Commit graph

7522 commits

Author SHA1 Message Date
Yuming Wang aa509c1eee [SPARK-34031][SQL] Union operator missing rowCount when CBO enabled
### What changes were proposed in this pull request?

This pr add row count to `Union` operator when CBO enabled.
```scala
spark.sql("CREATE TABLE t1 USING parquet AS SELECT id FROM RANGE(10)")
spark.sql("CREATE TABLE t2 USING parquet AS SELECT id FROM RANGE(10)")
spark.sql("ANALYZE TABLE t1 COMPUTE STATISTICS FOR ALL COLUMNS")
spark.sql("ANALYZE TABLE t2 COMPUTE STATISTICS FOR ALL COLUMNS")
spark.sql("set spark.sql.cbo.enabled=true")
spark.sql("SELECT * FROM t1 UNION ALL SELECT * FROM t2").explain("cost")
```

Before this pr:
```
== Optimized Logical Plan ==
Union false, false, Statistics(sizeInBytes=320.0 B)
:- Relation[id#5880L] parquet, Statistics(sizeInBytes=160.0 B, rowCount=10)
+- Relation[id#5881L] parquet, Statistics(sizeInBytes=160.0 B, rowCount=10)
```

After this pr:
```
== Optimized Logical Plan ==
Union false, false, Statistics(sizeInBytes=320.0 B, rowCount=20)
:- Relation[id#2138L] parquet, Statistics(sizeInBytes=160.0 B, rowCount=10)
+- Relation[id#2139L] parquet, Statistics(sizeInBytes=160.0 B, rowCount=10)
```

### Why are the changes needed?

Improve query performance,  [`JoinEstimation.estimateInnerOuterJoin`](d6a68e0b67/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/statsEstimation/JoinEstimation.scala (L55-L156)) need the row count.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Unit test.

Closes #31068 from wangyum/SPARK-34031.

Lead-authored-by: Yuming Wang <yumwang@ebay.com>
Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-01-07 14:41:10 +09:00
ulysses-you f9daf035f4 [SPARK-33806][SQL][FOLLOWUP] Fold RepartitionExpression num partition should check if partition expression is empty
### What changes were proposed in this pull request?

Add check partition expressions is empty.

### Why are the changes needed?

We should keep `spark.range(1).hint("REPARTITION_BY_RANGE")` has default shuffle number instead of 1.

### Does this PR introduce _any_ user-facing change?

Yes.

### How was this patch tested?

Add test.

Closes #31074 from ulysses-you/SPARK-33806-FOLLOWUP.

Authored-by: ulysses-you <ulyssesyou18@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-06 17:22:14 -08:00
Dongjoon Hyun 8bb70bf0d6 [SPARK-34029][SQL][TESTS] Add OrcEncryptionSuite and FakeKeyProvider
### What changes were proposed in this pull request?

This PR aims to add a basis for columnar encryption test framework by add `OrcEncryptionSuite` and `FakeKeyProvider`.

Please note that we will improve more in both Apache Spark and Apache ORC in Apache Spark 3.2.0 timeframe.

### Why are the changes needed?

Apache ORC 1.6 supports columnar encryption.

### Does this PR introduce _any_ user-facing change?

No. This is for a test case.

### How was this patch tested?

Pass the newly added test suite.

Closes #31065 from dongjoon-hyun/SPARK-34029.

Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-06 12:59:47 -08:00
angerszhu c0d0dbabdb [SPARK-33934][SQL][FOLLOW-UP] Use SubProcessor's exit code as assert condition to fix flaky test
### What changes were proposed in this pull request?
Follow comment and fix. flaky test https://github.com/apache/spark/pull/30973#issuecomment-754852130.
This flaky test is similar as https://github.com/apache/spark/pull/30896

Some task's failed with root cause but in driver may return error without root cause , change. UT to check with status exit code since different root cause's exit code is not same.

### Why are the changes needed?
Fix flaky test

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Existed UT

Closes #31046 from AngersZhuuuu/SPARK-33934-FOLLOW-UP.

Lead-authored-by: angerszhu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-05 22:33:15 -08:00
Max Gekk b77d11dfd9 [SPARK-34011][SQL] Refresh cache in ALTER TABLE .. RENAME TO PARTITION
### What changes were proposed in this pull request?
1. Invoke `refreshTable()` from `AlterTableRenamePartitionCommand.run()` after partitions renaming. In particular, this re-creates the cache associated with the modified table.
2. Refresh the cache associated with tables from v2 table catalogs in the `ALTER TABLE .. RENAME TO PARTITION` command.

### Why are the changes needed?
This fixes the issues portrayed by the example:
```sql
spark-sql> CREATE TABLE tbl1 (col0 int, part0 int) USING parquet PARTITIONED BY (part0);
spark-sql> INSERT INTO tbl1 PARTITION (part0=0) SELECT 0;
spark-sql> INSERT INTO tbl1 PARTITION (part0=1) SELECT 1;
spark-sql> CACHE TABLE tbl1;
spark-sql> SELECT * FROM tbl1;
0	0
1	1
spark-sql> ALTER TABLE tbl1 PARTITION (part0=0) RENAME TO PARTITION (part=2);
spark-sql> SELECT * FROM tbl1;
0	0
1	1
```
The last query must not return `0	2` since `0  0` was renamed by previous command.

### Does this PR introduce _any_ user-facing change?
Yes. After the changes for the example above:
```sql
...
spark-sql> ALTER TABLE tbl1 PARTITION (part=0) RENAME TO PARTITION (part=2);
spark-sql> SELECT * FROM tbl1;
0	2
1	1
```

### How was this patch tested?
By running the affected test suite:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableRenamePartitionSuite"
```

Closes #31044 from MaxGekk/rename-partition-refresh-cache.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-01-06 11:19:44 +09:00
angerszhu e279ed3044 [SPARK-34012][SQL] Keep behavior consistent when conf spark.sql.legacy.parser.havingWithoutGroupByAsWhere is true with migration guide
### What changes were proposed in this pull request?
In https://github.com/apache/spark/pull/22696 we support HAVING without GROUP BY means global aggregate
But since we treat having as Filter before, in this way will cause a lot of analyze error, after https://github.com/apache/spark/pull/28294 we use `UnresolvedHaving` to instead `Filter` to solve such problem, but break origin logical about treat `SELECT 1 FROM range(10) HAVING true` as `SELECT 1 FROM range(10) WHERE true`   .
This PR fix this issue and add UT.

### Why are the changes needed?
Keep consistent behavior of migration guide.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
added UT

Closes #31039 from AngersZhuuuu/SPARK-25780-Follow-up.

Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
2021-01-06 08:48:24 +09:00
Max Gekk 122f8f0fdb [SPARK-33919][SQL][TESTS] Unify v1 and v2 SHOW NAMESPACES tests
### What changes were proposed in this pull request?
1. Port DS V2 tests from `DataSourceV2SQLSuite` to the base test suite `ShowNamespacesSuiteBase` to run those tests for v1 catalogs.
2. Port DS v1 tests from `DDLSuite` to `ShowNamespacesSuiteBase` to run the tests for v2 catalogs too.

### Why are the changes needed?
To improve test coverage.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
By running new test suites:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *ShowNamespacesSuite"
```

Closes #30937 from MaxGekk/unify-show-namespaces-tests.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-05 07:30:59 +00:00
tanel.kiis@gmail.com f252a9334e [SPARK-33935][SQL] Fix CBO cost function
### What changes were proposed in this pull request?

Changed the cost function in CBO to match documentation.

