### What changes were proposed in this pull request?
This passes original SQL text to `CacheTableAsSelect` command in DSv1 and v2 so that it will be stored instead of the analyzed logical plan, similar to `CREATE VIEW` command.
In addition, this changes the behavior of dropping temporary view to also invalidate dependent caches in a cascade, when the config `SQLConf.STORE_ANALYZED_PLAN_FOR_VIEW` is false (which is the default value).
### Why are the changes needed?
Currently, after creating a temporary view with `CACHE TABLE ... AS SELECT` command, the view can still be queried even after the source table is dropped or replaced (in v2). This can cause correctness issue.
For instance, in the following:
```sql
> CREATE TABLE t ...;
> CACHE TABLE v AS SELECT * FROM t;
> DROP TABLE t;
> SELECT * FROM v;
```
The last select query still returns the old (and stale) result instead of fail. Note that the cache is already invalidated as part of dropping table `t`, but the temporary view `v` still exist.
On the other hand, the following:
```sql
> CREATE TABLE t ...;
> CREATE TEMPORARY VIEW v AS SELECT * FROM t;
> CACHE TABLE v;
> DROP TABLE t;
> SELECT * FROM v;
```
will throw "Table or view not found" error in the last select query.
This is related to #30567 which aligns the behavior of temporary view and global view by storing the original SQL text for temporary view, as opposed to the analyzed logical plan. However, the PR only handles `CreateView` case but not the `CacheTableAsSelect` case.
This also changes uncache logic and use cascade invalidation for temporary views created above. This is to align its behavior to how a permanent view is handled as of today, and also to avoid potential issues where a dependent view becomes invalid while its data is still kept in cache.
### Does this PR introduce _any_ user-facing change?
Yes, now when `SQLConf.STORE_ANALYZED_PLAN_FOR_VIEW` is set to false (the default value), whenever a table/permanent view/temp view that a cached view depends on is dropped, the cached view itself will become invalid during analysis, i.e., user will get "Table or view not found" error. In addition, when the dependent is a temp view in the previous case, the cache itself will also be invalidated.
### How was this patch tested?
Modified/Enhanced some existing tests.
Closes#31107 from sunchao/SPARK-34052.
Lead-authored-by: Chao Sun <sunchao@apple.com>
Co-authored-by: Chao Sun <sunchao@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
1. Port DS V2 tests from `AlterTablePartitionV2SQLSuite ` to the test suite `v2.AlterTableRecoverPartitionsSuite`.
2. Port DS v1 tests from `DDLSuite` to `v1.AlterTableRecoverPartitionsSuiteBase`.
### 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 *AlterTableRecoverPartitionsParserSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableRecoverPartitionsSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *CatalogedDDLSuite"
```
Closes#31105 from MaxGekk/unify-recover-partitions-tests.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This pr add row count to `Intersect` operator when CBO enabled.
### 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?
Added
Closes#31240 from AngersZhuuuu/SPARK-34121.
Authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Check SPARK_TESTING as lazy val to avoid slow down when there are many environment variables
### Why are the changes needed?
If there are many environment variables, sys.env slows is very slow. As Utils.isTesting is called very often during Dataframe-Optimization, this can slow down evaluation very much.
An example for triggering the problem can be found in the bug ticket https://issues.apache.org/jira/browse/SPARK-34115
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
With the example provided in the ticket.
Closes#31244 from nob13/bug/34115.
Lead-authored-by: Norbert Schultz <norbert.schultz@reactivecore.de>
Co-authored-by: Norbert Schultz <noschultz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Increase the timeout for StreamingLinearRegressionSuite to 60s to deflake the test.
### Why are the changes needed?
Reduce merge conflict.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Closes#31248 from liangz1/increase-timeout.
Authored-by: Liang Zhang <liang.zhang@databricks.com>
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
### What changes were proposed in this pull request?
Clear table cache after adding partitions to v2 table in `AlterTableAddPartitionExec`.
### Why are the changes needed?
This PR fixes correctness issue. Without the fix, queries on cached tables modified via `ALTER TABLE .. ADD PARTITION` return incorrect results.
### Does this PR introduce _any_ user-facing change?
Yes.
### How was this patch tested?
Added new UT to `org.apache.spark.sql.execution.command.v2.AlterTableAddPartitionSuite`:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.AlterTableAddPartitionSuite"
```
Closes#31229 from MaxGekk/v2-add-partition-recache.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Change `Column.named` code to let expression check if exists `UnresolvedExtractValue` and use `UnresolvedAlias` to assign name.
### Why are the changes needed?
It's more reasonable to treat user specify expression as unresolved expression then we should assign name after analyze.
Let's say we have this code
```
spark.range(1).selectExpr("id as id1", "id as id2")
.selectExpr("cast(struct(id1, id2).id1 as int)")
```
before this PR, the field name is `CAST(struct(id1, id2)[id1] AS INT)`.
After, the field name is `CAST(struct(id1, id2).id1 AS INT)`.
