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@xuanyuanking xuanyuanking commented Nov 2, 2018

What changes were proposed in this pull request?

Add UT to check:

  1. Accumulator only updated once.
  2. Map status overwrite by last success task.

How was this patch tested?

New UT

cloud-fan pushed a commit that referenced this pull request Jun 10, 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)#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)#12]
   +- InMemoryRelation [<lambda>(id)#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 16, 2021
@cloud-fan cloud-fan closed this Jun 16, 2021
cloud-fan pushed a commit that referenced this pull request Feb 27, 2024
…n properly

### What changes were proposed in this pull request?
Make `ResolveRelations` handle plan id properly

### Why are the changes needed?
bug fix for Spark Connect, it won't affect classic Spark SQL

before this PR:
```
from pyspark.sql import functions as sf

spark.range(10).withColumn("value_1", sf.lit(1)).write.saveAsTable("test_table_1")
spark.range(10).withColumnRenamed("id", "index").withColumn("value_2", sf.lit(2)).write.saveAsTable("test_table_2")

df1 = spark.read.table("test_table_1")
df2 = spark.read.table("test_table_2")
df3 = spark.read.table("test_table_1")

join1 = df1.join(df2, on=df1.id==df2.index).select(df2.index, df2.value_2)
join2 = df3.join(join1, how="left", on=join1.index==df3.id)

join2.schema
```

fails with
```
AnalysisException: [CANNOT_RESOLVE_DATAFRAME_COLUMN] Cannot resolve dataframe column "id". It's probably because of illegal references like `df1.select(df2.col("a"))`. SQLSTATE: 42704
```

That is due to existing plan caching in `ResolveRelations` doesn't work with Spark Connect

```
=== Applying Rule org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations ===
 '[#12]Join LeftOuter, '`==`('index, 'id)                     '[#12]Join LeftOuter, '`==`('index, 'id)
!:- '[#9]UnresolvedRelation [test_table_1], [], false         :- '[#9]SubqueryAlias spark_catalog.default.test_table_1
!+- '[#11]Project ['index, 'value_2]                          :  +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
!   +- '[#10]Join Inner, '`==`('id, 'index)                   +- '[#11]Project ['index, 'value_2]
!      :- '[#7]UnresolvedRelation [test_table_1], [], false      +- '[#10]Join Inner, '`==`('id, 'index)
!      +- '[#8]UnresolvedRelation [test_table_2], [], false         :- '[#9]SubqueryAlias spark_catalog.default.test_table_1
!                                                                   :  +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
!                                                                   +- '[#8]SubqueryAlias spark_catalog.default.test_table_2
!                                                                      +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_2`, [], false

Can not resolve 'id with plan 7
```

`[#7]UnresolvedRelation [test_table_1], [], false` was wrongly resolved to the cached one
```
:- '[#9]SubqueryAlias spark_catalog.default.test_table_1
   +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
```

### Does this PR introduce _any_ user-facing change?
yes, bug fix

### How was this patch tested?
added ut

### Was this patch authored or co-authored using generative AI tooling?
ci

Closes apache#45214 from zhengruifeng/connect_fix_read_join.

Authored-by: Ruifeng Zheng <ruifengz@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>
cloud-fan pushed a commit that referenced this pull request May 7, 2024
…plan properly

### What changes were proposed in this pull request?
Make `ResolveRelations` handle plan id properly

cherry-pick bugfix apache#45214 to 3.5

### Why are the changes needed?
bug fix for Spark Connect, it won't affect classic Spark SQL

before this PR:
```
from pyspark.sql import functions as sf

spark.range(10).withColumn("value_1", sf.lit(1)).write.saveAsTable("test_table_1")
spark.range(10).withColumnRenamed("id", "index").withColumn("value_2", sf.lit(2)).write.saveAsTable("test_table_2")

df1 = spark.read.table("test_table_1")
df2 = spark.read.table("test_table_2")
df3 = spark.read.table("test_table_1")

join1 = df1.join(df2, on=df1.id==df2.index).select(df2.index, df2.value_2)
join2 = df3.join(join1, how="left", on=join1.index==df3.id)

join2.schema
```

fails with
```
AnalysisException: [CANNOT_RESOLVE_DATAFRAME_COLUMN] Cannot resolve dataframe column "id". It's probably because of illegal references like `df1.select(df2.col("a"))`. SQLSTATE: 42704
```

That is due to existing plan caching in `ResolveRelations` doesn't work with Spark Connect

```
=== Applying Rule org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations ===
 '[#12]Join LeftOuter, '`==`('index, 'id)                     '[#12]Join LeftOuter, '`==`('index, 'id)
!:- '[#9]UnresolvedRelation [test_table_1], [], false         :- '[#9]SubqueryAlias spark_catalog.default.test_table_1
!+- '[#11]Project ['index, 'value_2]                          :  +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
!   +- '[#10]Join Inner, '`==`('id, 'index)                   +- '[#11]Project ['index, 'value_2]
!      :- '[#7]UnresolvedRelation [test_table_1], [], false      +- '[#10]Join Inner, '`==`('id, 'index)
!      +- '[#8]UnresolvedRelation [test_table_2], [], false         :- '[#9]SubqueryAlias spark_catalog.default.test_table_1
!                                                                   :  +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
!                                                                   +- '[#8]SubqueryAlias spark_catalog.default.test_table_2
!                                                                      +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_2`, [], false

Can not resolve 'id with plan 7
```

`[#7]UnresolvedRelation [test_table_1], [], false` was wrongly resolved to the cached one
```
:- '[#9]SubqueryAlias spark_catalog.default.test_table_1
   +- 'UnresolvedCatalogRelation `spark_catalog`.`default`.`test_table_1`, [], false
```

### Does this PR introduce _any_ user-facing change?
yes, bug fix

### How was this patch tested?
added ut

### Was this patch authored or co-authored using generative AI tooling?
ci

Closes apache#46291 from zhengruifeng/connect_fix_read_join_35.

Authored-by: Ruifeng Zheng <ruifengz@apache.org>
Signed-off-by: Ruifeng Zheng <ruifengz@apache.org>
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