### Why are the changes needed?

The parameter `spark.sql.cbo.joinReorder.card.weight` is documented as:
```
The weight of cardinality (number of rows) for plan cost comparison in join reorder: rows * weight + size * (1 - weight).
```
The implementation in `JoinReorderDP.betterThan` does not match this documentaiton:
```
def betterThan(other: JoinPlan, conf: SQLConf): Boolean = {
      if (other.planCost.card == 0 || other.planCost.size == 0) {
        false
      } else {
        val relativeRows = BigDecimal(this.planCost.card) / BigDecimal(other.planCost.card)
        val relativeSize = BigDecimal(this.planCost.size) / BigDecimal(other.planCost.size)
        relativeRows * conf.joinReorderCardWeight +
          relativeSize * (1 - conf.joinReorderCardWeight) < 1
      }
    }
```

This different implementation has an unfortunate consequence:
given two plans A and B, both A betterThan B and B betterThan A might give the same results. This happes when one has many rows with small sizes and other has few rows with large sizes.

A example values, that have this fenomen with the default weight value (0.7):
A.card = 500, B.card = 300
A.size = 30, B.size = 80
Both A betterThan B and B betterThan A would have score above 1 and would return false.

This happens with several of the TPCDS queries.

The new implementation does not have this behavior.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

New and existing UTs

Closes #30965 from tanelk/SPARK-33935_cbo_cost_function.

Authored-by: tanel.kiis@gmail.com <tanel.kiis@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
2021-01-05 16:00:24 +09:00
Kent Yao f0ffe0cd65 [SPARK-33992][SQL] override transformUpWithNewOutput to add allowInvokingTransformsInAnalyzer
### What changes were proposed in this pull request?

In https://github.com/apache/spark/pull/29643, we move  the plan rewriting methods to QueryPlan. we need to override transformUpWithNewOutput to add allowInvokingTransformsInAnalyzer
 because it and resolveOperatorsUpWithNewOutput are called in the analyzer.
For example,

PaddingAndLengthCheckForCharVarchar could fail query when resolveOperatorsUpWithNewOutput
with
```logtalk
[info] - char/varchar resolution in sub query  *** FAILED *** (367 milliseconds)
[info]   java.lang.RuntimeException: This method should not be called in the analyzer
[info]   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.assertNotAnalysisRule(AnalysisHelper.scala:150)
[info]   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.assertNotAnalysisRule$(AnalysisHelper.scala:146)
[info]   at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.assertNotAnalysisRule(LogicalPlan.scala:29)
[info]   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown(AnalysisHelper.scala:161)
[info]   at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown$(AnalysisHelper.scala:160)
[info]   at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
[info]   at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
[info]   at org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$updateOuterReferencesInSubquery(QueryPlan.scala:267)
```
### Why are the changes needed?

trivial bugfix
### Does this PR introduce _any_ user-facing change?

no
### How was this patch tested?

new tests

Closes #31013 from yaooqinn/SPARK-33992.

Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-05 05:34:11 +00:00
Terry Kim 15a863fd54 [SPARK-34001][SQL][TESTS] Remove unused runShowTablesSql() in DataSourceV2SQLSuite.scala
### What changes were proposed in this pull request?

After #30287, `runShowTablesSql()` in `DataSourceV2SQLSuite.scala` is no longer used. This PR removes the unused method.

### Why are the changes needed?

To remove unused method.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Existing test.

Closes #31022 from imback82/33382-followup.

Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 21:32:49 -08:00
Terry Kim 6b00fdc756 [SPARK-33998][SQL] Provide an API to create an InternalRow in V2CommandExec
### What changes were proposed in this pull request?

There are many v2 commands such as `SHOW TABLES`, `DESCRIBE TABLE`, etc. that require creating `InternalRow`s. Currently, the code to create `InternalRow`s are duplicated across many commands and it can be moved into `V2CommandExec` to remove duplicate code.

### Why are the changes needed?

To clean up duplicate code.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Existing test since this is just refactoring.

Closes #31020 from imback82/refactor_v2_command.

Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-05 05:32:36 +00:00
Chongguang LIU 976e97a80d [SPARK-33794][SQL] NextDay expression throw runtime IllegalArgumentException when receiving invalid input under ANSI mode
### What changes were proposed in this pull request?

Instead of returning NULL, the next_day function throws runtime IllegalArgumentException when ansiMode is enable and receiving invalid input of the dayOfWeek parameter.

### Why are the changes needed?

For ansiMode.

### Does this PR introduce _any_ user-facing change?

Yes.
When spark.sql.ansi.enabled = true, the next_day function will throw IllegalArgumentException when receiving invalid input of the dayOfWeek parameter.
When spark.sql.ansi.enabled = false, same behaviour as before.

### How was this patch tested?

Ansi mode is tested with existing tests.
End-to-end tests have been added.

Closes #30807 from chongguang/SPARK-33794.

Authored-by: Chongguang LIU <chongguang.liu@laposte.fr>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-05 05:20:16 +00:00
tanel.kiis@gmail.com bb6d6b5602 [SPARK-33964][SQL] Combine distinct unions in more cases
### What changes were proposed in this pull request?

Added the `RemoveNoopOperators` rule to optimization batch `Union`.  Also made sure that the `RemoveNoopOperators` would be idempotent.

### Why are the changes needed?

In several TPCDS queries the `CombineUnions` rule does not manage to combine unions, because they have noop `Project`s between them.
The `Project`s will be removed by `RemoveNoopOperators`, but by then `ReplaceDistinctWithAggregate` has been applied and there are aggregates between the unions. Adding a copy of `RemoveNoopOperators` earlier in the optimization chain allows `CombineUnions` to work on more queries.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

New UTs and the output of `PlanStabilitySuite`

Closes #30996 from tanelk/SPARK-33964_combine_unions.

Authored-by: tanel.kiis@gmail.com <tanel.kiis@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-01-05 11:01:31 +09:00
Max Gekk 84c1f43669 [SPARK-33987][SQL] Refresh cache in v2 ALTER TABLE .. DROP PARTITION
### What changes were proposed in this pull request?
1. Refresh the cache associated with tables from v2 table catalogs in the `ALTER TABLE .. DROP PARTITION` command.
2. Port the test for v1 catalogs to the base suite to run it for v2 table catalog.

### Why are the changes needed?
The changes fix incorrect query results from cached V2 table altered by `ALTER TABLE .. DROP PARTITION`, see the added test and SPARK-33987.

### Does this PR introduce _any_ user-facing change?
Yes, it could if users have v2 table catalogs.

### How was this patch tested?
By running unified tests for `ALTER TABLE .. DROP PARTITION`:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableDropPartitionSuite"
```

Closes #31017 from MaxGekk/drop-partition-refresh-cache-v2.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 15:00:48 -08:00
Kent Yao ac4651a7d1 [SPARK-33980][SS] Invalidate char/varchar in spark.readStream.schema
### What changes were proposed in this pull request?

invalidate char/varchar in `spark.readStream.schema` just like what we've done for `spark.read.schema` in da72b87374

### Why are the changes needed?

bugfix, char/varchar is only for table schema while `spark.sql.legacy.charVarcharAsString=false`

### Does this PR introduce _any_ user-facing change?

yes, char/varchar will fail to define ss readers when `spark.sql.legacy.charVarcharAsString=false`

### How was this patch tested?

new tests

Closes #31003 from yaooqinn/SPARK-33980.

Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 12:59:45 -08:00
Takeshi Yamamuro 414d323d6c [SPARK-33988][SQL][TEST] Add an option to enable CBO in TPCDSQueryBenchmark
### What changes were proposed in this pull request?

This PR intends to add a new option `--cbo` to enable CBO in TPCDSQueryBenchmark. I think this option is useful so as to monitor performance changes with CBO enabled.

### Why are the changes needed?

To monitor performance chaneges with CBO enabled.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Manually checked.

Closes #31011 from maropu/AddOptionForCBOInTPCDSBenchmark.

Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 10:31:20 -08:00
Max Gekk fc3f22645e [SPARK-33990][SQL][TESTS] Remove partition data by v2 ALTER TABLE .. DROP PARTITION
### What changes were proposed in this pull request?
Remove partition data by `ALTER TABLE .. DROP PARTITION` in V2 table catalog used in tests.

### Why are the changes needed?
This is a bug fix. Before the fix, `ALTER TABLE .. DROP PARTITION` does not remove the data belongs to the dropped partition. As a consequence of that, the `select` query returns removed data.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
By running tests suites for v1 and v2 catalogs:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableDropPartitionSuite"
```

Closes #31014 from MaxGekk/fix-drop-partition-v2.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 10:26:39 -08:00
Terry Kim ddc0d5148a [SPARK-33875][SQL] Implement DESCRIBE COLUMN for v2 tables
### What changes were proposed in this pull request?

