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From Marcelo Valle <marcelo.va...@ktech.com>
Subject help understanding physical plan
Date Tue, 13 Aug 2019 14:45:44 GMT
Hi,

I have a job running on AWS EMR. It's basically a join between 2 tables
(parquet files on s3), one somehow large (around 50 gb) and other small
(less than 1gb).
The small table is the result of other operations, but it was a dataframe
with `.persist(StorageLevel.MEMORY_AND_DISK_SER)` and the count on this
dataframe finishes quickly.
When I run my "LEFT_ANTI" join, I get the execution plan down bellow. While
most of my jobs on larges amount of data take max 1 h on this cluster, this
one takes almost 1 day to complete.

What could I be doing wrong? I am trying to analyze the plan, but I can't
find anything that justify the slowness. It has 2 shuffles followed by a
zip, but other jobs have similar things and they are not that slow.

Could anyone point me to possible actions I could take to investigate this?

Thanks,
Marcelo.

== Physical Plan ==
*(2) Project [USAGE_AGGREGATED_METADATA_ID#1493,
SENDER_RECORDING_IDENTIFIER#1499, AIP127258 AS SENDER_IP_ID#1702,
USAGE_AGGREGATED_METADATA_HASH#1513]
+- *(2) BroadcastHashJoin [coalesce(USAGE_AGGREGATED_METADATA_ID#1493, ),
coalesce(SENDER_RECORDING_IDENTIFIER#1499, )],
[coalesce(USAGE_AGGREGATED_METADATA_ID#356, ),
coalesce(SENDER_RECORDING_IDENTIFIER#357, )], LeftAnti, BuildRight,
((USAGE_AGGREGATED_METADATA_ID#356 <=> USAGE_AGGREGATED_METADATA_ID#1493)
&& (SENDER_RECORDING_IDENTIFIER#357 <=> SENDER_RECORDING_IDENTIFIER#1499))
   :- InMemoryTableScan [USAGE_AGGREGATED_METADATA_ID#1493,
SENDER_RECORDING_IDENTIFIER#1499, USAGE_AGGREGATED_METADATA_HASH#1513]
   :     +- InMemoryRelation [USAGE_AGGREGATED_METADATA_ID#1493, ISRC#1494,
ISWC#1495, RECORDING_TITLE#1496, RECORDING_DISPLAY_ARTIST#1497,
WORK_WRITERS#1498, SENDER_RECORDING_IDENTIFIER#1499,
RECORDING_VERSION_TITLE#1500, WORK_TITLE#1501, CONTENT_TYPE#1502,
USAGE_AGGREGATED_METADATA_HASH#1513], StorageLevel(disk, memory, 1 replicas)
   :           +- *(2) Project [ID#328 AS
USAGE_AGGREGATED_METADATA_ID#1493, isrc#289 AS ISRC#1494, iswc#290 AS
ISWC#1495, track_name#291 AS RECORDING_TITLE#1496, artist_name#292 AS
RECORDING_DISPLAY_ARTIST#1497, work_writer_names#293 AS WORK_WRITERS#1498,
uri#286 AS SENDER_RECORDING_IDENTIFIER#1499, null AS
RECORDING_VERSION_TITLE#1500, null AS WORK_TITLE#1501, SOUND AS
CONTENT_TYPE#1502, UDF(array(isrc#289, track_name#291, null,
artist_name#292, iswc#290, null, work_writer_names#293, SOUND)) AS
USAGE_AGGREGATED_METADATA_HASH#1513]
   :              +- *(2) BroadcastHashJoin [coalesce(isrc_1#1419, ),
coalesce(iswc_1#1420, ), coalesce(track_name_1#1421, ),
coalesce(artist_name_1#1422, ), coalesce(work_writer_names_1#1423, )],
[coalesce(isrc#289, ), coalesce(iswc#290, ), coalesce(track_name#291, ),
coalesce(artist_name#292, ), coalesce(work_writer_names#293, )], Inner,
BuildLeft, (((((isrc#289 <=> isrc_1#1419) && (iswc#290 <=> iswc_1#1420))
&&
(track_name#291 <=> track_name_1#1421)) && (artist_name#292 <=>
artist_name_1#1422)) && (work_writer_names#293 <=>
work_writer_names_1#1423))
   :                 :- BroadcastExchange
HashedRelationBroadcastMode(List(coalesce(input[1, string, true], ),
coalesce(input[2, string, true], ), coalesce(input[3, string, true], ),
coalesce(input[4, string, true], ), coalesce(input[5, string, true], )))
   :                 :  +- *(1) Project [ID#328, isrc#289 AS isrc_1#1419,
iswc#290 AS iswc_1#1420, track_name#291 AS track_name_1#1421,
artist_name#292 AS artist_name_1#1422, work_writer_names#293 AS
work_writer_names_1#1423]
   :                 :     +- *(1) Filter isnotnull(ID#328)
   :                 :        +- InMemoryTableScan [ID#328,