### Does this PR introduce _any_ user-facing change?
Yes, the default field name may be changed.
### How was this patch tested?
Add test.
Closes#30974 from ulysses-you/SPARK-33939-0.
Authored-by: ulysses-you <ulyssesyou18@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This could reduce the `generate.java` size to prevent codegen fallback which causes performance regression.
here is a case from tpcds that could be fixed by this improvement
https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/133964/testReport/org.apache.spark.sql.execution/LogicalPlanTagInSparkPlanSuite/q41/
The original case generate 20K bytes, we are trying to reduce it to less than 8k
### Why are the changes needed?
performance improvement as in the PR benchmark test, the performance w/ codegen is 2~3x better than w/o codegen.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
yes, it's a code reflect so the existing ut should be enough
cross-check with https://github.com/apache/spark/pull/31012 where the tpcds shall all pass
benchmark compared with master
```logtalk
================================================================================================
Char Varchar Read Side Perf
================================================================================================
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Read with length 20, hasSpaces: false: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
read string with length 20 1571 1667 83 63.6 15.7 1.0X
read char with length 20 1710 1764 58 58.5 17.1 0.9X
read varchar with length 20 1774 1792 16 56.4 17.7 0.9X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Read with length 40, hasSpaces: false: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
read string with length 40 1824 1927 91 54.8 18.2 1.0X
read char with length 40 1788 1928 137 55.9 17.9 1.0X
read varchar with length 40 1676 1700 40 59.7 16.8 1.1X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Read with length 60, hasSpaces: false: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
read string with length 60 1727 1762 30 57.9 17.3 1.0X
read char with length 60 1628 1674 43 61.4 16.3 1.1X
read varchar with length 60 1651 1665 13 60.6 16.5 1.0X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Read with length 80, hasSpaces: true: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
read string with length 80 1748 1778 28 57.2 17.5 1.0X
read char with length 80 1673 1678 9 59.8 16.7 1.0X
read varchar with length 80 1667 1684 27 60.0 16.7 1.0X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Read with length 100, hasSpaces: true: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
read string with length 100 1709 1743 48 58.5 17.1 1.0X
read char with length 100 1610 1664 67 62.1 16.1 1.1X
read varchar with length 100 1614 1673 53 61.9 16.1 1.1X
================================================================================================
Char Varchar Write Side Perf
================================================================================================
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Write with length 20, hasSpaces: false: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
write string with length 20 2277 2327 67 4.4 227.7 1.0X
write char with length 20 2421 2443 19 4.1 242.1 0.9X
write varchar with length 20 2393 2419 27 4.2 239.3 1.0X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Write with length 40, hasSpaces: false: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
write string with length 40 2249 2290 38 4.4 224.9 1.0X
write char with length 40 2386 2444 57 4.2 238.6 0.9X
write varchar with length 40 2397 2405 12 4.2 239.7 0.9X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Write with length 60, hasSpaces: false: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
write string with length 60 2326 2367 41 4.3 232.6 1.0X
write char with length 60 2478 2501 37 4.0 247.8 0.9X
write varchar with length 60 2475 2503 24 4.0 247.5 0.9X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Write with length 80, hasSpaces: true: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
write string with length 80 9367 9773 354 1.1 936.7 1.0X
write char with length 80 10454 10621 238 1.0 1045.4 0.9X
write varchar with length 80 18943 19503 571 0.5 1894.3 0.5X
Java HotSpot(TM) 64-Bit Server VM 1.8.0_251-b08 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU 2.40GHz
Write with length 100, hasSpaces: true: Best Time(ms) Avg Time(ms) Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
write string with length 100 11055 11104 59 0.9 1105.5 1.0X
write char with length 100 12204 12275 63 0.8 1220.4 0.9X
write varchar with length 100 21737 22275 574 0.5 2173.7 0.5X
```
Closes#31199 from yaooqinn/SPARK-34130.
Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR proposes to consider the case when [`inspect.currentframe()`](https://docs.python.org/3/library/inspect.html#inspect.currentframe) returns `None` because the underlyining Python implementation does not support frame.
### Why are the changes needed?
To be safer and potentially for the official support of other Python implementations in the future.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manually tested via:
When frame is available:
```
vi tmp.py
```
```python
from inspect import *
lineno = getframeinfo(currentframe()).lineno + 1 if currentframe() is not None else 0
print(warnings.formatwarning(
"Failed to set memory limit: {0}".format(Exception("argh!")),
ResourceWarning,
__file__,
lineno),
file=sys.stderr)
```
```
python tmp.py
```
```
/.../tmp.py:3: ResourceWarning: Failed to set memory limit: argh!
print(warnings.formatwarning(
```
When frame is not available:
```
vi tmp.py
```
```python
from inspect import *
lineno = getframeinfo(currentframe()).lineno + 1 if None is not None else 0
print(warnings.formatwarning(
"Failed to set memory limit: {0}".format(Exception("argh!")),
ResourceWarning,
__file__,
lineno),
file=sys.stderr)
```
```
python tmp.py
```
```
/.../tmp.py:0: ResourceWarning: Failed to set memory limit: argh!