This PR proposes to implement `DESCRIBE COLUMN` for v2 tables.

Note that `isExnteded` option is not implemented in this PR.

### Why are the changes needed?

Parity with v1 tables.

### Does this PR introduce _any_ user-facing change?

Yes, now, `DESCRIBE COLUMN` works for v2 tables.
```scala
sql("CREATE TABLE testcat.tbl (id bigint, data string COMMENT 'hello') USING foo")
sql("DESCRIBE testcat.tbl data").show
```
```
+---------+----------+
|info_name|info_value|
+---------+----------+
| col_name|      data|
|data_type|    string|
|  comment|     hello|
+---------+----------+
```

Before this PR, the command would fail with: `Describing columns is not supported for v2 tables.`

### How was this patch tested?

Added new test.

Closes #30881 from imback82/describe_col_v2.

Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-04 16:14:33 +00:00
Dongjoon Hyun 271c4f6e00 [SPARK-33978][SQL] Support ZSTD compression in ORC data source
### What changes were proposed in this pull request?

This PR aims to support ZSTD compression in ORC data source.

### Why are the changes needed?

Apache ORC 1.6 supports ZSTD compression to generate more compact files and save the storage cost.
- https://issues.apache.org/jira/browse/ORC-363

**BEFORE**
```scala
scala> spark.range(10).write.option("compression", "zstd").orc("/tmp/zstd")
java.lang.IllegalArgumentException: Codec [zstd] is not available. Available codecs are uncompressed, lzo, snappy, zlib, none.
```

**AFTER**
```scala
scala> spark.range(10).write.option("compression", "zstd").orc("/tmp/zstd")
```

```bash
$ orc-tools meta /tmp/zstd
Processing data file file:/tmp/zstd/part-00011-a63d9a17-456f-42d3-87a1-d922112ed28c-c000.orc [length: 230]
Structure for file:/tmp/zstd/part-00011-a63d9a17-456f-42d3-87a1-d922112ed28c-c000.orc
File Version: 0.12 with ORC_14
Rows: 1
Compression: ZSTD
Compression size: 262144
Calendar: Julian/Gregorian
Type: struct<id:bigint>

Stripe Statistics:
  Stripe 1:
    Column 0: count: 1 hasNull: false
    Column 1: count: 1 hasNull: false bytesOnDisk: 6 min: 9 max: 9 sum: 9

File Statistics:
  Column 0: count: 1 hasNull: false
  Column 1: count: 1 hasNull: false bytesOnDisk: 6 min: 9 max: 9 sum: 9

Stripes:
  Stripe: offset: 3 data: 6 rows: 1 tail: 35 index: 35
    Stream: column 0 section ROW_INDEX start: 3 length 11
    Stream: column 1 section ROW_INDEX start: 14 length 24
    Stream: column 1 section DATA start: 38 length 6
    Encoding column 0: DIRECT
    Encoding column 1: DIRECT_V2

File length: 230 bytes
Padding length: 0 bytes
Padding ratio: 0%

User Metadata:
  org.apache.spark.version=3.2.0
```

### Does this PR introduce _any_ user-facing change?

Yes, this is a new feature.

### How was this patch tested?

Pass the newly added test case.

Closes #31002 from dongjoon-hyun/SPARK-33978.

Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-04 00:54:47 -08:00
Hoa 0b647fe69c [SPARK-33888][SQL] JDBC SQL TIME type represents incorrectly as TimestampType, it should be physical Int in millis
### What changes were proposed in this pull request?
JDBC SQL TIME type represents incorrectly as TimestampType, we change it to be physical Int in millis for now.

### Why are the changes needed?
Currently, for JDBC, SQL TIME type represents incorrectly as Spark TimestampType. This should be represent as physical int in millis Represents a time of day, with no reference to a particular calendar, time zone or date, with a precision of one millisecond. It stores the number of milliseconds after midnight, 00:00:00.000.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?

Close #30902

Closes #30902 from saikocat/SPARK-33888.

Lead-authored-by: Hoa <hoameomu@gmail.com>
Co-authored-by: Hoa <saikocatz@gmail.com>
Co-authored-by: Duc Hoa, Nguyen <hoa.nd@teko.vn>
Co-authored-by: Duc Hoa, Nguyen <hoameomu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-04 06:53:12 +00:00
angerszhu adac633f93 [SPARK-33934][SQL] Add SparkFile's root dir to env property PATH
### What changes were proposed in this pull request?
In hive we always use
```
add file /path/to/script.py;
select transform(col1, col2, ..)
using 'script.py' as (col1, col2, ...)
from ...
```
Since in spark we wrapper script command with `/bash/bin -c`, in this case we will throw `script.py command not found`.

This pr add a SparkFile's root dir path to execution env property `PATH`, then  sub-processor will find `scrip.py` as program under `PATH`.

### Why are the changes needed?
Support SQL migration form Hive to Spark.

### Does this PR introduce _any_ user-facing change?
User can direct use script file name as program in script transform SQL.

```
add file /path/to/script.py;
select transform(col1, col2, ..)
using 'script.py' as (col1, col2, ...)
from ...
```
### How was this patch tested?
UT

Closes #30973 from AngersZhuuuu/SPARK-33934.

Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2021-01-04 15:46:49 +09:00
Max Gekk 67195d0d97 [SPARK-33950][SQL] Refresh cache in v1 ALTER TABLE .. DROP PARTITION
### What changes were proposed in this pull request?
Invoke `refreshTable()` from `AlterTableDropPartitionCommand.run()` after partitions dropping. In particular, this invalidates the cache associated with the modified table.

### Why are the changes needed?
This fixes the issues portrayed by the example:
```sql
spark-sql> CREATE TABLE tbl1 (col0 int, part0 int) USING parquet PARTITIONED BY (part0);
spark-sql> INSERT INTO tbl1 PARTITION (part0=0) SELECT 0;
spark-sql> INSERT INTO tbl1 PARTITION (part0=1) SELECT 1;
spark-sql> CACHE TABLE tbl1;
spark-sql> SELECT * FROM tbl1;
0	0
1	1
spark-sql> ALTER TABLE tbl1 DROP PARTITION (part0=0);
spark-sql> SELECT * FROM tbl1;
0	0
1	1
```
The last query must not return `0	0` since it was deleted by previous command.

