## What changes were proposed in this pull request?
We have completed a significant subset of the object related Expressions to provide an interpreted fallback. This PR is going to modify the tests to also test the interpreted code paths.
One concern right now is that by testing the interpreted code paths too, we will double current test time or more. Otherwise, we can only choose to test the interpreted code paths for just few test suites such as encoder related.
## How was this patch tested?
Existing tests.
Closes#21535 from viirya/SPARK-23596.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
This pr is a follow-up pr of #21982 and fixes the examples.
## How was this patch tested?
Existing tests.
Closes#22035 from ueshin/issues/SPARK-23911/fup1.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
## What changes were proposed in this pull request?
The PR remove the following compilation error using scala-2.12 with sbt by adding a default case to `match`.
```
/home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/ValueInterval.scala:63: match may not be exhaustive.
[error] It would fail on the following inputs: (NumericValueInterval(_, _), _), (_, NumericValueInterval(_, _)), (_, _)
[error] [warn] def isIntersected(r1: ValueInterval, r2: ValueInterval): Boolean = (r1, r2) match {
[error] [warn]
[error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/ValueInterval.scala:79: match may not be exhaustive.
[error] It would fail on the following inputs: (NumericValueInterval(_, _), _), (_, NumericValueInterval(_, _)), (_, _)
[error] [warn] (r1, r2) match {
[error] [warn]
[error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproxCountDistinctForIntervals.scala:67: match may not be exhaustive.
[error] It would fail on the following inputs: (ArrayType(_, _), _), (_, ArrayData()), (_, _)
[error] [warn] (endpointsExpression.dataType, endpointsExpression.eval()) match {
[error] [warn]
[error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala:470: match may not be exhaustive.
[error] It would fail on the following inputs: NewFunctionSpec(_, None, Some(_)), NewFunctionSpec(_, Some(_), None)
[error] [warn] newFunction match {
[error] [warn]
[error] [warn] [error] [warn] /home/ishizaki/Spark/PR/scala212/spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala:709: match may not be exhaustive.
[error] It would fail on the following input: Schema((x: org.apache.spark.sql.types.DataType forSome x not in org.apache.spark.sql.types.StructType), _)
[error] [warn] def attributesFor[T: TypeTag]: Seq[Attribute] = schemaFor[T] match {
[error] [warn]
```
## How was this patch tested?
Existing UTs with Scala-2.11.
Manually build with Scala-2.12
Closes#22014 from kiszk/SPARK-25036b.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
This PR fixes an exception during the compilation of generated code of `mapEntry`. This error occurs since the current code uses `key` type to store a `value` when `key` and `value` types are primitive type.
```
val mid0 = Literal.create(Map(1 -> 1.1, 2 -> 2.2), MapType(IntegerType, DoubleType))
checkEvaluation(MapEntries(mid0), Seq(r(1, 1.1), r(2, 2.2)))
```
```
[info] Code generation of map_entries(keys: [1,2], values: [1.1,2.2]) failed:
[info] java.util.concurrent.ExecutionException: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 80, Column 20: failed to compile: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 80, Column 20: No applicable constructor/method found for actual parameters "int, double"; candidates are: "public void org.apache.spark.sql.catalyst.expressions.UnsafeRow.setInt(int, int)", "public void org.apache.spark.sql.catalyst.InternalRow.setInt(int, int)"
[info] java.util.concurrent.ExecutionException: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 80, Column 20: failed to compile: org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 80, Column 20: No applicable constructor/method found for actual parameters "int, double"; candidates are: "public void org.apache.spark.sql.catalyst.expressions.UnsafeRow.setInt(int, int)", "public void org.apache.spark.sql.catalyst.InternalRow.setInt(int, int)"
[info] at com.google.common.util.concurrent.AbstractFuture$Sync.getValue(AbstractFuture.java:306)
[info] at com.google.common.util.concurrent.AbstractFuture$Sync.get(AbstractFuture.java:293)
[info] at com.google.common.util.concurrent.AbstractFuture.get(AbstractFuture.java:116)
[info] at com.google.common.util.concurrent.Uninterruptibles.getUninterruptibly(Uninterruptibles.java:135)
[info] at com.google.common.cache.LocalCache$Segment.getAndRecordStats(LocalCache.java:2410)
[info] at com.google.common.cache.LocalCache$Segment.loadSync(LocalCache.java:2380)
[info] at com.google.common.cache.LocalCache$Segment.lockedGetOrLoad(LocalCache.java:2342)
[info] at com.google.common.cache.LocalCache$Segment.get(LocalCache.java:2257)
[info] at com.google.common.cache.LocalCache.get(LocalCache.java:4000)
[info] at com.google.common.cache.LocalCache.getOrLoad(LocalCache.java:4004)
[info] at com.google.common.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4874)
[info] at org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator$.compile(CodeGenerator.scala:1290)
...
