Commit graph

3094 commits

Author SHA1 Message Date
liuxian 4b11d909fd [MINOR][DOC] Add missing compression codec .
## What changes were proposed in this pull request?

Parquet file provides six codecs: "snappy", "gzip", "lzo", "lz4", "brotli", "zstd".
This pr add missing compression codec :"lz4", "brotli", "zstd" .
## How was this patch tested?
N/A

Closes #22068 from 10110346/nosupportlz4.

Authored-by: liuxian <liu.xian3@zte.com.cn>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-08-11 20:49:52 +08:00
Liang-Chi Hsieh 4f17585098 [SPARK-19355][SQL] Use map output statistics to improve global limit's parallelism
## What changes were proposed in this pull request?

A logical `Limit` is performed physically by two operations `LocalLimit` and `GlobalLimit`.

Most of time, we gather all data into a single partition in order to run `GlobalLimit`. If we use a very big limit number, shuffling data causes performance issue also reduces parallelism.

We can avoid shuffling into single partition if we don't care data ordering. This patch implements this idea by doing a map stage during global limit. It collects the info of row numbers at each partition. For each partition, we locally retrieves limited data without any shuffling to finish this global limit.

For example, we have three partitions with rows (100, 100, 50) respectively. In global limit of 100 rows, we may take (34, 33, 33) rows for each partition locally. After global limit we still have three partitions.

If the data partition has certain ordering, we can't distribute required rows evenly to each partitions because it could change data ordering. But we still can avoid shuffling.

## How was this patch tested?

Jenkins tests.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #16677 from viirya/improve-global-limit-parallelism.
2018-08-10 11:32:15 +02:00
Kazuaki Ishizaki ab1029fb8a [SPARK-23912][SQL][FOLLOWUP] Refactor ArrayDistinct
## What changes were proposed in this pull request?

This PR simplified code generation for `ArrayDistinct`. #21966 enabled code generation only if the type can be specialized by the hash set. This PR follows this strategy.

Optimization of null handling will be implemented in #21912.

## How was this patch tested?

Existing UTs

Closes #22044 from kiszk/SPARK-23912-follow.

Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
2018-08-10 15:41:59 +09:00
Ryan Blue bdd27961c8 [SPARK-24251][SQL] Add analysis tests for AppendData.
## What changes were proposed in this pull request?

This is a follow-up to #21305 that adds a test suite for AppendData analysis.

This also fixes the following problems uncovered by these tests:
* Incorrect order of data types passed to `canWrite` is fixed
* The field check calls `canWrite` first to ensure all errors are found
* `AppendData#resolved` must check resolution of the query's attributes
* Column names are quoted to show empty names

## How was this patch tested?

This PR adds a test suite for AppendData analysis.

Closes #22043 from rdblue/SPARK-24251-add-append-data-analysis-tests.

Authored-by: Ryan Blue <blue@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2018-08-10 11:10:23 +08:00
Takuya UESHIN 9b8521e53e [SPARK-25068][SQL] Add exists function.
## What changes were proposed in this pull request?

This pr adds `exists` function which tests whether a predicate holds for one or more elements in the array.

```sql
> SELECT exists(array(1, 2, 3), x -> x % 2 == 0);
 true
```

## How was this patch tested?

Added tests.

Closes #22052 from ueshin/issues/SPARK-25068/exists.

Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
2018-08-09 14:41:59 -07:00
Achuth17 d36539741f [SPARK-24626][SQL] Improve location size calculation in Analyze Table command
## What changes were proposed in this pull request?

Currently, Analyze table calculates table size sequentially for each partition. We can parallelize size calculations over partitions.

Results : Tested on a table with 100 partitions and data stored in S3.
With changes :
- 10.429s
- 10.557s
- 10.439s
- 9.893s


Without changes :
- 110.034s
- 99.510s
- 100.743s
- 99.106s

## How was this patch tested?

Simple unit test.

Closes #21608 from Achuth17/improveAnalyze.

Lead-authored-by: Achuth17 <Achuth.narayan@gmail.com>
Co-authored-by: arajagopal17 <arajagopal@qubole.com>
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
2018-08-09 08:29:24 -07:00
maryannxue 2949a835fa [SPARK-25063][SQL] Rename class KnowNotNull to KnownNotNull
## What changes were proposed in this pull request?

Correct the class name typo checked in through SPARK-24891

## How was this patch tested?

Passed all existing tests.

Closes #22049 from maryannxue/known-not-null.

Authored-by: maryannxue <maryannxue@apache.org>
Signed-off-by: Xiao Li <gatorsmile@gmail.com>
2018-08-09 08:11:30 -07:00
Kazuaki Ishizaki 386fbd3aff [SPARK-23415][SQL][TEST] Make behavior of BufferHolderSparkSubmitSuite correct and stable
## What changes were proposed in this pull request?

This PR addresses two issues in `BufferHolderSparkSubmitSuite`.