### Does this PR introduce _any_ user-facing change?
Yes. After the changes for the example above:
```sql
...
spark-sql> ALTER TABLE tbl1 DROP PARTITION (part0=0);
spark-sql> SELECT * FROM tbl1;
1	1
```

### How was this patch tested?
By running the affected test suite:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableDropPartitionSuite"
```

Closes #30983 from MaxGekk/drop-partition-refresh-cache.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-01-04 04:11:39 +00:00
Liang-Chi Hsieh 963c60fe49 [SPARK-33955][SS] Add latest offsets to source progress
### What changes were proposed in this pull request?

This patch proposes to add latest offset to source progress for streaming queries.

### Why are the changes needed?

Currently we record start and end offsets per source in streaming process. Latest offset is an important information for streaming process but the progress lacks of this info. We can use it to track the process lag and adjust streaming queries. We should add latest offset to source progress.

### Does this PR introduce _any_ user-facing change?

Yes, for new metric about latest source offset in source progress.

### How was this patch tested?

Unit test. Manually test in Spark cluster:

```
    "description" : "KafkaV2[Subscribe[page_view_events]]",
    "startOffset" : {
      "page_view_events" : {
        "2" : 582370921,
        "4" : 391910836,
        "1" : 631009201,
        "3" : 406601346,
        "0" : 195799112
      }
    },
    "endOffset" : {
      "page_view_events" : {
        "2" : 583764414,
        "4" : 392338002,
        "1" : 632183480,
        "3" : 407101489,
        "0" : 197304028
      }
    },
    "latestOffset" : {
      "page_view_events" : {
        "2" : 589852545,
        "4" : 394204277,
        "1" : 637313869,
        "3" : 409286602,
        "0" : 203878962
      }
    },
    "numInputRows" : 4999997,
    "inputRowsPerSecond" : 29287.70501405811,
```

Closes #30988 from viirya/latest-offset.

Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2021-01-03 01:31:38 -08:00
Kent Yao ed9f728801 [SPARK-33944][SQL] Incorrect logging for warehouse keys in SharedState options
### What changes were proposed in this pull request?

While using SparkSession's initial options to generate the sharable Spark conf and Hadoop conf in ShardState, we shall put the log in the codeblock that the warehouse keys being handled.

### Why are the changes needed?

bugfix, rm ambiguous log when setting spark.sql.warehouse.dir in SparkSession.builder.config, but only warn setting hive.metastore.warehouse.dir
### Does this PR introduce _any_ user-facing change?

no
### How was this patch tested?

 new tests

Closes #30978 from yaooqinn/SPARK-33944.

Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-12-31 13:20:31 -08:00
angerszhu 771c538620 [SPARK-33084][SQL][TESTS][FOLLOW-UP] Fix Scala 2.13 UT failure
### What changes were proposed in this pull request?
Fix UT according to  https://github.com/apache/spark/pull/29966#issuecomment-752830046

Change StructType construct from
```
def inputSchema: StructType = StructType(StructField("inputColumn", LongType) :: Nil)
```
to
```
  def inputSchema: StructType = new StructType().add("inputColumn", LongType)
```
The whole udf class is :

```
package org.apache.spark.examples.sql

import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction}
import org.apache.spark.sql.types._
import org.apache.spark.sql.Row

class Spark33084 extends UserDefinedAggregateFunction {
  // Data types of input arguments of this aggregate function
  def inputSchema: StructType = new StructType().add("inputColumn", LongType)

  // Data types of values in the aggregation buffer
  def bufferSchema: StructType =
    new StructType().add("sum", LongType).add("count", LongType)
  // The data type of the returned value
  def dataType: DataType = DoubleType
  // Whether this function always returns the same output on the identical input
  def deterministic: Boolean = true
  // Initializes the given aggregation buffer. The buffer itself is a `Row` that in addition to
  // standard methods like retrieving a value at an index (e.g., get(), getBoolean()), provides
  // the opportunity to update its values. Note that arrays and maps inside the buffer are still
  // immutable.
  def initialize(buffer: MutableAggregationBuffer): Unit = {
    buffer(0) = 0L
    buffer(1) = 0L
  }
  // Updates the given aggregation buffer `buffer` with new input data from `input`
  def update(buffer: MutableAggregationBuffer, input: Row): Unit = {
    if (!input.isNullAt(0)) {
      buffer(0) = buffer.getLong(0) + input.getLong(0)
      buffer(1) = buffer.getLong(1) + 1
    }
  }
  // Merges two aggregation buffers and stores the updated buffer values back to `buffer1`
  def merge(buffer1: MutableAggregationBuffer, buffer2: Row): Unit = {
    buffer1(0) = buffer1.getLong(0) + buffer2.getLong(0)
    buffer1(1) = buffer1.getLong(1) + buffer2.getLong(1)
  }
  // Calculates the final result
  def evaluate(buffer: Row): Double = buffer.getLong(0).toDouble / buffer.getLong(1)
}
```

### Why are the changes needed?
Fix UT for scala 2.13

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Existed UT

Closes #30980 from AngersZhuuuu/spark-33084-followup.

Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-12-31 13:18:31 -08:00
Liang-Chi Hsieh f38265ddda [SPARK-33907][SQL] Only prune columns of from_json if parsing options is empty
### What changes were proposed in this pull request?

As a follow-up task to SPARK-32958, this patch takes safer approach to only prune columns from JsonToStructs if the parsing option is empty. It is to avoid unexpected behavior change regarding parsing.

This patch also adds a few e2e tests to make sure failfast parsing behavior is not changed.

### Why are the changes needed?

It is to avoid unexpected behavior change regarding parsing.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Unit test.

Closes #30970 from viirya/SPARK-33907-3.2.

Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
2020-12-30 09:57:15 -08:00
gengjiaan ba974ea8e4 [SPARK-30789][SQL] Support (IGNORE | RESPECT) NULLS for LEAD/LAG/NTH_VALUE/FIRST_VALUE/LAST_VALUE
### What changes were proposed in this pull request?
All of `LEAD`/`LAG`/`NTH_VALUE`/`FIRST_VALUE`/`LAST_VALUE` should support IGNORE NULLS | RESPECT NULLS. For example:
```
LEAD (value_expr [, offset ])
[ IGNORE NULLS | RESPECT NULLS ]
OVER ( [ PARTITION BY window_partition ] ORDER BY window_ordering )
```

```
LAG (value_expr [, offset ])
[ IGNORE NULLS | RESPECT NULLS ]
OVER ( [ PARTITION BY window_partition ] ORDER BY window_ordering )
```