```
## How was this patch tested?
Added a new test to `CollectionExpressionsSuite`
Closes#22033 from kiszk/SPARK-23935-followup.
Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
## What changes were proposed in this pull request?
This is a follow-up pr of #21980.
`Shuffle` can also be `ExpressionWithRandomSeed` to produce different values for each execution in streaming query.
## How was this patch tested?
Added a test.
Closes#22027 from ueshin/issues/SPARK-25010/random_seed.
Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
## What changes were proposed in this pull request?
This adds a new logical plan, AppendData, that was proposed in SPARK-23521: Standardize SQL logical plans.
* DataFrameWriter uses the new AppendData plan for DataSourceV2 appends
* AppendData is resolved if its output columns match the incoming data frame
* A new analyzer rule, ResolveOutputColumns, validates data before it is appended. This rule will add safe casts, rename columns, and checks nullability
## How was this patch tested?
Existing tests for v2 appends. Will add AppendData tests to validate logical plan analysis.
Closes#21305 from rdblue/SPARK-24251-add-append-data.
Lead-authored-by: Ryan Blue <blue@apache.org>
Co-authored-by: Ryan Blue <rdblue@users.noreply.github.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
## What changes were proposed in this pull request?
The PR fix the bug in `buildFormattedString` function in `MapType`, which makes the printed schema misleading.
## How was this patch tested?
Added UT
Closes#22006 from invkrh/fix-map-schema-print.
Authored-by: invkrh <invkrh@gmail.com>
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
## What changes were proposed in this pull request?
The PR adds the high order function `map_filter`, which filters the entries of a map and returns a new map which contains only the entries which satisfied the filter function.
## How was this patch tested?
added UTs
Closes#21986 from mgaido91/SPARK-23937.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
## What changes were proposed in this pull request?
This is a followup of https://github.com/apache/spark/pull/21822
Similar to `TreeNode`, `AnalysisHelper` should also provide 3 versions of transformations: `resolveOperatorsUp`, `resolveOperatorsDown` and `resolveOperators`.
This PR adds the missing `resolveOperatorsUp`, and also fixes some code style which is missed in #21822
## How was this patch tested?
existing tests.
Author: Wenchen Fan <wenchen@databricks.com>
Closes#21932 from cloud-fan/follow.
## What changes were proposed in this pull request?
The tests for shuffle can be flaky (eg. https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/94355/testReport/). This happens because we have not set the seed for `Random`.
## How was this patch tested?
running 10000 times the UT (validated that with a different seed eg. 12345 the test fails).
Closes#22023 from mgaido91/SPARK-23928_followup.
Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
## What changes were proposed in this pull request?
The design details is attached to the JIRA issue [here](https://drive.google.com/file/d/1zKm3aNZ3DpsqIuoMvRsf0kkDkXsAasxH/view)
High level overview of the changes are:
- Enhance the qualifier to be more than one string
- Add support to store the qualifier. Enhance the lookupRelation to keep the qualifier appropriately.
- Enhance the table matching column resolution algorithm to account for qualifier being more than a string.
- Enhance the table matching algorithm in UnresolvedStar.expand
- Ensure that we continue to support select t1.i1 from db1.t1
## How was this patch tested?
- New tests are added.
- Several test scenarios were added in a separate [test pr 17067](https://github.com/apache/spark/pull/17067). The tests that were not supported earlier are marked with TODO markers and those are now supported with the code changes here.
- Existing unit tests ( hive, catalyst and sql) were run successfully.
Closes#17185 from skambha/colResolution.
