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@CodingCat CodingCat commented Oct 27, 2017

  • add configuration entry for partition level metadata

  • CachedRDD and CachedRDDPartition framework

  • Implement update of partition level metadata in InMemoryRelation

  • Implement Filter Evaluation in InMemoryTableScanExec

  • Implement CachedRDD compute method

  • add test

fix compilation of tests

fix tests

revise the test

fix test

revise the test

add missing file

revise the test

revise the test

revise the test

revise the test

revise the test

revise the test

revise the test

revise the test
@CodingCat CodingCat force-pushed the partition_level_pruning branch 2 times, most recently from 9406c48 to 46d68db Compare November 11, 2017 04:26
test for remove metadata block

fix the test

fix the test

fix the test
@CodingCat CodingCat force-pushed the master branch 2 times, most recently from 62a34c1 to 9b87ba8 Compare December 25, 2017 02:34
CodingCat pushed a commit that referenced this pull request Jun 16, 2020
### What changes were proposed in this pull request?

This PR proposes to make `PythonFunction` holds `Seq[Byte]` instead of `Array[Byte]` to be able to compare if the byte array has the same values for the cache manager.

### Why are the changes needed?

Currently the cache manager doesn't use the cache for `udf` if the `udf` is created again even if the functions is the same.

```py
>>> func = lambda x: x

>>> df = spark.range(1)
>>> df.select(udf(func)("id")).cache()
```
```py
>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
*(2) Project [pythonUDF0#14 AS <lambda>(id)apache#12]
+- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#14]
 +- *(1) Range (0, 1, step=1, splits=12)
```

This is because `PythonFunction` holds `Array[Byte]`, and `equals` method of array equals only when the both array is the same instance.

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

Yes, if the user reuse the Python function for the UDF, the cache manager will detect the same function and use the cache for it.

### How was this patch tested?

I added a test case and manually.

```py
>>> df.select(udf(func)("id")).explain()
== Physical Plan ==
InMemoryTableScan [<lambda>(id)apache#12]
   +- InMemoryRelation [<lambda>(id)apache#12], StorageLevel(disk, memory, deserialized, 1 replicas)
         +- *(2) Project [pythonUDF0#5 AS <lambda>(id)#3]
            +- BatchEvalPython [<lambda>(id#0L)], [pythonUDF0#5]
               +- *(1) Range (0, 1, step=1, splits=12)
```

Closes apache#28774 from ueshin/issues/SPARK-31945/udf_cache.

Authored-by: Takuya UESHIN <ueshin@databricks.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
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We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable.
If you'd like to revive this PR, please reopen it and ask a committer to remove the Stale tag!

@github-actions github-actions bot added the Stale label Jun 17, 2020
@github-actions github-actions bot closed this Jun 18, 2020
CodingCat pushed a commit that referenced this pull request Aug 31, 2020
… without WindowExpression

### What changes were proposed in this pull request?

Add WindowFunction check at `CheckAnalysis`.

### Why are the changes needed?
Provide friendly error msg.

**BEFORE**
```scala
scala> sql("select rank() from values(1)").show
java.lang.UnsupportedOperationException: Cannot generate code for expression: rank()
```

**AFTER**
```scala
scala> sql("select rank() from values(1)").show
org.apache.spark.sql.AnalysisException: Window function rank() requires an OVER clause.;;
Project [rank() AS RANK()#3]
+- LocalRelation [col1#2]
```

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

Yes, user wiill be given a better error msg.

### How was this patch tested?

Pass the newly added UT.

Closes apache#28808 from ulysses-you/SPARK-31975.

Authored-by: ulysses <youxiduo@weidian.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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