```
NTH_VALUE (expr, offset)
[ IGNORE NULLS | RESPECT NULLS ]
OVER
( [ PARTITION BY window_partition ]
[ ORDER BY window_ordering
 frame_clause ] )
```

The mainstream database or engine supports this syntax contains:
**Oracle**
https://docs.oracle.com/en/database/oracle/oracle-database/19/sqlrf/NTH_VALUE.html#GUID-F8A0E88C-67E5-4AA6-9515-95D03A7F9EA0

**Redshift**
https://docs.aws.amazon.com/redshift/latest/dg/r_WF_NTH.html

**Presto**
https://prestodb.io/docs/current/functions/window.html

**DB2**
https://www.ibm.com/support/knowledgecenter/SSGU8G_14.1.0/com.ibm.sqls.doc/ids_sqs_1513.htm

**Teradata**
https://docs.teradata.com/r/756LNiPSFdY~4JcCCcR5Cw/GjCT6l7trjkIEjt~7Dhx4w

**Snowflake**
https://docs.snowflake.com/en/sql-reference/functions/lead.html
https://docs.snowflake.com/en/sql-reference/functions/lag.html
https://docs.snowflake.com/en/sql-reference/functions/nth_value.html
https://docs.snowflake.com/en/sql-reference/functions/first_value.html
https://docs.snowflake.com/en/sql-reference/functions/last_value.html

**Exasol**
https://docs.exasol.com/sql_references/functions/alphabeticallistfunctions/lead.htm
https://docs.exasol.com/sql_references/functions/alphabeticallistfunctions/lag.htm
https://docs.exasol.com/sql_references/functions/alphabeticallistfunctions/nth_value.htm
https://docs.exasol.com/sql_references/functions/alphabeticallistfunctions/first_value.htm
https://docs.exasol.com/sql_references/functions/alphabeticallistfunctions/last_value.htm

### Why are the changes needed?
Support `(IGNORE | RESPECT) NULLS` for `LEAD`/`LAG`/`NTH_VALUE`/`FIRST_VALUE`/`LAST_VALUE `is very useful.

### Does this PR introduce _any_ user-facing change?
Yes.

### How was this patch tested?
Jenkins test

Closes #30943 from beliefer/SPARK-30789.

Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: beliefer <beliefer@163.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-30 13:14:31 +00:00
Max Gekk 2afd1fb492 [SPARK-33904][SQL] Recognize spark_catalog in saveAsTable() and insertInto()
### What changes were proposed in this pull request?
In the `saveAsTable()` and `insertInto()` methods of `DataFrameWriter`, recognize `spark_catalog` as the default session catalog in table names.

### Why are the changes needed?
1. To simplify writing of unified v1 and v2 tests
2. To improve Spark SQL user experience. `insertInto()` should have feature parity with the `INSERT INTO` sql command. Currently, `insertInto()` fails on a table from a namespace in `spark_catalog`:
```scala
scala> sql("CREATE NAMESPACE spark_catalog.ns")
scala> Seq(0).toDF().write.saveAsTable("spark_catalog.ns.tbl")
org.apache.spark.sql.AnalysisException: Couldn't find a catalog to handle the identifier spark_catalog.ns.tbl.
  at org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:629)
  ... 47 elided
scala> Seq(0).toDF().write.insertInto("spark_catalog.ns.tbl")
org.apache.spark.sql.AnalysisException: Couldn't find a catalog to handle the identifier spark_catalog.ns.tbl.
  at org.apache.spark.sql.DataFrameWriter.insertInto(DataFrameWriter.scala:498)
  ... 47 elided
```
but `INSERT INTO` succeed:
```sql
spark-sql> create table spark_catalog.ns.tbl (c int);
spark-sql> insert into spark_catalog.ns.tbl select 0;
spark-sql> select * from spark_catalog.ns.tbl;
0
```

### Does this PR introduce _any_ user-facing change?
Yes. After the changes for the example above:
```scala
scala> Seq(0).toDF().write.saveAsTable("spark_catalog.ns.tbl")
scala> Seq(1).toDF().write.insertInto("spark_catalog.ns.tbl")
scala> spark.table("spark_catalog.ns.tbl").show(false)
+-----+
|value|
+-----+
|0    |
|1    |
+-----+
```

### How was this patch tested?
By running the affected test suites:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.ShowPartitionsSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.FileFormatWriterSuite"
```

Closes #30919 from MaxGekk/insert-into-spark_catalog.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-30 07:56:34 +00:00
Max Gekk 0eb4961ca8 [SPARK-33926][SQL] Improve the error message from resolving of v1 database name
### What changes were proposed in this pull request?
1. Replace `SessionCatalogAndNamespace` by `DatabaseInSessionCatalog` in resolving database name from v1 session catalog.
2. Throw more precise errors from `DatabaseInSessionCatalog`
3. Fix expected error messages in `v1.ShowTablesSuiteBase`

Closes #30947

### Why are the changes needed?
Current error message "multi-part identifier cannot be empty" may confuse users. And this error message is just a consequence of "incorrectly" applied an implicit class. For example, `SHOW TABLES IN spark_catalog`:

1. Spark cuts off `spark_catalog` from namespaces in `SessionCatalogAndNamespace`, so, `ns == Seq.empty` here: 0617dfce7b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala (L365)
2. Then `ns.length != 1` is `true` and Spark tries to raise the exception at 0617dfce7b/sql/core/src/main/scala/org/apache/spark/sql/catalyst/analysis/ResolveSessionCatalog.scala (L367)
3.  ... but `ns.quoted` triggers implicit wrapping `Seq.empty` by `MultipartIdentifierHelper`, and hit to the second check `if (parts.isEmpty)` at 156704ba0d/sql/catalyst/src/main/scala/org/apache/spark/sql/connector/catalog/CatalogV2Implicits.scala (L120-L122)

So, Spark throws the exception at third step instead of `new AnalysisException(s"The database name is not valid: $quoted")` on the second step. And even on the second step, the exception doesn't show actual reason as it is pretty generic.

### Does this PR introduce _any_ user-facing change?
Yes in the case of v1 DDL commands when a database is not specified or nested databases is set.

### How was this patch tested?
By running the affected test suites:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *DDLSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *ShowTablesSuite"
```

Closes #30963 from MaxGekk/database-in-session-catalog.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-30 07:52:34 +00:00
angerszhu aadda4b561 [SPARK-33930][SQL] Script Transform default FIELD DELIMIT should be \u0001 for no serde
### What changes were proposed in this pull request?
For same SQL
```
SELECT TRANSFORM(a, b, c, null)
ROW FORMAT DELIMITED
USING 'cat'
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '&'
FROM (select 1 as a, 2 as b, 3  as c) t
```
In hive:
```
hive> SELECT TRANSFORM(a, b, c, null)
    > ROW FORMAT DELIMITED
    > USING 'cat'
    > ROW FORMAT DELIMITED
    > FIELDS TERMINATED BY '&'
    > FROM (select 1 as a, 2 as b, 3  as c) t;
OK
123\N	NULL
Time taken: 14.519 seconds, Fetched: 1 row(s)
hive> packet_write_wait: Connection to 10.191.58.100 port 32200: Broken pipe
```

In Spark
```
Spark master: local[*], Application Id: local-1609225830376
spark-sql> SELECT TRANSFORM(a, b, c, null)
         > ROW FORMAT DELIMITED
         > USING 'cat'
         > ROW FORMAT DELIMITED
         > FIELDS TERMINATED BY '&'
         > FROM (select 1 as a, 2 as b, 3  as c) t;
1	2	3	null	NULL
Time taken: 4.297 seconds, Fetched 1 row(s)
spark-sql>
```
We should keep same. Change default ROW FORMAT FIELD DELIMIT to `\u0001`

In hive default value is '1' to char is '\u0001'
```
bucket_count -1
column.name.delimiter ,
columns
columns.comments
columns.types
file.inputformat org.apache.hadoop.hive.ql.io.NullRowsInputFormat
```

### Why are the changes needed?
Keep same behavior with hive

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Added UT

Closes #30958 from AngersZhuuuu/SPARK-33930.

Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-12-29 23:26:27 +09:00
Max Gekk e0d2ffec31 [SPARK-33859][SQL] Support V2 ALTER TABLE .. RENAME PARTITION
### What changes were proposed in this pull request?
1. Add `renamePartition()` to the `SupportsPartitionManagement`
2. Implement `renamePartition()` in `InMemoryPartitionTable`
3. Add v2 execution node `AlterTableRenamePartitionExec`
4. Resolve the logical node `AlterTableRenamePartition` to `AlterTableRenamePartitionExec` for v2 tables that support `SupportsPartitionManagement`
5. Move v1 tests to the base suite `org.apache.spark.sql.execution.command.AlterTableRenamePartitionSuiteBase` to run them for v2 table catalogs.

### Why are the changes needed?
To have feature parity with Datasource V1.

### Does this PR introduce _any_ user-facing change?
Yes

### How was this patch tested?
By running the unified tests:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableRenamePartitionSuite"
```

Closes #30935 from MaxGekk/alter-table-rename-partition-v2.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-29 13:29:48 +00:00
Liang-Chi Hsieh f9fe742442 [SPARK-32968][SQL] Prune unnecessary columns from CsvToStructs
### What changes were proposed in this pull request?

This patch proposes to do column pruning for CsvToStructs expression if we only require some fields from it.

### Why are the changes needed?

`CsvToStructs` takes a schema parameter used to tell CSV Parser what fields are needed to parse. If `CsvToStructs` is followed by GetStructField. We can prune the schema to only parse certain field.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Unit test

Closes #30912 from viirya/SPARK-32968.