artist_name#292, isrc#289, iswc#290, track_name#291,
work_writer_names#293], [isnotnull(ID#328)]
   :                 :              +- InMemoryRelation [ID#328, isrc#289,
iswc#290, track_name#291, artist_name#292, work_writer_names#293],
StorageLevel(disk, memory, 1 replicas)
   :                 :                    +- *(2) Project [ID#328,
isrc#289, iswc#290, track_name#291, artist_name#292, work_writer_names#293]
   :                 :                       +- *(2) BroadcastHashJoin
[coalesce(ISRC#329, ), coalesce(ISWC#330, ), coalesce(RECORDING_TITLE#331,
), coalesce(RECORDING_DISPLAY_ARTIST#332, ), coalesce(WORK_WRITERS#333, )],
[coalesce(isrc#289, ), coalesce(iswc#290, ), coalesce(track_name#291, ),
coalesce(substring(artist_name#292, 0, 1000), ),
coalesce(work_writer_names#293, )], RightOuter, BuildLeft, (((((isrc#289
<=> ISRC#329) && (iswc#290 <=> ISWC#330)) && (track_name#291 <=>
RECORDING_TITLE#331)) && (substring(artist_name#292, 0, 1000) <=>
RECORDING_DISPLAY_ARTIST#332)) && (work_writer_names#293 <=>
WORK_WRITERS#333))
   :                 :                          :- BroadcastExchange
HashedRelationBroadcastMode(List(coalesce(input[1, string, true], ),
coalesce(input[2, string, true], ), coalesce(input[3, string, true], ),
coalesce(input[4, string, true], ), coalesce(input[5, string, true], )))
   :                 :                          :  +- *(1) Project [ID#328,
ISRC#329, ISWC#330, RECORDING_TITLE#331, RECORDING_DISPLAY_ARTIST#332,
WORK_WRITERS#333]
   :                 :                          :     +- *(1) Filter
((isnull(WORK_TITLE#334) && isnull(RECORDING_VERSION_TITLE#335)) &&
(CONTENT_TYPE#336 <=> SOUND))
   :                 :                          :        +- *(1) FileScan
parquet
[ID#328,ISRC#329,ISWC#330,RECORDING_TITLE#331,RECORDING_DISPLAY_ARTIST#332,WORK_WRITERS#333,WORK_TITLE#334,RECORDING_VERSION_TITLE#335,CONTENT_TYPE#336]
Batched: true, Format: Parquet, Location:
InMemoryFileIndex[file:/Users/marcelo.valle/git/amra-cloud-usage-ingestion/target/test-classes/ua...,
PartitionFilters: [], PushedFilters: [IsNull(WORK_TITLE),
IsNull(RECORDING_VERSION_TITLE), EqualNullSafe(CONTENT_TYPE,SOUND)],
ReadSchema:
struct<ID:string,ISRC:string,ISWC:string,RECORDING_TITLE:string,RECORDING_DISPLAY_ARTIST:string,W...
   :                 :                          +- *(2) FileScan parquet
[isrc#289,iswc#290,track_name#291,artist_name#292,work_writer_names#293]
Batched: true, Format: Parquet, Location:
InMemoryFileIndex[file:/Users/marcelo.valle/git/amra-cloud-usage-ingestion/target/test-classes/ua...,
PartitionFilters: [], PushedFilters: [], ReadSchema:
struct<isrc:string,iswc:string,track_name:string,artist_name:string,work_writer_names:string>
   :                 +- *(2) FileScan parquet
[uri#286,isrc#289,iswc#290,track_name#291,artist_name#292,work_writer_names#293]
Batched: true, Format: Parquet, Location:
InMemoryFileIndex[file:/Users/marcelo.valle/git/amra-cloud-usage-ingestion/target/test-classes/ua...,
PartitionFilters: [], PushedFilters: [], ReadSchema:
struct<uri:string,isrc:string,iswc:string,track_name:string,artist_name:string,work_writer_names:...
   +- BroadcastExchange HashedRelationBroadcastMode(List(coalesce(input[0,
string, true], ), coalesce(input[1, string, true], )))
      +- *(1) FileScan parquet
[USAGE_AGGREGATED_METADATA_ID#356,SENDER_RECORDING_IDENTIFIER#357] Batched:
true, Format: Parquet, Location:
InMemoryFileIndex[file:/Users/marcelo.valle/git/amra-cloud-usage-ingestion/target/test-classes/ua...,
PartitionFilters: [], PushedFilters: [], ReadSchema:
struct<USAGE_AGGREGATED_METADATA_ID:string,SENDER_RECORDING_IDENTIFIER:string>

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