1. While `BufferHolderSparkSubmitSuite` tried to allocate a large object several times, it actually allocated an object once and reused the object.
2. `BufferHolderSparkSubmitSuite` may fail due to timeout

To assign a small object before allocating a large object each time solved issue 1 by avoiding reuse.
To increasing heap size from 4g to 7g solved issue 2. It can also avoid OOM after fixing issue 1.

## How was this patch tested?

Updated existing `BufferHolderSparkSubmitSuite`

Closes #20636 from kiszk/SPARK-23415.

Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2018-08-09 20:28:14 +08:00
Kazuaki Ishizaki 56e9e97073 [MINOR][DOC] Fix typo
## What changes were proposed in this pull request?

This PR fixes typo regarding `auxiliary verb + verb[s]`. This is a follow-on of #21956.

## How was this patch tested?

N/A

Closes #22040 from kiszk/spellcheck1.

Authored-by: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
2018-08-09 20:10:17 +08:00
Takuya UESHIN 519e03d82e [SPARK-25058][SQL] Use Block.isEmpty/nonEmpty to check whether the code is empty or not.
## What changes were proposed in this pull request?

We should use `Block.isEmpty/nonEmpty` instead of comparing with empty string to check whether the code is empty or not.

```
[error] [warn] /.../sql/core/src/main/scala/org/apache/spark/sql/execution/WholeStageCodegenExec.scala:278: org.apache.spark.sql.catalyst.expressions.codegen.Block and String are unrelated: they will most likely always compare unequal
[error] [warn]       if (ev.code != "" && required.contains(attributes(i))) {
[error] [warn]
[error] [warn] /.../sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastHashJoinExec.scala:323: org.apache.spark.sql.catalyst.expressions.codegen.Block and String are unrelated: they will most likely never compare equal
[error] [warn]          |  ${buildVars.filter(_.code == "").map(v => s"${v.isNull} = true;").mkString("\n")}
[error] [warn]
```

## How was this patch tested?

Existing tests.

Closes #22041 from ueshin/issues/SPARK-25058/fix_comparison.

Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
2018-08-09 14:06:28 +09:00
Liang-Chi Hsieh a40806d2bd [SPARK-23596][SQL] Test interpreted path on encoders test suites
## 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>
2018-08-09 12:07:57 +08:00
Takuya UESHIN 6f6a420078 [SPARK-23911][SQL][FOLLOW-UP] Fix examples of aggregate function.
## 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>
2018-08-09 00:01:03 +09:00
Kazuaki Ishizaki 960af63913 [SPARK-25036][SQL] avoid match may not be exhaustive in Scala-2.12
## 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>
2018-08-08 14:46:00 +08:00
Kazuaki Ishizaki f08f6f4314 [SPARK-23935][SQL][FOLLOWUP] mapEntry throws org.codehaus.commons.compiler.CompileException
## 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>
2018-08-08 14:38:55 +09:00
Takuya UESHIN c7a229d655 [SPARK-25010][SQL][FOLLOWUP] Shuffle should also produce different values for each execution in streaming query.
## 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>
2018-08-08 11:05:52 +08:00
Ryan Blue 5fef6e3513 [SPARK-24251][SQL] Add AppendData logical plan.
## 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>
2018-08-08 09:55:52 +08:00
invkrh 8c13cb2ae4 [SPARK-25031][SQL] Fix MapType schema print
## 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>
2018-08-07 11:04:37 -07:00
Marco Gaido cb6cb31363 [SPARK-23937][SQL] Add map_filter SQL function
## 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>
2018-08-08 02:12:19 +09:00
Wenchen Fan 1a29fec8e2 [SPARK-24979][SQL] add AnalysisHelper#resolveOperatorsUp
## 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.
2018-08-07 08:45:20 -07:00
Marco Gaido 6a143e3ebf [SPARK-23928][TESTS][FOLLOWUP] Set seed to avoid flakiness
## 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>
2018-08-07 22:23:59 +08:00
Sunitha Kambhampati b4bf8be549 [SPARK-19602][SQL] Support column resolution of fully qualified column name ( 3 part name)
## 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>
2018-08-07 21:11:08 +08:00
Marco Gaido 88e0c7bbd5 [SPARK-24341][SQL] Support only IN subqueries with the same number of items per row
## 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>
2018-08-07 15:43:41 +08:00
Liang-Chi Hsieh 43763629f1 [SPARK-25010][SQL] Rand/Randn should produce different values for each execution in streaming query
## 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>
2018-08-07 14:28:14 +08:00
Kazuaki Ishizaki 4446a0b0d9 [SPARK-23914][SQL][FOLLOW-UP] refactor ArrayUnion
## 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.
2018-08-07 12:07:56 +09:00
Marco Gaido 0f3fa2f289 [SPARK-24996][SQL] Use DSL in DeclarativeAggregate
## 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.
2018-08-06 19:46:51 -04:00
Kazuaki Ishizaki 408a3ff2c4 [SPARK-25036][SQL] Should compare ExprValue.isNull with LiteralTrue/LiteralFalse
## 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.
2018-08-06 19:43:21 -04:00
Kazuaki Ishizaki 1a5e460762 [SPARK-23913][SQL] Add array_intersect function
## 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.
2018-08-06 23:27:57 +09:00
Dilip Biswal c1760da5dd [SPARK-25025][SQL] Remove the default value of isAll in INTERSECT/EXCEPT
## 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.
2018-08-06 06:56:36 -04:00
John Zhuge d063e3a478 [SPARK-24940][SQL] Use IntegerLiteral in ResolveCoalesceHints
## 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.
2018-08-06 06:41:55 -04:00
Takuya UESHIN 327bb30075 [SPARK-23911][SQL] Add aggregate function.
## 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.
2018-08-05 08:58:35 +09:00
hyukjinkwon 55e3ae6930 [SPARK-25001][BUILD] Fix miscellaneous build warnings
## 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.
2018-08-04 11:52:49 -05:00
Wenchen Fan 684c719cc0 [SPARK-23915][SQL][FOLLOWUP] Add array_except function
## 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.
2018-08-04 16:35:14 +09:00
Takuya UESHIN 0ecc132d6b [SPARK-23909][SQL] Add filter function.
## 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.
2018-08-04 16:08:53 +09:00
John Zhuge 36ea55e97e [SPARK-24940][SQL] Coalesce and Repartition Hint for SQL Queries
## 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.
2018-08-04 02:27:15 -04:00
Dilip Biswal 19a4531913 [SPARK-24997][SQL] Enable support of MINUS ALL
## 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.
2018-08-02 22:45:10 -07:00
Dilip Biswal 73dd6cf9b5 [SPARK-24966][SQL] Implement precedence rules for set operations.
## 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.
2018-08-02 22:04:17 -07:00
Gengliang Wang 7cf16a7fa4 [SPARK-24773] Avro: support logical timestamp type with different precisions
## 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.
2018-08-03 08:32:08 +08:00
Kazuaki Ishizaki bbdcc3bf61 [SPARK-22219][SQL] Refactor code to get a value for "spark.sql.codegen.comments"
## 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.
2018-08-02 18:19:04 -05:00
Takuya UESHIN 02f967795b [SPARK-23908][SQL] Add transform function.
## 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.
2018-08-02 13:00:33 -07:00
Wenchen Fan f04cd67094 [MINOR] remove dead code in ExpressionEvalHelper
## What changes were proposed in this pull request?