Lead-authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Co-authored-by: Hyukjin Kwon <gurwls223@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-12-29 21:37:17 +09:00
Max Gekk 379afcd2ce [SPARK-33924][SQL][TESTS] Preserve partition metadata by INSERT INTO in v2 table catalog
### What changes were proposed in this pull request?
For `InMemoryPartitionTable` used in tests, set empty partition metadata only when a partition doesn't exists.

### Why are the changes needed?
This bug fix is needed to use `INSERT INTO .. PARTITION` in other tests.

### Does this PR introduce _any_ user-facing change?
No. It affects only the v2 table catalog used in tests.

### How was this patch tested?
Added new UT to `DataSourceV2SQLSuite`, and run the affected test suite by:
```
$ build/sbt -Phive -Phive-thriftserver "test:testOnly org.apache.spark.sql.connector.DataSourceV2SQLSuite"
```

Closes #30952 from MaxGekk/fix-insert-into-partition-v2.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-29 06:49:26 +00:00
Max Gekk 0617dfce7b [SPARK-33899][SQL] Fix assert failure in v1 SHOW TABLES/VIEWS on spark_catalog
### What changes were proposed in this pull request?
Remove `assert(ns.nonEmpty)` in `ResolveSessionCatalog` for:
- `SHOW TABLES`
- `SHOW TABLE EXTENDED`
- `SHOW VIEWS`

### Why are the changes needed?
Spark SQL shouldn't fail with internal assert failures even for invalid user inputs. For instance:
```sql
spark-sql> show tables in spark_catalog;
20/12/24 11:19:46 ERROR SparkSQLDriver: Failed in [show tables in spark_catalog]
java.lang.AssertionError: assertion failed
	at scala.Predef$.assert(Predef.scala:208)
	at org.apache.spark.sql.catalyst.analysis.ResolveSessionCatalog$$anonfun$apply$1.applyOrElse(ResolveSessionCatalog.scala:366)
	at org.apache.spark.sql.catalyst.analysis.ResolveSessionCatalog$$anonfun$apply$1.applyOrElse(ResolveSessionCatalog.scala:49)
	at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.$anonfun$resolveOperatorsUp$3(AnalysisHelper.scala:90)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:73)
```

### Does this PR introduce _any_ user-facing change?
Yes. After the changes, for the example above:
```sql
spark-sql> show tables in spark_catalog;
Error in query: multi-part identifier cannot be empty.
```

### How was this patch tested?
Added new UT to `v1/ShowTablesSuite`.

Closes #30915 from MaxGekk/remove-assert-ns-nonempty.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-28 09:07:21 +00:00
angerszhu fc508d1898 [SPARK-32685][SQL] When specify serde, default filed.delim is '\t'
### What changes were proposed in this pull request?
In hive script transform, when we use specified serde, the `filed.delim` is '\t'
![image](https://user-images.githubusercontent.com/46485123/103187960-7dd77800-4901-11eb-8241-f4636e66fbc8.png)
And change to other serde and explain query plan, `filed.delim` is same.

In spark current code, the result is as below:
![image](https://user-images.githubusercontent.com/46485123/103187999-95aefc00-4901-11eb-9850-5c385000b78c.png)

We should keep same as hive.

Notic:
the result's NULL value is   different is another issue  https://issues.apache.org/jira/browse/SPARK-32684

### Why are the changes needed?
Keep same with hive serde

### Does this PR introduce _any_ user-facing change?
In script transform, is not specified,  `field.delim` keep same with hive as `\t`

### How was this patch tested?
UT added

Closes #30942 from AngersZhuuuu/SPARK-32685.

Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-28 08:23:01 +00:00
yi.wu 00fa49aeaa [SPARK-33923][SQL][TESTS] Fix some tests with AQE enabled
### What changes were proposed in this pull request?

* Remove the explicit AQE disable confs
* Use `AdaptiveSparkPlanHelper` to check plans
* No longer extending `DisableAdaptiveExecutionSuite` for `BucketedReadSuite` but only disable AQE for two certain tests there.

### Why are the changes needed?

Some tests that are fixed in https://github.com/apache/spark/pull/30655 doesn't really require AQE off.  Instead, they could use `AdaptiveSparkPlanHelper` to pass when AQE on. It's better to run tests with AQE on since we've turned it on by default.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Pass all tests and the updated tests.

Closes #30941 from Ngone51/SPARK-33680-follow-up.

Authored-by: yi.wu <yi.wu@databricks.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-12-28 00:03:45 -08:00
Liang-Chi Hsieh c75f779fd7 [SPARK-33827][SS] Unload inactive state store as soon as possible
### What changes were proposed in this pull request?

This patch proposes to unload inactive state store as soon as possible. The timing of unload inactive state stores, happens when we get to load active state store provider at executors. At the time, state store coordinator will return back the state store provider list including loaded stores that are already loaded by other executors in new batch. Each state store provider in the list will go to unload.

### Why are the changes needed?

Per the discussion at #30770, it makes sense to me we should unload inactive state store asap. Now we run a maintenance task periodically to unload inactive state stores. So there will be some delays between a state store becomes inactive and it is unloaded.

However, we can force Spark to always allocate a state store to same executor, by using task locality configuration. This can reduce the possibility to have inactive state store.

Normally, with locality configuration, we might not able to see inactive state store generally. There is still chance an executor can be failed and reallocated, but in this case, inactive state store is also lost too. So it is not an issue.

Making driver-executor bi-directional for unloading inactive state store looks non-trivial, and seems to me, it is not worth, after considering what we can do with locality.

This proposes a simpler but effective approach. We can check if loaded state store is already loaded at other executor during reporting active state store to the coordinator. If so, it means the loaded store is inactive now, and it is going to be unload by the next maintenance task. Then we unload that store immediately.

How do we make sure the loaded state store in previous batch is loaded at other executor in this batch before reporting in this executor? With task locality and preferred location, once an executor is ready to be scheduled, Spark should assign the state store provider previously loaded at the executor. So when this executor gets a new assignment other than previously loaded state store, it means the previously loaded one is already assigned to other executor.

There is still a delay between the state store is loaded at other executor, and unloading it when reporting active state store at this executor. But it should be minimized now. And there won't be multiple state store belonging to same operator are loaded at the same time at one single executor, because once the executor reports any active store, it will unload all inactive stores. This should not be an issue IMHO.

This is a minimal change to unload inactive state store asap without significant change.

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?

Unit test.

Closes #30827 from viirya/SPARK-33827.

Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Jungtaek Lim <kabhwan.opensource@gmail.com>
2020-12-28 16:52:56 +09:00
Max Gekk 4a61fc1a92 [SPARK-33914][SQL][DOCS] Describe the structure of unified DS v1 and v2 tests
### What changes were proposed in this pull request?
Add comments for the unified datasource tests, describe what kind of tests they contain, and put refs to other test suits.

### Why are the changes needed?
To improve code maintenance.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
By running `./dev/scalastyle`.

Closes #30929 from MaxGekk/doc-unified-tests.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-28 07:03:29 +00:00
Kent Yao 3fdbc48373 [SPARK-33901][SQL] Fix Char and Varchar display error after DDLs
### What changes were proposed in this pull request?

After CTAS / CREATE TABLE LIKE / CVAS/ alter table add columns, the target tables will display string instead of char/varchar

### Why are the changes needed?

bugfix

### Does this PR introduce _any_ user-facing change?

no
### How was this patch tested?

new tests

Closes #30918 from yaooqinn/SPARK-33901.