```
Closes#31239 from HyukjinKwon/SPARK-33730-followup.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This pr keep necessary stats after partition pruning.
### Why are the changes needed?
Improve query performance. It will push down aggregate since SPARK-34081 because it can be planed as BroadcastHashJoin. But it lacks column statistics after [`PruneFileSourcePartitions`](d0c83f372b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PruneFileSourcePartitions.scala (L102-L103)). Therefore, it will eventually be planned as SortMergeJoin.
Please see the log:
```
join.right.stats: org.apache.spark.sql.catalyst.optimizer.PushDownPredicates: Statistics(sizeInBytes=348.8 KiB, rowCount=1.79E+4)
join.right.stats: org.apache.spark.sql.execution.datasources.PruneFileSourcePartitions: Statistics(sizeInBytes=1414.2 EiB)
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit test and benchmark test
SQL | Before this PR(Seconds) | After this PR(Seconds)
-- | -- | --
q14a | 594 | 384
q14b | 600 | 402
This change will not affect the results of `PlanStabilitySuite`, because it does not have partition column.
Closes#31205 from wangyum/SPARK-34119.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
While adding new partition to v2 `InMemoryAtomicPartitionTable`/`InMemoryPartitionTable`, add single row to the table content when the table is fully partitioned.
### Why are the changes needed?
The `ALTER TABLE .. ADD PARTITION` command does not change content of fully partitioned v2 table. For instance, `INSERT INTO` changes table content:
```scala
sql(s"CREATE TABLE t (p0 INT, p1 STRING) USING _ PARTITIONED BY (p0, p1)")
sql(s"INSERT INTO t SELECT 1, 'def'")
sql(s"SELECT * FROM t").show(false)
+---+---+
|p0 |p1 |
+---+---+
|1 |def|
+---+---+
```
but `ALTER TABLE .. ADD PARTITION` doesn't change v2 table content:
```scala
sql(s"ALTER TABLE t ADD PARTITION (p0 = 0, p1 = 'abc')")
sql(s"SELECT * FROM t").show(false)
+---+---+
|p0 |p1 |
+---+---+
+---+---+
```
### Does this PR introduce _any_ user-facing change?
No, the changes impact only on tests but for the example above in tests:
```scala
sql(s"ALTER TABLE t ADD PARTITION (p0 = 0, p1 = 'abc')")
sql(s"SELECT * FROM t").show(false)
+---+---+
|p0 |p1 |
+---+---+
|0 |abc|
+---+---+
```
### How was this patch tested?
By running the unified tests for `ALTER TABLE .. ADD PARTITION`.
Closes#31216 from MaxGekk/add-partition-by-all-columns.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Change null Literal to PrettyAttribute during ResolveAlias.
### Why are the changes needed?
We will convert `Literal(null)` to target data type during analysis. Then the generated alias name will include something like `CAST(NULL AS String)` instead of `NULL`.
```
spark.sql("SELECT RAND(null)").columns
-- before
rand(CAST(NULL AS INT))
-- after
rand(NULL)
```
### Does this PR introduce _any_ user-facing change?
Yes, the default column name maybe changed.
### How was this patch tested?
Add test and pass exists test.
Closes#31233 from ulysses-you/SPARK-34150.
Authored-by: ulysses-you <ulyssesyou18@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Remove unused call of `getRawTable()` from `HiveExternalCatalog.alterPartitions()`.
### Why are the changes needed?
It reduces the number of calls to Hive External catalog.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the modified test suite:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableRenamePartitionSuite"
```
Closes#31234 from MaxGekk/remove-getRawTable-from-alterPartitions.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Fix table size parsing from the `Statistics` field which is formed at: c3d81fbe79/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/interface.scala (L573) . Before the fix, `getTableSize()` returns only the last digit. This works for Hive table in the tests because its size < 10 bytes, and accidentally works for V1 In-Memory catalog table in the tests.
### Why are the changes needed?
This makes tests more reliable. For example, the parsing can not work in `AlterTableDropPartitionSuite` when table size before partition dropping:
```
+---------+
|data_type|
+---------+
|878 bytes|
+---------+
```
After:
```
+---------+
|data_type|
+---------+
|439 bytes|
+---------+
```
at:
```scala
val onePartSize = getTableSize(t)
assert(0 < onePartSize && onePartSize < twoPartSize)
```
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By existing test suites:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.AlterTableAddPartitionSuite"
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *.AlterTableDropPartitionSuite"
```
Closes#31237 from MaxGekk/optimize-updateTableStats-followup.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR is the 3rd try to upgrade Scala 2.12.x in order to see the feasibility.
- https://github.com/apache/spark/pull/27929 (Upgrade Scala to 2.12.11, wangyum )
- https://github.com/apache/spark/pull/30940 (Upgrade Scala to 2.12.12, viirya )
`silencer` library is updated accordingly. And, Kafka version upgrade is required because it fails like the following.