This addresses https://github.com/apache/spark/pull/21236/files#r207078480

both https://github.com/apache/spark/pull/21236 and https://github.com/apache/spark/pull/21838 add a InternalRow result check to ExpressionEvalHelper and becomes duplicated.

## How was this patch tested?

N/A

Author: Wenchen Fan <wenchen@databricks.com>

Closes #21958 from cloud-fan/minor.
2018-08-02 09:26:27 -05:00
Kaya Kupferschmidt 7be6fc3c77 [SPARK-24742] Fix NullPointerexception in Field Metadata
## 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.
2018-08-02 09:22:21 -05:00
Xiao Li 46110a589f [SPARK-24865][FOLLOW-UP] Remove AnalysisBarrier LogicalPlan Node
## 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.
2018-08-02 22:20:41 +08:00
Xiao Li 166f346185 [SPARK-24957][SQL][FOLLOW-UP] Clean the code for AVERAGE
## 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.
2018-08-01 23:00:17 -07:00
Kazuaki Ishizaki 95a9d5e3a5 [SPARK-23915][SQL] Add array_except function
## 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.
2018-08-02 02:52:30 +08:00
Reynold Xin 1efffb7993 [SPARK-24982][SQL] UDAF resolution should not throw AssertionError
## 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.
2018-08-01 00:15:31 -07:00
Reynold Xin 1f7e22c72c [SPARK-24951][SQL] Table valued functions should throw AnalysisException
## 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.
2018-07-31 22:25:40 -07:00
DB Tsai 5f3441e542 [SPARK-24893][SQL] Remove the entire CaseWhen if all the outputs are semantic equivalence
## 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.
2018-08-01 10:31:02 +08:00
Mauro Palsgraaf 4ac2126bc6 [SPARK-24536] Validate that an evaluated limit clause cannot be null
## 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.
2018-07-31 08:18:08 -07:00
maryannxue b4fd75fb9b [SPARK-24972][SQL] PivotFirst could not handle pivot columns of complex types
## 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.
2018-07-30 23:43:53 -07:00
Maxim Gekk d20c10fdf3 [SPARK-24952][SQL] Support LZMA2 compression by Avro datasource
## 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.
2018-07-31 09:12:57 +08:00