Lead-authored-by: Kent Yao <yao@apache.org>
Co-authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-28 06:48:27 +00:00
yangjie01 1be9e7e40b [SPAKR-33801][CORE][SQL] Fix compilation warnings about 'Unicode escapes in triple quoted strings are deprecated'
### What changes were proposed in this pull request?
There are total 15 compilation warnings about `Unicode escapes in triple quoted strings are deprecated` in Spark code now:
```
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2930: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2931: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2932: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2933: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2934: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2935: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2936: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/core/src/main/scala/org/apache/spark/util/Utils.scala:2937: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/csv/CSVExprUtils.scala:82: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/csv/CSVExprUtilsSuite.scala:32: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/csv/CSVExprUtilsSuite.scala:79: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/parser/ParserUtilsSuite.scala:97: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/parser/ParserUtilsSuite.scala:101: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonParsingOptionsSuite.scala:76: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
[WARNING] /spark-source/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/json/JsonParsingOptionsSuite.scala:83: Unicode escapes in triple quoted strings are deprecated, use the literal character instead
```

This pr try to fix these warnnings.

### Why are the changes needed?
Cleanup compilation warnings about `Unicode escapes in triple quoted strings are deprecated`

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Pass the Jenkins or GitHub Action

Closes #30926 from LuciferYang/SPARK-33801.

Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-12-28 15:29:09 +09:00
yangjie01 e6f019836c [SPARK-33532][SQL] Add comments to a unreachable branch in SpecificParquetRecordReaderBase.initialize method
### What changes were proposed in this pull request?
This pr mainly adds a comment for the 'rowgroupoffsets! = null' branch in `SpecificParquetRecordReaderBase.init(InputSplit, TaskAttemptContext)` to indicate that spark read parquet process will not enter this branch after SPARK-13883 and SPARK-13989.  It is not deleted because PARQUET-131 wants to move `SpecificParquetRecordReaderBase` into the parquet-mr project.

### Why are the changes needed?
Add a useful comment.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Pass the Jenkins or GitHub Action

Closes #30484 from LuciferYang/SPARK-33532.

Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-12-28 14:07:50 +09:00
yangjie01 37ae0a6086 [SPARK-33560][TEST-MAVEN][BUILD] Add "unused-import" check to Maven compilation process
### What changes were proposed in this pull request?

Similar to SPARK-33441, this pr add `unused-import` check to Maven compilation process. After this pr `unused-import` will trigger Maven compilation error.

For Scala 2.13 profile, this pr also left TODO(SPARK-33499) similar to SPARK-33441 because `scala.language.higherKinds` no longer needs to be imported explicitly since Scala 2.13.1

### Why are the changes needed?
Let Maven build also check for unused imports as compilation error.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?

- Pass the Jenkins or GitHub Action

- Local manual test:add an unused import intentionally to trigger maven compilation error.

Closes #30784 from LuciferYang/SPARK-33560.

Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
2020-12-26 17:40:19 -06:00
kozakana 2553d53dc8 [SPARK-33897][SQL] Can't set option 'cross' in join method
### What changes were proposed in this pull request?

[The PySpark documentation](https://spark.apache.org/docs/3.0.1/api/python/pyspark.sql.html#pyspark.sql.DataFrame.join) says "Must be one of: inner, cross, outer, full, fullouter, full_outer, left, leftouter, left_outer, right, rightouter, right_outer, semi, leftsemi, left_semi, anti, leftanti and left_anti."
However, I get the following error when I set the cross option.

```
scala> val df1 = spark.createDataFrame(Seq((1,"a"),(2,"b")))
df1: org.apache.spark.sql.DataFrame = [_1: int, _2: string]

scala> val df2 = spark.createDataFrame(Seq((1,"A"),(2,"B"), (3, "C")))
df2: org.apache.spark.sql.DataFrame = [_1: int, _2: string]

scala> df1.join(right = df2, usingColumns = Seq("_1"), joinType = "cross").show()
java.lang.IllegalArgumentException: requirement failed: Unsupported using join type Cross
  at scala.Predef$.require(Predef.scala:281)
  at org.apache.spark.sql.catalyst.plans.UsingJoin.<init>(joinTypes.scala:106)
  at org.apache.spark.sql.Dataset.join(Dataset.scala:1025)
  ... 53 elided
```

### Why are the changes needed?

The documentation says cross option can be set, but when I try to set it, I get an java.lang.IllegalArgumentException.

### Does this PR introduce _any_ user-facing change?

Accepting this PR fix will behave the same as the documentation.

### How was this patch tested?

There is already a test for [JoinTypes](1b9fd67904/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/plans/JoinTypesTest.scala), but I can't find a test for the join option itself.

Closes #30803 from kozakana/allow_cross_option.

Authored-by: kozakana <goki727@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-12-26 16:30:50 +09:00
angerszhu 10b6466e91 [SPARK-33084][CORE][SQL] Add jar support ivy path
### What changes were proposed in this pull request?
Support add jar with ivy path

### Why are the changes needed?
Since submit app can support ivy, add jar we can also support ivy now.

### Does this PR introduce _any_ user-facing change?
User can add jar with sql like
```
add jar ivy:://group:artifict:version?exclude=xxx,xxx&transitive=true
add jar ivy:://group:artifict:version?exclude=xxx,xxx&transitive=false
```

core api
```
sparkContext.addJar("ivy:://group:artifict:version?exclude=xxx,xxx&transitive=true")
sparkContext.addJar("ivy:://group:artifict:version?exclude=xxx,xxx&transitive=false")
```

#### Doc Update snapshot
![image](https://user-images.githubusercontent.com/46485123/101227738-de451200-36d3-11eb-813d-78a8b879da4f.png)

### How was this patch tested?
Added UT

Closes #29966 from AngersZhuuuu/support-add-jar-ivy.

Lead-authored-by: angerszhu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Signed-off-by: Takeshi Yamamuro <yamamuro@apache.org>
2020-12-25 09:07:48 +09:00
Takeshi Yamamuro 65a9ac2ff4 [SPARK-30027][SQL] Support codegen for aggregate filters in HashAggregateExec
### What changes were proposed in this pull request?

This pr intends to support code generation for `HashAggregateExec` with filters.

Quick benchmark results:
```
$ ./bin/spark-shell --master=local[1] --conf spark.driver.memory=8g --conf spark.sql.shuffle.partitions=1 -v

scala> spark.range(100000000).selectExpr("id % 3 as k1", "id % 5 as k2", "rand() as v1", "rand() as v2").write.saveAsTable("t")
scala> sql("SELECT k1, k2, AVG(v1) FILTER (WHERE v2 > 0.5) FROM t GROUP BY k1, k2").write.format("noop").mode("overwrite").save()

>> Before this PR
Elapsed time: 16.170697619s

>> After this PR
Elapsed time: 6.7825313s
```