```
[info] KafkaDataConsumerSuite:
[info] org.apache.spark.streaming.kafka010.KafkaDataConsumerSuite *** ABORTED *** (1 second, 580 milliseconds)
[info] java.lang.NoClassDefFoundError: scala/math/Ordering$$anon$7
[info] at kafka.api.ApiVersion$.orderingByVersion(ApiVersion.scala:45)
```
### Why are the changes needed?
Apache Spark was stuck to 2.12.10 due to the regression in Scala 2.12.11 and 2.12.12. This will bring all the bug fixes.
- https://github.com/scala/scala/releases/tag/v2.12.13
- https://github.com/scala/scala/releases/tag/v2.12.12
- https://github.com/scala/scala/releases/tag/v2.12.11
### Does this PR introduce _any_ user-facing change?
Yes, but this is a bug-fixed version.
### How was this patch tested?
Pass the CIs.
Closes#31223 from dongjoon-hyun/SPARK-31168.
Authored-by: Dongjoon Hyun <dhyun@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This patch moves move general StateStore-related tests into `StateStoreSuiteBase`.
### Why are the changes needed?
There are some general StateStore tests in `StateStoreSuite` which is `HDFSBackedStateStoreProvider`-specific test suite. We should move general tests into `StateStoreSuiteBase`, so it is easier to incorporate other StateStores.
### Does this PR introduce _any_ user-facing change?
No, dev only.
### How was this patch tested?
Unit test.
Closes#31219 from viirya/SPARK-34148.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
update the ParamValidators of `maxDepth`
### Why are the changes needed?
current impl of tree models only support maxDepth<=30
### Does this PR introduce _any_ user-facing change?
If `maxDepth`>30, fail quickly
### How was this patch tested?
existing testsuites
Closes#31163 from zhengruifeng/param_maxDepth_upbound.
Authored-by: Ruifeng Zheng <ruifengz@foxmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Invoke `refreshTable()` from `CatalogImpl` which refreshes the cache in v1 `ALTER TABLE .. RECOVER PARTITIONS`.
### Why are the changes needed?
This fixes the issues portrayed by the example:
```sql
spark-sql> create table tbl (col int, part int) using parquet partitioned by (part);
spark-sql> insert into tbl partition (part=0) select 0;
spark-sql> cache table tbl;
spark-sql> select * from tbl;
0 0
spark-sql> show table extended like 'tbl' partition(part=0);
default tbl false Partition Values: [part=0]
Location: file:/Users/maximgekk/proj/recover-partitions-refresh-cache/spark-warehouse/tbl/part=0
...
```
Create new partition by copying the existing one:
```
$ cp -r /Users/maximgekk/proj/recover-partitions-refresh-cache/spark-warehouse/tbl/part=0 /Users/maximgekk/proj/recover-partitions-refresh-cache/spark-warehouse/tbl/part=1
```
```sql
spark-sql> alter table tbl recover partitions;
spark-sql> select * from tbl;
0 0
```
The last query must return `0 1` since it has been recovered by `ALTER TABLE .. RECOVER PARTITIONS`.
### Does this PR introduce _any_ user-facing change?
Yes. After the changes for the example above:
```sql
...
spark-sql> alter table tbl recover partitions;
spark-sql> select * from tbl;
0 0
0 1
```
### How was this patch tested?
By running the affected test suite:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *CachedTableSuite"
```
Closes#31066 from MaxGekk/recover-partitions-refresh-cache.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
`java.io.FIle.toURL` method does not automatically escape characters that are illegal in URLs.
Java doc recommended that new code convert an abstract pathname into a URL by first converting it into a URI, via the `toURI` method, and then converting the URI into a URL via the `URI.toURL` method.
So this pr cleaned up the relevant cases in Spark code.
### Why are the changes needed?
Cleaning up `Deprecated` Java API usage.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#31230 from LuciferYang/SPARK-34151.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Currently, there are many DDL commands where the position of the unresolved identifiers are incorrect:
```
scala> sql("CACHE TABLE unknown")
org.apache.spark.sql.AnalysisException: Table or view not found: unknown; line 1 pos 0;
```
, whereas the `pos` should be `12`.
This PR proposes to fix this issue for commands using `UnresolvedRelation`:
```
CACHE TABLE unknown
UNCACHE TABLE unknown
DELETE FROM unknown
UPDATE unknown SET name='abc'
MERGE INTO unknown1 AS target USING unknown2 AS source ON target.col = source.col WHEN MATCHED THEN DELETE
INSERT INTO TABLE unknown SELECT 1
INSERT OVERWRITE TABLE unknown VALUES (1, 'a')
```
### Why are the changes needed?
To fix a bug.
### Does this PR introduce _any_ user-facing change?
Yes, now the above example will print the following:
```
org.apache.spark.sql.AnalysisException: Table or view not found: unknown; line 1 pos 12;
```
### How was this patch tested?
Add a new test.