Authored-by: Sunitha Kambhampati <skambha@us.ibm.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?
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?
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?
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.
## 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?
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?
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?
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?
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?
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?
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?
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 pull request provides a fix for SPARK-24742: SQL Field MetaData was throwing an Exception in the hashCode method when a "null" Metadata was added via "putNull"
## How was this patch tested?
A new unittest is provided in org/apache/spark/sql/types/MetadataSuite.scala
Author: Kaya Kupferschmidt <k.kupferschmidt@dimajix.de>
Closes#21722 from kupferk/SPARK-24742.
## What changes were proposed in this pull request?
Remove the AnalysisBarrier LogicalPlan node, which is useless now.
## How was this patch tested?
N/A
Author: Xiao Li <gatorsmile@gmail.com>
Closes#21962 from gatorsmile/refactor2.
## What changes were proposed in this pull request?
This PR is to refactor the code in AVERAGE by dsl.
## How was this patch tested?
N/A
Author: Xiao Li <gatorsmile@gmail.com>
Closes#21951 from gatorsmile/refactor1.
## What changes were proposed in this pull request?
The PR adds the SQL function `array_except`. The behavior of the function is based on Presto's one.
This function returns returns an array of the elements in array1 but not in 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#21103 from kiszk/SPARK-23915.
## What changes were proposed in this pull request?
When user calls anUDAF with the wrong number of arguments, Spark previously throws an AssertionError, which is not supposed to be a user-facing exception. This patch updates it to throw AnalysisException instead, so it is consistent with a regular UDF.
## How was this patch tested?
Updated test case udaf.sql.
Author: Reynold Xin <rxin@databricks.com>
Closes#21938 from rxin/SPARK-24982.
## What changes were proposed in this pull request?
Previously TVF resolution could throw IllegalArgumentException if the data type is null type. This patch replaces that exception with AnalysisException, enriched with positional information, to improve error message reporting and to be more consistent with rest of Spark SQL.
## How was this patch tested?
Updated the test case in table-valued-functions.sql.out, which is how I identified this problem in the first place.
Author: Reynold Xin <rxin@databricks.com>
Closes#21934 from rxin/SPARK-24951.
## What changes were proposed in this pull request?
Similar to SPARK-24890, if all the outputs of `CaseWhen` are semantic equivalence, `CaseWhen` can be removed.
## How was this patch tested?
Tests added.
Author: DB Tsai <d_tsai@apple.com>
Closes#21852 from dbtsai/short-circuit-when.
## What changes were proposed in this pull request?
It proposes a version in which nullable expressions are not valid in the limit clause
## How was this patch tested?
It was tested with unit and e2e tests.
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: Mauro Palsgraaf <mauropalsgraaf@hotmail.com>
Closes#21807 from mauropalsgraaf/SPARK-24536.
## What changes were proposed in this pull request?
When the pivot column is of a complex type, the eval() result will be an UnsafeRow, while the keys of the HashMap for column value matching is a GenericInternalRow. As a result, there will be no match and the result will always be empty.
So for a pivot column of complex-types, we should:
1) If the complex-type is not comparable (orderable), throw an Exception. It cannot be a pivot column.
2) Otherwise, if it goes through the `PivotFirst` code path, `PivotFirst` should use a TreeMap instead of HashMap for such columns.
This PR has also reverted the walk-around in Analyzer that had been introduced to avoid this `PivotFirst` issue.
## How was this patch tested?
Added UT.
Author: maryannxue <maryannxue@apache.org>
Closes#21926 from maryannxue/pivot_followup.
## What changes were proposed in this pull request?
In the PR, I propose to support `LZMA2` (`XZ`) and `BZIP2` compressions by `AVRO` datasource in write since the codecs may have better characteristics like compression ratio and speed comparing to already supported `snappy` and `deflate` codecs.
## How was this patch tested?
It was tested manually and by an existing test which was extended to check the `xz` and `bzip2` compressions.
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#21902 from MaxGekk/avro-xz-bzip2.
## What changes were proposed in this pull request?
I didn't want to pollute the diff in the previous PR and left some TODOs. This is a follow-up to address those TODOs.
## How was this patch tested?
Should be covered by existing tests.
