Repository: spark
Updated Branches:
refs/heads/master 18eaabb71 -> 3ba69b648
[SPARK-18634][PYSPARK][SQL] Corruption and Correctness issues with exploding
Python UDFs
## What changes were proposed in this pull request?
As reported in the Jira, there are some weird issues with exploding Python UDFs
in SparkSQL.
The following test code can reproduce it. Notice: the following test code is
reported to return wrong results in the Jira. However, as I tested on master
branch, it causes exception and so can't return any result.
>>> from pyspark.sql.functions import *
>>> from pyspark.sql.types import *
>>>
>>> df = spark.range(10)
>>>
>>> def return_range(value):
... return [(i, str(i)) for i in range(value - 1, value + 1)]
...
>>> range_udf = udf(return_range,
ArrayType(StructType([StructField("integer_val", IntegerType()),
...
StructField("string_val", StringType())])))
>>>
>>> df.select("id", explode(range_udf(df.id))).show()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/spark/python/pyspark/sql/dataframe.py", line 318, in show
print(self._jdf.showString(n, 20))
File "/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line
1133, in __call__
File "/spark/python/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319,
in get_return_value py4j.protocol.Py4JJavaError: An error occurred while
calling o126.showString.: java.lang.AssertionError: assertion failed
at scala.Predef$.assert(Predef.scala:156)
at
org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:120)
at
org.apache.spark.sql.execution.GenerateExec.consume(GenerateExec.scala:57)
The cause of this issue is, in `ExtractPythonUDFs` we insert
`BatchEvalPythonExec` to run PythonUDFs in batch. `BatchEvalPythonExec` will
add extra outputs (e.g., `pythonUDF0`) to original plan. In above case, the
original `Range` only has one output `id`. After `ExtractPythonUDFs`, the added
`BatchEvalPythonExec` has two outputs `id` and `pythonUDF0`.
Because the output of `GenerateExec` is given after analysis phase, in above
case, it is the combination of `id`, i.e., the output of `Range`, and `col`.
But in planning phase, we change `GenerateExec`'s child plan to
`BatchEvalPythonExec` with additional output attributes.
It will cause no problem in non wholestage codegen. Because when evaluating the
additional attributes are projected out the final output of `GenerateExec`.
However, as `GenerateExec` now supports wholestage codegen, the framework will
input all the outputs of the child plan to `GenerateExec`. Then when consuming
`GenerateExec`'s output data (i.e., calling `consume`), the number of output
attributes is different to the output variables in wholestage codegen.
To solve this issue, this patch only gives the generator's output to
`GenerateExec` after analysis phase. `GenerateExec`'s output is the combination
of its child plan's output and the generator's output. So when we change
`GenerateExec`'s child, its output is still correct.
## How was this patch tested?
Added test cases to PySpark.
Please review http://spark.apache.org/contributing.html before opening a pull
request.
Author: Liang-Chi Hsieh <[email protected]>
Closes #16120 from viirya/fix-py-udf-with-generator.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/3ba69b64
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/3ba69b64
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/3ba69b64
Branch: refs/heads/master
Commit: 3ba69b64852ccbf6d4ec05a021bc20616a09f574
Parents: 18eaabb
Author: Liang-Chi Hsieh <[email protected]>
Authored: Mon Dec 5 17:50:43 2016 -0800
Committer: Herman van Hovell <[email protected]>
Committed: Mon Dec 5 17:50:43 2016 -0800
----------------------------------------------------------------------
python/pyspark/sql/tests.py | 20 ++++++++++++++++++++
.../plans/logical/basicLogicalOperators.scala | 12 ++++++------
.../spark/sql/execution/GenerateExec.scala | 15 ++++++++++++---
.../spark/sql/execution/SparkStrategies.scala | 3 ++-
4 files changed, 40 insertions(+), 10 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/spark/blob/3ba69b64/python/pyspark/sql/tests.py
----------------------------------------------------------------------
diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py
index 9f34414..66a3490 100644
--- a/python/pyspark/sql/tests.py
+++ b/python/pyspark/sql/tests.py
@@ -384,6 +384,26 @@ class SQLTests(ReusedPySparkTestCase):