Closes#31209 from imback82/unresolved_relation_message.
Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
Hive 2.3.8 changes:
HIVE-19662: Upgrade Avro to 1.8.2
HIVE-24324: Remove deprecated API usage from Avro
HIVE-23980: Shade Guava from hive-exec in Hive 2.3
HIVE-24436: Fix Avro NULL_DEFAULT_VALUE compatibility issue
HIVE-24512: Exclude calcite in packaging.
HIVE-22708: Fix for HttpTransport to replace String.equals
HIVE-24551: Hive should include transitive dependencies from calcite after shading it
HIVE-24553: Exclude calcite from test-jar dependency of hive-exec
### Why are the changes needed?
Upgrade Avro and Parquet to latest version.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Existing test add test try to upgrade Parquet to 1.11.1 and Avro to 1.10.1: https://github.com/apache/spark/pull/30517Closes#30657 from wangyum/SPARK-33696.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR is a followup of #27433. It fixes the naming to match with Scala side, and this is similar with https://github.com/apache/spark/pull/31062.
Note that:
- there are a bit of inconsistency already e.g.) `x`, `y` in SparkR and they are documented together for doc deduplication. This part I did not change but the name `zero` vs `initialValue` looks unnecessary.
- such naming matching seems already pretty common in SparkR.
### Why are the changes needed?
To make the usage similar with Scala side, and for consistency.
### Does this PR introduce _any_ user-facing change?
No, this is not released yet.
### How was this patch tested?
GitHub Actions and Jenkins build will test it out.
Also, I manually tested:
```r
> df <- select(createDataFrame(data.frame(id = 1)),expr("CAST(array(1.0, 2.0, -3.0, -4.0) AS array<double>) xs"))
> collect(select(df, array_aggregate("xs", initialValue = lit(0.0), merge = function(x, y) otherwise(when(x > y, x), y))))
aggregate(xs, 0.0, lambdafunction(CASE WHEN (x > y) THEN x ELSE y END, x, y), lambdafunction(id, id))
1 2
```
Closes#31226 from HyukjinKwon/SPARK-30682.
Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
1, make `getTopIndices`/`selectIndicesFromPValues` private;
2, avoid setting `selectionThreshold` in `fit`
3, move param checking to `transformSchema`
### Why are the changes needed?
`getTopIndices`/`selectIndicesFromPValues` should not be exposed to end users;
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
existing testsuites
Closes#31222 from zhengruifeng/selector_clean_up.
Authored-by: Ruifeng Zheng <ruifengz@foxmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR aims to support fallback storage clean-up during stopping `SparkContext`.
### Why are the changes needed?
SPARK-33545 added `Support Fallback Storage during worker decommission` for the managed cloud-storages with TTL support. Usually, it's one day. This PR will add an additional clean-up feature during stopping `SparkContext` in order to save some money before TTL or the other HDFS-compatible storage which doesn't have TTL support.
### Does this PR introduce _any_ user-facing change?
Yes, but this is a new feature.
### How was this patch tested?
Pass the newly added UT.
Closes#31215 from dongjoon-hyun/SPARK-34142.
Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR:
- Adds as small hierarchy of warnings to be used in PySpark applications. These extend built-in classes and top level `PySparkWarning`.
- Replaces `DeprecationWarnings` (intended for developers) with PySpark specific subclasses of `FutureWarning` (intended for end users).
### Why are the changes needed?
- To be more precise and add users additional control (in addition to standard module level filters) over PySpark warnings handling.
- Correct semantics (at the moment we use `DeprecationWarning` in user-facing API, but it is intended "for warnings about deprecated features when those warnings are intended for other Python developers").
### Does this PR introduce _any_ user-facing change?
Yes. Code can raise different type of warning than before.
### How was this patch tested?
Existing tests.
Closes#30985 from zero323/SPARK-33730.
Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
Display history server entries using datatables instead of Mustache + Datatables which proved to be faster and non-blocking for the webpage while searching (using search bar in the page)
### Why are the changes needed?
Small changes in the attempts (entries) and removed part of HTML (Mustache template).
### Does this PR introduce _any_ user-facing change?
Not very sure, but it's not supposed to change the way the page looks rather it changes how entries are displayed.
### How was this patch tested?
Running test, since it's not adding new functionality.
Closes#31191 from mohan3d/feat/history-server-ui-optimization.
Lead-authored-by: mohan3d <mohan3d94@gmail.com>
Co-authored-by: Author: mohan3d <mohan3d94@gmail.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
This PR aims to update a broken link in asf.yml to the correct one.
### Why are the changes needed?
The previous link shows a page not found error.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
N/A
Closes#31210 from williamhyun/minorasf.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
`QueryCompilationErrors.scala` and `QueryExecutionErrors.scala` use the `org.apache.spark.sql.errors` package, but these files are reside in `org/apache/spark/sql` directory. This PR proposes to move these files to `org/apache/spark/sql/errors`.