Author: Reynold Xin <rxin@databricks.com>
Closes#21896 from rxin/SPARK-24865-addendum.
## What changes were proposed in this pull request?
This pr supported Date/Timestamp in a JDBC partition column (a numeric column is only supported in the master). This pr also modified code to verify a partition column type;
```
val jdbcTable = spark.read
.option("partitionColumn", "text")
.option("lowerBound", "aaa")
.option("upperBound", "zzz")
.option("numPartitions", 2)
.jdbc("jdbc:postgresql:postgres", "t", options)
// with this pr
org.apache.spark.sql.AnalysisException: Partition column type should be numeric, date, or timestamp, but string found.;
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.verifyAndGetNormalizedPartitionColumn(JDBCRelation.scala:165)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRelation$.columnPartition(JDBCRelation.scala:85)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:36)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:317)
// without this pr
java.lang.NumberFormatException: For input string: "aaa"
at java.lang.NumberFormatException.forInputString(NumberFormatException.java:65)
at java.lang.Long.parseLong(Long.java:589)
at java.lang.Long.parseLong(Long.java:631)
at scala.collection.immutable.StringLike$class.toLong(StringLike.scala:277)
```
Closes#19999
## How was this patch tested?
Added tests in `JDBCSuite`.
Author: Takeshi Yamamuro <yamamuro@apache.org>
Closes#21834 from maropu/SPARK-22814.
## What changes were proposed in this pull request?
When we do an average, the result is computed dividing the sum of the values by their count. In the case the result is a DecimalType, the way we are casting/managing the precision and scale is not really optimized and it is not coherent with what we do normally.
In particular, a problem can happen when the `Divide` operand returns a result which contains a precision and scale different by the ones which are expected as output of the `Divide` operand. In the case reported in the JIRA, for instance, the result of the `Divide` operand is a `Decimal(38, 36)`, while the output data type for `Divide` is 38, 22. This is not an issue when the `Divide` is followed by a `CheckOverflow` or a `Cast` to the right data type, as these operations return a decimal with the defined precision and scale. Despite in the `Average` operator we do have a `Cast`, this may be bypassed if the result of `Divide` is the same type which it is casted to, hence the issue reported in the JIRA may arise.
The PR proposes to use the normal rules/handling of the arithmetic operators with Decimal data type, so we both reuse the existing code (having a single logic for operations between decimals) and we fix this problem as the result is always guarded by `CheckOverflow`.
## How was this patch tested?
added UT
Author: Marco Gaido <marcogaido91@gmail.com>
Closes#21910 from mgaido91/SPARK-24957.
## What changes were proposed in this pull request?
Implements INTERSECT ALL clause through query rewrites using existing operators in Spark. Please refer to [Link](https://drive.google.com/open?id=1nyW0T0b_ajUduQoPgZLAsyHK8s3_dko3ulQuxaLpUXE) for the design.
Input Query
``` SQL
SELECT c1 FROM ut1 INTERSECT ALL SELECT c1 FROM ut2
```
Rewritten Query
```SQL
SELECT c1
FROM (
SELECT replicate_row(min_count, c1)
FROM (
SELECT c1,
IF (vcol1_cnt > vcol2_cnt, vcol2_cnt, vcol1_cnt) AS min_count
FROM (
SELECT c1, count(vcol1) as vcol1_cnt, count(vcol2) as vcol2_cnt
FROM (
SELECT c1, true as vcol1, null as vcol2 FROM ut1
UNION ALL
SELECT c1, null as vcol1, true as vcol2 FROM ut2
) AS union_all
GROUP BY c1
HAVING vcol1_cnt >= 1 AND vcol2_cnt >= 1
)
)
)
```
## How was this patch tested?
Added test cases in SQLQueryTestSuite, DataFrameSuite, SetOperationSuite
Author: Dilip Biswal <dbiswal@us.ibm.com>
Closes#21886 from dilipbiswal/dkb_intersect_all_final.
## What changes were proposed in this pull request?
- Update DateTimeUtilsSuite so that when testing roundtripping in daysToMillis and millisToDays multiple skipdates can be specified.
- Updated test so that both new years eve 2014 and new years day 2015 are skipped for kiribati time zones. This is necessary as java versions pre 181-b13 considered new years day 2015 to be skipped while susequent versions corrected this to new years eve.