The query above is compiled into code below;

```
...
/* 285 */   private void agg_doAggregate_avg_0(boolean agg_exprIsNull_2_0, org.apache.spark.sql.catalyst.InternalRow agg_unsafeRowAggBuffer_0, double agg_expr_2_0) throws java.io.IOException {
/* 286 */     // evaluate aggregate function for avg
/* 287 */     boolean agg_isNull_10 = true;
/* 288 */     double agg_value_12 = -1.0;
/* 289 */     boolean agg_isNull_11 = agg_unsafeRowAggBuffer_0.isNullAt(0);
/* 290 */     double agg_value_13 = agg_isNull_11 ?
/* 291 */     -1.0 : (agg_unsafeRowAggBuffer_0.getDouble(0));
/* 292 */     if (!agg_isNull_11) {
/* 293 */       agg_agg_isNull_12_0 = true;
/* 294 */       double agg_value_14 = -1.0;
/* 295 */       do {
/* 296 */         if (!agg_exprIsNull_2_0) {
/* 297 */           agg_agg_isNull_12_0 = false;
/* 298 */           agg_value_14 = agg_expr_2_0;
/* 299 */           continue;
/* 300 */         }
/* 301 */
/* 302 */         if (!false) {
/* 303 */           agg_agg_isNull_12_0 = false;
/* 304 */           agg_value_14 = 0.0D;
/* 305 */           continue;
/* 306 */         }
/* 307 */
/* 308 */       } while (false);
/* 309 */
/* 310 */       agg_isNull_10 = false; // resultCode could change nullability.
/* 311 */
/* 312 */       agg_value_12 = agg_value_13 + agg_value_14;
/* 313 */
/* 314 */     }
/* 315 */     boolean agg_isNull_15 = false;
/* 316 */     long agg_value_17 = -1L;
/* 317 */     if (!false && agg_exprIsNull_2_0) {
/* 318 */       boolean agg_isNull_18 = agg_unsafeRowAggBuffer_0.isNullAt(1);
/* 319 */       long agg_value_20 = agg_isNull_18 ?
/* 320 */       -1L : (agg_unsafeRowAggBuffer_0.getLong(1));
/* 321 */       agg_isNull_15 = agg_isNull_18;
/* 322 */       agg_value_17 = agg_value_20;
/* 323 */     } else {
/* 324 */       boolean agg_isNull_19 = true;
/* 325 */       long agg_value_21 = -1L;
/* 326 */       boolean agg_isNull_20 = agg_unsafeRowAggBuffer_0.isNullAt(1);
/* 327 */       long agg_value_22 = agg_isNull_20 ?
/* 328 */       -1L : (agg_unsafeRowAggBuffer_0.getLong(1));
/* 329 */       if (!agg_isNull_20) {
/* 330 */         agg_isNull_19 = false; // resultCode could change nullability.
/* 331 */
/* 332 */         agg_value_21 = agg_value_22 + 1L;
/* 333 */
/* 334 */       }
/* 335 */       agg_isNull_15 = agg_isNull_19;
/* 336 */       agg_value_17 = agg_value_21;
/* 337 */     }
/* 338 */     // update unsafe row buffer
/* 339 */     if (!agg_isNull_10) {
/* 340 */       agg_unsafeRowAggBuffer_0.setDouble(0, agg_value_12);
/* 341 */     } else {
/* 342 */       agg_unsafeRowAggBuffer_0.setNullAt(0);
/* 343 */     }
/* 344 */
/* 345 */     if (!agg_isNull_15) {
/* 346 */       agg_unsafeRowAggBuffer_0.setLong(1, agg_value_17);
/* 347 */     } else {
/* 348 */       agg_unsafeRowAggBuffer_0.setNullAt(1);
/* 349 */     }
/* 350 */   }
...
```

### Why are the changes needed?

For high performance.

### Does this PR introduce any user-facing change?

No.

### How was this patch tested?

Existing tests.

Closes #27019 from maropu/AggregateFilterCodegen.

Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
2020-12-24 14:44:16 -08:00
Kent Yao 29cca68e9e [SPARK-33892][SQL] Display char/varchar in DESC and SHOW CREATE TABLE
### What changes were proposed in this pull request?

Display char/varchar in
  - DESC table
  - DESC column
  - SHOW CREATE TABLE

### Why are the changes needed?

show the correct definition for users

### Does this PR introduce _any_ user-facing change?

yes, char/varchar  column's will print char/varchar instead of string
### How was this patch tested?

new tests

Closes #30908 from yaooqinn/SPARK-33892.

Authored-by: Kent Yao <yaooqinn@hotmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-24 08:56:02 +00:00
Max Gekk 54a67842e6 [SPARK-33881][SQL][TESTS] Check null and empty string as partition values in DS v1 and v2 tests
### What changes were proposed in this pull request?
Add tests to check handling `null` and `''` (empty string) as partition values in commands `SHOW PARTITIONS`, `ALTER TABLE .. ADD PARTITION`, `ALTER TABLE .. DROP PARTITION`.

### Why are the changes needed?
To improve test coverage.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
By running the modified test suites:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.ShowPartitionsSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.AlterTableAddPartitionSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.AlterTableDropPartitionSuite"
```

Closes #30893 from MaxGekk/partition-value-empty-string.

Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-24 08:54:53 +00:00
gengjiaan 3e9821edfd [SPARK-33443][SQL] LEAD/LAG should support [ IGNORE NULLS | RESPECT NULLS ]
### What changes were proposed in this pull request?
The mainstream database support `[ IGNORE NULLS | RESPECT NULLS ]` for `LEAD`/`LAG`/`NTH_VALUE`/`FIRST_VALUE`/`LAST_VALUE`.
But the current implement of `LEAD`/`LAG` don't support this syntax.

**Oracle**
https://docs.oracle.com/en/database/oracle/oracle-database/19/sqlrf/LEAD.html#GUID-0A0481F1-E98F-4535-A739-FCCA8D1B5B77

**Presto**
https://prestodb.io/docs/current/functions/window.html

**Redshift**
https://docs.aws.amazon.com/redshift/latest/dg/r_WF_LEAD.html

**DB2**
https://www.ibm.com/support/knowledgecenter/SSGU8G_14.1.0/com.ibm.sqls.doc/ids_sqs_1513.htm

**Teradata**
https://docs.teradata.com/r/756LNiPSFdY~4JcCCcR5Cw/GjCT6l7trjkIEjt~7Dhx4w

**Snowflake**
https://docs.snowflake.com/en/sql-reference/functions/lead.html
https://docs.snowflake.com/en/sql-reference/functions/lag.html

### Why are the changes needed?
Support `[ IGNORE NULLS | RESPECT NULLS ]` for `LEAD`/`LAG` is very useful.

### Does this PR introduce _any_ user-facing change?
'Yes'.

### How was this patch tested?
Jenkins test.

Closes #30387 from beliefer/SPARK-33443.

Lead-authored-by: gengjiaan <gengjiaan@360.cn>
Co-authored-by: beliefer <beliefer@163.com>
Co-authored-by: Jiaan Geng <beliefer@163.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-24 08:13:48 +00:00
Yuming Wang 32d4a2b062 [SPARK-33861][SQL] Simplify conditional in predicate
### What changes were proposed in this pull request?

This pr simplify conditional in predicate, after this change we can push down the filter to datasource:

Expression | After simplify
-- | --
IF(cond, trueVal, false)                   | AND(cond, trueVal)
IF(cond, trueVal, true)                    | OR(NOT(cond), trueVal)
IF(cond, false, falseVal)                  | AND(NOT(cond), elseVal)
IF(cond, true, falseVal)                   | OR(cond, elseVal)
CASE WHEN cond THEN trueVal ELSE false END | AND(cond, trueVal)
CASE WHEN cond THEN trueVal END            | AND(cond, trueVal)
CASE WHEN cond THEN trueVal ELSE null END  | AND(cond, trueVal)
CASE WHEN cond THEN trueVal ELSE true END  | OR(NOT(cond), trueVal)
CASE WHEN cond THEN false ELSE elseVal END | AND(NOT(cond), elseVal)
CASE WHEN cond THEN false END              | false
CASE WHEN cond THEN true ELSE elseVal END  | OR(cond, elseVal)
CASE WHEN cond THEN true END               | cond

### Why are the changes needed?

Improve query performance.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Unit test.

Closes #30865 from wangyum/SPARK-33861.

Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2020-12-24 08:10:28 +00:00
Yuanjian Li 86c1cfc579 [SPARK-33659][SS] Document the current behavior for DataStreamWriter.toTable API
### What changes were proposed in this pull request?
Follow up work for #30521, document the following behaviors in the API doc:

- Figure out the effects when configurations are (provider/partitionBy) conflicting with the existing table.
- Document the lack of functionality on creating a v2 table, and guide that the users should ensure a table is created in prior to avoid the behavior unintended/insufficient table is being created.

### Why are the changes needed?
We didn't have full support for the V2 table created in the API now. (TODO SPARK-33638)

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
Document only.

Closes #30885 from xuanyuanking/SPARK-33659.

Authored-by: Yuanjian Li <yuanjian.li@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-12-24 12:44:37 +09:00