMP_MICROS`
* `TIMESTAMP_MILLIS`
The default output type is `TIMESTAMP_MICROS`
## How was this patch tested?
Unit test
Author: Gengliang Wang <gengliang.wang@databricks.com>
Closes#21935 from gengliangwang/avro_timestamp.
## What changes were proposed in this pull request?
According to https://github.com/apache/spark/pull/21758#discussion_r206746905 , current declaration of `BarrierTaskContext` didn't extend methods from `TaskContext`. Since `TaskContext` is an abstract class and we don't want to change it to a trait, we have to define class `BarrierTaskContext` directly.
## How was this patch tested?
Existing tests.
Author: Xingbo Jiang <xingbo.jiang@databricks.com>
Closes#21972 from jiangxb1987/BarrierTaskContext.
## What changes were proposed in this pull request?
This PR refactors code to get a value for "spark.sql.codegen.comments" by avoiding `SparkEnv.get.conf`. This PR uses `SQLConf.get.codegenComments` since `SQLConf.get` always returns an instance of `SQLConf`.
## How was this patch tested?
Added test case to `DebuggingSuite`
Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Closes#19449 from kiszk/SPARK-22219.
## What changes were proposed in this pull request?
`Uuid`'s results depend on random seed given during analysis. Thus under streaming query, we will have the same uuids in each execution. This seems to be incorrect for streaming query execution.
## How was this patch tested?
Added test.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#21854 from viirya/uuid_in_streaming.
## What changes were proposed in this pull request?
In the current master, `EnsureRequirements` sets the number of exchanges in `ExchangeCoordinator` before `ReuseExchange`. Then, `ReuseExchange` removes some duplicate exchange and the actual number of registered exchanges changes. Finally, the assertion in `ExchangeCoordinator` fails because the logical number of exchanges and the actual number of registered exchanges become different;
https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/ExchangeCoordinator.scala#L201
This pr fixed the issue and the code to reproduce this is as follows;
```
scala> sql("SET spark.sql.adaptive.enabled=true")
scala> sql("SET spark.sql.autoBroadcastJoinThreshold=-1")
scala> val df = spark.range(1).selectExpr("id AS key", "id AS value")
scala> val resultDf = df.join(df, "key").join(df, "key")
scala> resultDf.show
...
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
... 101 more
Caused by: java.lang.AssertionError: assertion failed
at scala.Predef$.assert(Predef.scala:156)
at org.apache.spark.sql.execution.exchange.ExchangeCoordinator.doEstimationIfNecessary(ExchangeCoordinator.scala:201)
at org.apache.spark.sql.execution.exchange.ExchangeCoordinator.postShuffleRDD(ExchangeCoordinator.scala:259)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:124)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
...
```
## How was this patch tested?
Added tests in `ExchangeCoordinatorSuite`.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#21754 from maropu/SPARK-24705-2.
## What changes were proposed in this pull request?
This pr adds `transform` function which transforms elements in an array using the function.
Optionally we can take the index of each element as the second argument.
```sql
> SELECT transform(array(1, 2, 3), x -> x + 1);
array(2, 3, 4)
> SELECT transform(array(1, 2, 3), (x, i) -> x + i);
array(1, 3, 5)
```
## How was this patch tested?
Added tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#21954 from ueshin/issues/SPARK-23908/transform.
## What changes were proposed in this pull request?
This pr fixes lint-python.
```
./python/pyspark/accumulators.py:231:9: E306 expected 1 blank line before a nested definition, found 0
./python/pyspark/accumulators.py:257:101: E501 line too long (107 > 100 characters)
./python/pyspark/accumulators.py:264:1: E302 expected 2 blank lines, found 1
./python/pyspark/accumulators.py:281:1: E302 expected 2 blank lines, found 1
```
## How was this patch tested?
Executed lint-python manually.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes#21973 from ueshin/issues/build/1/fix_lint-python.
## What changes were proposed in this pull request?
Check on job submit to make sure we don't launch a barrier stage with unsupported RDD chain pattern. The following patterns are not supported:
- Ancestor RDDs that have different number of partitions from the resulting RDD (eg. union()/coalesce()/first()/PartitionPruningRDD);
- An RDD that depends on multiple barrier RDDs (eg. barrierRdd1.zip(barrierRdd2)).
## How was this patch tested?
Add test cases in `BarrierStageOnSubmittedSuite`.
Author: Xingbo Jiang <xingbo.jiang@databricks.com>
Closes#21927 from jiangxb1987/SPARK-24820.