## How was this patch tested?
Unit tests
Author: Chris Martin <chris@cmartinit.co.uk>
Closes#21901 from d80tb7/SPARK-24950_datetimeUtilsSuite_failures.
## What changes were proposed in this pull request?
Implements EXCEPT ALL clause through query rewrites using existing operators in Spark. In this PR, an internal UDTF (replicate_rows) is added to aid in preserving duplicate rows. Please refer to [Link](https://drive.google.com/open?id=1nyW0T0b_ajUduQoPgZLAsyHK8s3_dko3ulQuxaLpUXE) for the design.
**Note** This proposed UDTF is kept as a internal function that is purely used to aid with this particular rewrite to give us flexibility to change to a more generalized UDTF in future.
Input Query
``` SQL
SELECT c1 FROM ut1 EXCEPT ALL SELECT c1 FROM ut2
```
Rewritten Query
```SQL
SELECT c1
FROM (
SELECT replicate_rows(sum_val, c1)
FROM (
SELECT c1, sum_val
FROM (
SELECT c1, sum(vcol) AS sum_val
FROM (
SELECT 1L as vcol, c1 FROM ut1
UNION ALL
SELECT -1L as vcol, c1 FROM ut2
) AS union_all
GROUP BY union_all.c1
)
WHERE sum_val > 0
)
)
```
## How was this patch tested?
Added test cases in SQLQueryTestSuite, DataFrameSuite and SetOperationSuite
Author: Dilip Biswal <dbiswal@us.ibm.com>
Closes#21857 from dilipbiswal/dkb_except_all_final.
## What changes were proposed in this pull request?
In the PR, I added new option for Avro datasource - `compression`. The option allows to specify compression codec for saved Avro files. This option is similar to `compression` option in another datasources like `JSON` and `CSV`.
Also I added the SQL configs `spark.sql.avro.compression.codec` and `spark.sql.avro.deflate.level`. I put the configs into `SQLConf`. If the `compression` option is not specified by an user, the first SQL config is taken into account.
## How was this patch tested?
I added new test which read meta info from written avro files and checks `avro.codec` property.
Author: Maxim Gekk <maxim.gekk@databricks.com>
Closes#21837 from MaxGekk/avro-compression.
## What changes were proposed in this pull request?
This PR adds a new collection function: shuffle. It generates a random permutation of the given array. This implementation uses the "inside-out" version of Fisher-Yates algorithm.
## How was this patch tested?
New tests are added to CollectionExpressionsSuite.scala and DataFrameFunctionsSuite.scala.
Author: Takuya UESHIN <ueshin@databricks.com>
Author: pkuwm <ihuizhi.lu@gmail.com>
Closes#21802 from ueshin/issues/SPARK-23928/shuffle.
## What changes were proposed in this pull request?
AnalysisBarrier was introduced in SPARK-20392 to improve analysis speed (don't re-analyze nodes that have already been analyzed).
Before AnalysisBarrier, we already had some infrastructure in place, with analysis specific functions (resolveOperators and resolveExpressions). These functions do not recursively traverse down subplans that are already analyzed (with a mutable boolean flag _analyzed). The issue with the old system was that developers started using transformDown, which does a top-down traversal of the plan tree, because there was not top-down resolution function, and as a result analyzer performance became pretty bad.
In order to fix the issue in SPARK-20392, AnalysisBarrier was introduced as a special node and for this special node, transform/transformUp/transformDown don't traverse down. However, the introduction of this special node caused a lot more troubles than it solves. This implicit node breaks assumptions and code in a few places, and it's hard to know when analysis barrier would exist, and when it wouldn't. Just a simple search of AnalysisBarrier in PR discussions demonstrates it is a source of bugs and additional complexity.
Instead, this pull request removes AnalysisBarrier and reverts back to the old approach. We added infrastructure in tests that fail explicitly if transform methods are used in the analyzer.
## How was this patch tested?
Added a test suite AnalysisHelperSuite for testing the resolve* methods and transform* methods.
Author: Reynold Xin <rxin@databricks.com>
Author: Xiao Li <gatorsmile@gmail.com>
Closes#21822 from rxin/SPARK-24865.
