Franck Tago created SPARK-44768:
-----------------------------------
Summary: Improve WSCG handling of row buffer by accounting for
executor memory
Key: SPARK-44768
URL: https://issues.apache.org/jira/browse/SPARK-44768
Project: Spark
Issue Type: Bug
Components: Optimizer
Affects Versions: 3.4.1, 3.4.0, 3.3.2
Reporter: Franck Tago
consider a scenario where you flatten a nested array
// e.g you can use the following steps to create the dataframe
/create a partClass
case class partClass (PARTNAME: String , PartNumber: String , PartPrice :
Double )
//create a nested array array class
case class array_array_class (
col_int: Int,
arr_arr_string : Seq[Seq[String]],
arr_arr_bigint : Seq[Seq[Long]],
col_string : String,
parts_s : Seq[Seq[partClass]]
)
//create a dataframe
var df_array_array = sc.parallelize(
Seq(
(1,Seq(Seq("a","b" ,"c" ,"d") ,Seq("aa","bb" ,"cc","dd")) ,
Seq(Seq(1000,20000), Seq(30000,-10000)),"ItemPart1",
Seq(Seq(partClass("PNAME1","P1",20.75),partClass("PNAME1_1","P1_1",30.75)))
) ,
(2,Seq(Seq("ab","bc" ,"cd" ,"de") ,Seq("aab","bbc"
,"ccd","dde"),Seq("aaaaaabbbbb")) , Seq(Seq(-1000,-20000,-1,-2),
Seq(0,30000,-10000)),"ItemPart2",
Seq(Seq(partClass("PNAME2","P2",170.75),partClass("PNAME2_1","P2_1",33.75),partClass("PNAME2_2","P2_2",73.75)))
)
)
).toDF("c1" ,"c2" ,"c3" ,"c4" ,"c5")
//explode a nested array
var result = df_array_array.select( col("c1"),
explode(col("c2"))).select('c1 , explode('col))
result.explain
The physical for this operator is seen below.
-------------------------------------
Physical plan
== Physical Plan ==
*(1) Generate explode(col#27), [c1#17], false, [col#30]
+- *(1) Filter ((size(col#27, true) > 0) AND isnotnull(col#27))
+- *(1) Generate explode(c2#18), [c1#17], false, [col#27]
+- *(1) Project [_1#6 AS c1#17, _2#7 AS c2#18]
+- *(1) Filter ((size(_2#7, true) > 0) AND isnotnull(_2#7))
+- *(1) SerializeFromObject [knownnotnull(assertnotnull(input[0,
scala.Tuple5, true]))._1 AS _1#6, mapobjects(lambdavariable(MapObject,
ObjectType(class java.lang.Object), true, -1),
mapobjects(lambdavariable(MapObject, ObjectType(class java.lang.Object), true,
-2), staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType,
fromString, validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -2), StringType, ObjectType(class java.lang.String)),
true, false, true), validateexternaltype(lambdavariable(MapObject,
ObjectType(class java.lang.Object), true, -1), ArrayType(StringType,true),
ObjectType(interface scala.collection.Seq)), None),
knownnotnull(assertnotnull(input[0, scala.Tuple5, true]))._2, None) AS _2#7,
mapobjects(lambdavariable(MapObject, ObjectType(class java.lang.Object), true,
-3), mapobjects(lambdavariable(MapObject, ObjectType(class java.lang.Object),
true, -4), assertnotnull(validateexternaltype(lambdavariable(MapObject,
ObjectType(class java.lang.Object), true, -4), IntegerType, IntegerType)),
validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -3), ArrayType(IntegerType,false),
ObjectType(interface scala.collection.Seq)), None),
knownnotnull(assertnotnull(input[0, scala.Tuple5, true]))._3, None) AS _3#8,
staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType,
fromString, knownnotnull(assertnotnull(input[0, scala.Tuple5, true]))._4, true,
false, true) AS _4#9, mapobjects(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -5), mapobjects(lambdavariable(MapObject,
ObjectType(class java.lang.Object), true, -6), if
(isnull(validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -6), StructField(PARTNAME,StringType,true),
StructField(PartNumber,StringType,true),
StructField(PartPrice,DoubleType,false), ObjectType(class
$line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$partClass)))) null else
named_struct(PARTNAME, staticinvoke(class
org.apache.spark.unsafe.types.UTF8String, StringType, fromString,
knownnotnull(validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -6), StructField(PARTNAME,StringType,true),
StructField(PartNumber,StringType,true),
StructField(PartPrice,DoubleType,false), ObjectType(class
$line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$partClass))).PARTNAME, true,
false, true), PartNumber, staticinvoke(class
org.apache.spark.unsafe.types.UTF8String, StringType, fromString,
knownnotnull(validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -6), StructField(PARTNAME,StringType,true),
StructField(PartNumber,StringType,true),
StructField(PartPrice,DoubleType,false), ObjectType(class
$line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$partClass))).PartNumber, true,
false, true), PartPrice,
knownnotnull(validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -6), StructField(PARTNAME,StringType,true),
StructField(PartNumber,StringType,true),
StructField(PartPrice,DoubleType,false), ObjectType(class
$line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw$partClass))).PartPrice),
validateexternaltype(lambdavariable(MapObject, ObjectType(class
java.lang.Object), true, -5),
ArrayType(StructType(StructField(PARTNAME,StringType,true),StructField(PartNumber,StringType,true),StructField(PartPrice,DoubleType,false)),true),
ObjectType(interface scala.collection.Seq)), None),
knownnotnull(assertnotnull(input[0, scala.Tuple5, true]))._5, None) AS _5#10]
+- Scan[obj#5]
Because the explode function can create multiple rows from a single row , we
should account for the memory available when adding rows to the buffer .
This is even more important when we are exploding nested arrays .
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