row = df.select(explode(f(*df))).groupBy().sum().first()
self.assertEqual(row[0], 10)
+ df = self.spark.range(3)
+ res = df.select("id", explode(f(df.id))).collect()
+ self.assertEqual(res[0][0], 1)
+ self.assertEqual(res[0][1], 0)
+ self.assertEqual(res[1][0], 2)
+ self.assertEqual(res[1][1], 0)
+ self.assertEqual(res[2][0], 2)
+ self.assertEqual(res[2][1], 1)
+
+ range_udf = udf(lambda value: list(range(value - 1, value + 1)),
ArrayType(IntegerType()))
+ res = df.select("id", explode(range_udf(df.id))).collect()
+ self.assertEqual(res[0][0], 0)
+ self.assertEqual(res[0][1], -1)
+ self.assertEqual(res[1][0], 0)
+ self.assertEqual(res[1][1], 0)
+ self.assertEqual(res[2][0], 1)
+ self.assertEqual(res[2][1], 0)
+ self.assertEqual(res[3][0], 1)
+ self.assertEqual(res[3][1], 1)
+
def test_udf_with_order_by_and_limit(self):
from pyspark.sql.functions import udf
my_copy = udf(lambda x: x, IntegerType())
http://git-wip-us.apache.org/repos/asf/spark/blob/3ba69b64/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
----------------------------------------------------------------------
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
index 7aaefc8..324662e 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
@@ -93,13 +93,13 @@ case class Generate(
override def producedAttributes: AttributeSet = AttributeSet(generatorOutput)
- def output: Seq[Attribute] = {
- val qualified = qualifier.map(q =>
- // prepend the new qualifier to the existed one
- generatorOutput.map(a => a.withQualifier(Some(q)))
- ).getOrElse(generatorOutput)
+ val qualifiedGeneratorOutput: Seq[Attribute] = qualifier.map { q =>
+ // prepend the new qualifier to the existed one
+ generatorOutput.map(a => a.withQualifier(Some(q)))
+ }.getOrElse(generatorOutput)
- if (join) child.output ++ qualified else qualified
+ def output: Seq[Attribute] = {
+ if (join) child.output ++ qualifiedGeneratorOutput else
qualifiedGeneratorOutput
}
}
http://git-wip-us.apache.org/repos/asf/spark/blob/3ba69b64/sql/core/src/main/scala/org/apache/spark/sql/execution/GenerateExec.scala
----------------------------------------------------------------------
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/GenerateExec.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/GenerateExec.scala
index f80214a..04b16af 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/GenerateExec.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/GenerateExec.scala
@@ -51,17 +51,26 @@ private[execution] sealed case class LazyIterator(func: ()
=> TraversableOnce[In
* it.
* @param outer when true, each input row will be output at least once, even
if the output of the
* given `generator` is empty. `outer` has no effect when `join`
is false.
- * @param output the output attributes of this node, which constructed in
analysis phase,
- * and we can not change it, as the parent node bound with it
already.
+ * @param generatorOutput the qualified output attributes of the generator of
this node, which
+ * constructed in analysis phase, and we can not change
it, as the
+ * parent node bound with it already.
*/
case class GenerateExec(
generator: Generator,
join: Boolean,
outer: Boolean,
- output: Seq[Attribute],
+ generatorOutput: Seq[Attribute],
child: SparkPlan)
extends UnaryExecNode with CodegenSupport {
+ override def output: Seq[Attribute] = {
+ if (join) {
+ child.output ++ generatorOutput
+ } else {
+ generatorOutput
+ }
+ }
+
override lazy val metrics = Map(
"numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output
rows"))
http://git-wip-us.apache.org/repos/asf/spark/blob/3ba69b64/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
----------------------------------------------------------------------
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
index 2308ae8..d88cbdf 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala
@@ -403,7 +403,8 @@ abstract class SparkStrategies extends
QueryPlanner[SparkPlan] {
execution.UnionExec(unionChildren.map(planLater)) :: Nil
case g @ logical.Generate(generator, join, outer, _, _, child) =>
execution.GenerateExec(
- generator, join = join, outer = outer, g.output, planLater(child))
:: Nil
+ generator, join = join, outer = outer, g.qualifiedGeneratorOutput,
+ planLater(child)) :: Nil
case logical.OneRowRelation =>
execution.RDDScanExec(Nil, singleRowRdd, "OneRowRelation") :: Nil
case r: logical.Range =>
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