### Why are the changes needed?
To match the package name with the directory structure.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Existing tests
Closes#31211 from imback82/error_package.
Authored-by: Terry Kim <yuminkim@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to update the Parquet website link from http://parquet.io to https://parquet.apache.orc
### Why are the changes needed?
The old website goes to the incubator site.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
N/A
Closes#31208 from williamhyun/minor-parquet.
Authored-by: William Hyun <williamhyun3@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR upgrade Zookeeper to 3.6.2.
### Why are the changes needed?
To make Spark running on jdk 14, otherwise:
```
21/01/13 20:25:32,533 WARN [Driver-SendThread(apache-spark-zk-3.vip.hadoop.com:2181)] zookeeper.ClientCnxn:1164 : Session 0x0 for server apache-spark-zk-3.vip.hadoop.com/<unresolved>:2181, unexpected error, closing socket connection and attempting reconnect
java.lang.IllegalArgumentException: Unable to canonicalize address apache-spark-zk-3.vip.hadoop.com/<unresolved>:2181 because it's not resolvable
at org.apache.zookeeper.SaslServerPrincipal.getServerPrincipal(SaslServerPrincipal.java:65)
at org.apache.zookeeper.SaslServerPrincipal.getServerPrincipal(SaslServerPrincipal.java:41)
at org.apache.zookeeper.ClientCnxn$SendThread.startConnect(ClientCnxn.java:1001)
at org.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1060)
```
Please see [ZOOKEEPER-3779](https://issues.apache.org/jira/browse/ZOOKEEPER-3779) for more details.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Manual test:
1. Replace zookeeper-3.4.14.jar with zookeeper-3.6.2.jar and zookeeper-jute-3.6.2.jar
2. Run Spark on jdk 14. Hadoop 2.7 with HADOOP-12760, Hive 1.2.1 and Zookeeper server version is 3.4.6.
Some key configurations:
```
# spark-defaults.conf
spark.yarn.appMasterEnv.JAVA_HOME /apache/releases/jdk-14.0.2
spark.executorEnv.JAVA_HOME /apache/releases/jdk-14.0.2
# spark-env.sh
export JAVA_HOME=/apache/releases/jdk-14.0.2
```
Jenkins Tests
- Hadoop 3.2: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/134048/testReport
- Hadoop 2.7: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/134063/testReportCloses#31177 from wangyum/SPARK-34110.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
Add UnivariateFeatureSelector
### Why are the changes needed?
Have one UnivariateFeatureSelector, so we don't need to have three Feature Selectors.
### Does this PR introduce _any_ user-facing change?
Yes
```
selector = UnivariateFeatureSelector(featureCols=["x", "y", "z"], labelCol=["target"], featureType="categorical", labelType="continuous", selectorType="numTopFeatures", numTopFeatures=100)
```
Or
numTopFeatures
```
selector = UnivariateFeatureSelector(featureCols=["x", "y", "z"], labelCol=["target"], scoreFunction="f_classif", selectorType="numTopFeatures", numTopFeatures=100)
```
### How was this patch tested?
Add Unit test
Closes#31160 from huaxingao/UnivariateSelector.
Authored-by: Huaxin Gao <huaxing@us.ibm.com>
Signed-off-by: Weichen Xu <weichen.xu@databricks.com>
### What changes were proposed in this pull request?
Replace `toMap` by `map(identity).toMap` while getting canonicalized representation of `CatalogTable`. `CatalogTable` became not serializable after https://github.com/apache/spark/pull/31112 due to usage of `filterKeys`. The workaround was taken from https://github.com/scala/bug/issues/7005.
### Why are the changes needed?
This prevents the errors like:
```
[info] org.apache.spark.SparkException: Job aborted due to stage failure: Task not serializable: java.io.NotSerializableException: scala.collection.immutable.MapLike$$anon$1
[info] Cause: java.io.NotSerializableException: scala.collection.immutable.MapLike$$anon$1
```
### Does this PR introduce _any_ user-facing change?
Should not.
### How was this patch tested?
By running the test suite affected by https://github.com/apache/spark/pull/31112:
```
$ build/sbt -Phive-2.3 -Phive-thriftserver "test:testOnly *AlterTableDropPartitionSuite"
```
Closes#31197 from MaxGekk/fix-caching-hive-table-2-followup.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This:
1. switches Spark to use shaded Hadoop clients, namely hadoop-client-api and hadoop-client-runtime, for Hadoop 3.x.
2. upgrade built-in version for Hadoop 3.x to Hadoop 3.2.2
Note that for Hadoop 2.7, we'll still use the same modules such as hadoop-client.
In order to still keep default Hadoop profile to be hadoop-3.2, this defines the following Maven properties:
```
hadoop-client-api.artifact
hadoop-client-runtime.artifact
hadoop-client-minicluster.artifact
```
which default to:
```
hadoop-client-api
hadoop-client-runtime
hadoop-client-minicluster
```
but all switch to `hadoop-client` when the Hadoop profile is hadoop-2.7. A side affect from this is we'll import the same dependency multiple times. For this I have to disable Maven enforcer `banDuplicatePomDependencyVersions`.
Besides above, there are the following changes:
- explicitly add a few dependencies which are imported via transitive dependencies from Hadoop jars, but are removed from the shaded client jars.
- removed the use of `ProxyUriUtils.getPath` from `ApplicationMaster` which is a server-side/private API.
- modified `IsolatedClientLoader` to exclude `hadoop-auth` jars when Hadoop version is 3.x. This change should only matter when we're not sharing Hadoop classes with Spark (which is _mostly_ used in tests).
### Why are the changes needed?
Hadoop 3.2.2 is released with new features and bug fixes, so it's good for the Spark community to adopt it. However, latest Hadoop versions starting from Hadoop 3.2.1 have upgraded to use Guava 27+. In order to resolve Guava conflicts, this takes the approach by switching to shaded client jars provided by Hadoop. This also has the benefits of avoid pulling other 3rd party dependencies from Hadoop side so as to avoid more potential future conflicts.
### Does this PR introduce _any_ user-facing change?
When people use Spark with `hadoop-provided` option, they should make sure class path contains `hadoop-client-api` and `hadoop-client-runtime` jars. In addition, they may need to make sure these jars appear before other Hadoop jars in the order. Otherwise, classes may be loaded from the other non-shaded Hadoop jars and cause potential conflicts.
### How was this patch tested?
Relying on existing tests.
Closes#30701 from sunchao/test-hadoop-3.2.2.
Authored-by: Chao Sun <sunchao@apple.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
The type-coercion for numeric types of average and sum is not necessary at all, as the resultType and sumType can prevent the overflow.
### Why are the changes needed?
rm unnecessary logic which may cause potential performance regressions
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
tpcds tests for plan
Closes#31079 from yaooqinn/SPARK-34037.
Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>
### What changes were proposed in this pull request?
Some local variables are declared as `var`, but they are never reassigned and should be declared as `val`, so this pr turn these from `var` to `val` except for `mockito` related cases.
### Why are the changes needed?
Use `val` instead of `var` when possible.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#31142 from LuciferYang/SPARK-33346.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: Sean Owen <srowen@gmail.com>
### What changes were proposed in this pull request?
Add support for `orc.force.positional.evolution` config that forces ORC top level column matching by position rather than by name.
This does work in Hive:
```
> set orc.force.positional.evolution;
+--------------------------------------+
| set |
+--------------------------------------+
| orc.force.positional.evolution=true |
+--------------------------------------+
> create table t (c1 string, c2 string) stored as orc;
> insert into t values ('foo', 'bar');
> alter table t change c1 c3 string;
```
The orc file in this case contains the original `c1` and `c2` columns that doesn't match the metadata in HMS. But due to the positional evolution setting, Hive is capable to return all the data:
```
> select * from t;
+--------+--------+
| t.c3 | t.c2 |
+--------+--------+
| foo | bar |
+--------+--------+
```
Without this PR Spark returns `null`s for the renamed `c3` column.
After this PR Spark returns the data in `c3` column.
### Why are the changes needed?
Hive/ORC does support it.
### Does this PR introduce _any_ user-facing change?
Yes, we will support `orc.force.positional.evolution`.
### How was this patch tested?
New UT.
Closes#29737 from peter-toth/SPARK-32864-support-orc-forced-positional-evolution.
Lead-authored-by: Peter Toth <peter.toth@gmail.com>
Co-authored-by: Peter Toth <ptoth@cloudera.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
On the read-side, we should respect the original data instead of trimming it first.
It brings extra overhead on the code-gen code side, trimming and padding for the same field, and it's also unnecessary and a bug
### Why are the changes needed?
bugfix and perf regression
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
new tests
Closes#31181 from yaooqinn/SPARK-34114.
Authored-by: Kent Yao <yao@apache.org>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This PR introduces a new property `spark.sql.cli.print.header` to let users change the behavior of printing header for spark-sql CLI by SET command.
### Why are the changes needed?
Like Hive CLI, spark-sql CLI accepts `hive.cli.print.header` property and we can change the behavior of printing header.
But spark-sql CLI doesn't allow users to change Hive specific configurations dynamically by SET command.
So, it's better to support the way to change the behavior by SET command.
### Does this PR introduce _any_ user-facing change?
Yes. Users can dynamically change the behavior by SET command.
### How was this patch tested?
I confirmed with the following commands/queries.
```
spark-sql> select (1) as a, (2) as b, (3) as c, (4) as d;
1 2 3 4
Time taken: 3.218 seconds, Fetched 1 row(s)
spark-sql> set spark.sql.cli.print.header=true;
key value
spark.sql.cli.print.header true
Time taken: 1.506 seconds, Fetched 1 row(s)
spark-sql> select (1) as a, (2) as b, (3) as c, (4) as d;
a b c d
1 2 3 4
Time taken: 0.79 seconds, Fetched 1 row(s)
```
Closes#31173 from sarutak/spark-sql-print-header.
Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This PR changes cache refreshing of v2 tables in v2 commands. In particular, v2 table dependents are not removed from the cache after this PR. Comparing to current implementation, we just clear cached data of all dependents and keep them in the cache. So, the next actions will fill in the cached data of the original v2 table and its dependents. In more details:
1. Add new method `recacheTable()` to `DataSourceV2Strategy` and pass it the exec node where need to recache table. New method uses `recacheByPlan` to refresh data cache of v2 tables, and keeps table dependents still cached **while clearing their caches**.
2. Simplify `invalidateCache` (and rename it `invalidateTableCache`) by retargeting it for only table cache invalidation.
3. Modify a test for `REFRESH TABLE` and check that v2 table dependent is still cached after refreshing the base table.
### Why are the changes needed?
1. This should improve user experience with table/view caching. For example, let's imagine that an user has cached v2 table and cached view based on the table. And the user passed the table to external library which drops/renames/adds partitions in the v2 table. Unfortunately, the user gets the view uncached after that even he/she hasn't uncached the view explicitly.
2. Improve code maintenance.
3. Reduce the number of calls to the Cache Manager when need to recache a table. Before the changes, `invalidateCache()` invokes the Cache Manager 3 times: `lookupCachedData()`, `uncacheQuery()` and `cacheQuery()`.
4. Also this should speed up table recaching.
### Does this PR introduce _any_ user-facing change?
From the view of the correctness of query results, there are no behavior changes but the changes might influence on consuming memory and query execution time.
### How was this patch tested?
By running the existing test suites for v2 the add/drop/rename partition commands.
Closes#31172 from MaxGekk/dsv2-recache-table.
Authored-by: Max Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
This pr use `exists` or `forall` to simplify `filter + emptiness check`, it's semantically consistent, but looks simpler. The rule as follow:
- `seq.filter(p).size == 0)` -> `!seq.exists(p)`
- `seq.filter(p).length > 0` -> `seq.exists(p)`
- `seq.filterNot(p).isEmpty` -> `seq.forall(p)`
- `seq.filterNot(p).nonEmpty` -> `!seq.forall(p)`
### Why are the changes needed?
Code Simpilefications.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass the Jenkins or GitHub Action
Closes#31184 from LuciferYang/SPARK-34118.
Authored-by: yangjie01 <yangjie01@baidu.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
### What changes were proposed in this pull request?
This patch proposes to pull the test of `numKeys` metric into a separate test in `StateStoreSuite`.
### Why are the changes needed?
Right now in `StateStoreSuite`, the tests of get/put/remove/commit are mixed with `numKeys` metric test. I found it is flaky when I was testing with other `StateStore` implementation.
Current test logic is tightly bound to the in-memory map behavior of `HDFSBackedStateStore`. For example, put can immediately show up in the `numKeys` metric.
But for a `StateStore` implementation relying on external storage, e.g. RocksDB, the metric might be updated once the data is actually committed. And `StateStoreSuite` should be a common test suite for all kinds of StateStore implementations.
Specifically, we also are able to check these metrics after state store is updated (committed). So I think we can refactor the test a little bit to make it easier to incorporate other `StateStore` externally.
### Does this PR introduce _any_ user-facing change?
No, dev only.
### How was this patch tested?
Unit test.
Closes#31183 from viirya/SPARK-34116.
Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
### What changes were proposed in this pull request?
This PR aims to strip auto-generated cast. The main logic is:
1. Add tag if Cast is specified by user.
2. Wrap `PrettyAttribute` in usePrettyExpression.
### Why are the changes needed?
Make sql consistent with dsl. Here is an inconsistent example before this PR:
```
-- output field name: FLOOR(1)
spark.emptyDataFrame.select(floor(lit(1)))
-- output field name: FLOOR(CAST(1 AS DOUBLE))
spark.sql("select floor(1)")
```
Note that, we don't remove the `Cast` so the auto-generated `Cast` can still work. The only changed place is `usePrettyExpression`, we use `PrettyAttribute` replace `Cast` to give a better sql string.
### Does this PR introduce _any_ user-facing change?
Yes, the default field name may change.
### How was this patch tested?
Add test and pass exists test.
Closes#31034 from ulysses-you/SPARK-33989.
Authored-by: ulysses-you <ulyssesyou18@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
### What changes were proposed in this pull request?
PartitionPruning push down pruningHasBenefit function into insertPredicate function to decrease calculate time
### Why are the changes needed?
to accelerate PartitionPruning prune calculate
### Does this PR introduce _any_ user-facing change?
NO
### How was this patch tested?
existed unit test
Closes#31122 from monkeyboy123/optimize-dynamic-pruning.
Authored-by: Dereck Li <monkeyboy.ljh@gmail.com>
Signed-off-by: Yuming Wang <yumwang@ebay.com>
