{"Event":"SparkListenerLogStart","Spark Version":"3.5.1"}
{"Event":"SparkListenerResourceProfileAdded","Resource Profile Id":0,"Executor Resource Requests":{"memory":{"Resource Name":"memory","Amount":1024,"Discovery Script":"","Vendor":""},"offHeap":{"Resource Name":"offHeap","Amount":0,"Discovery Script":"","Vendor":""}},"Task Resource Requests":{"cpus":{"Resource Name":"cpus","Amount":1.0}}}
{"Event":"SparkListenerBlockManagerAdded","Block Manager ID":{"Executor ID":"driver","Host":"73850a3d530b","Port":40655},"Maximum Memory":455501414,"Timestamp":1783414873958,"Maximum Onheap Memory":455501414,"Maximum Offheap Memory":0}
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{"Event":"org.apache.spark.sql.execution.ui.SparkListenerSQLExecutionStart","executionId":0,"rootExecutionId":0,"description":"parquet at NativeMethodAccessorImpl.java:0","details":"org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:792)\njava.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\njava.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)\njava.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\njava.base/java.lang.reflect.Method.invoke(Method.java:569)\npy4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\npy4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)\npy4j.Gateway.invoke(Gateway.java:282)\npy4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\npy4j.commands.CallCommand.execute(CallCommand.java:79)\npy4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)\npy4j.ClientServerConnection.run(ClientServerConnection.java:106)\njava.base/java.lang.Thread.run(Thread.java:840)","physicalPlanDescription":"== Physical Plan ==\nAdaptiveSparkPlan (32)\n+- Execute InsertIntoHadoopFsRelationCommand (31)\n   +- WriteFiles (30)\n      +- Project (29)\n         +- HashAggregate (28)\n            +- HashAggregate (27)\n               +- Project (26)\n                  +- BroadcastHashJoin Inner BuildRight (25)\n                     :- Project (18)\n                     :  +- BroadcastHashJoin Inner BuildRight (17)\n                     :     :- Project (13)\n                     :     :  +- BroadcastHashJoin Inner BuildRight (12)\n                     :     :     :- HashAggregate (8)\n                     :     :     :  +- Exchange (7)\n                     :     :     :     +- HashAggregate (6)\n                     :     :     :        +- HashAggregate (5)\n                     :     :     :           +- Exchange (4)\n                     :     :     :              +- HashAggregate (3)\n                     :     :     :                 +- Filter (2)\n                     :     :     :                    +- Scan parquet  (1)\n                     :     :     +- BroadcastExchange (11)\n                     :     :        +- Filter (10)\n                     :     :           +- Scan parquet  (9)\n                     :     +- BroadcastExchange (16)\n                     :        +- Filter (15)\n                     :           +- Scan parquet  (14)\n                     +- BroadcastExchange (24)\n                        +- HashAggregate (23)\n                           +- Exchange (22)\n                              +- HashAggregate (21)\n                                 +- Filter (20)\n                                    +- Scan parquet  (19)\n\n\n(1) Scan parquet \nOutput [3]: [user_id#0, lesson_id#1, course_id#2]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet]\nPushedFilters: [IsNotNull(user_id), IsNotNull(course_id)]\nReadSchema: struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(2) Filter\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(3) HashAggregate\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(4) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=112]\n\n(5) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(6) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(7) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=116]\n\n(8) HashAggregate\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(9) Scan parquet \nOutput [2]: [user_id#8, name#9]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_user.parquet]\nPushedFilters: [IsNotNull(user_id)]\nReadSchema: struct<user_id:decimal(20,0),name:string>\n\n(10) Filter\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(11) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=119]\n\n(12) BroadcastHashJoin\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(13) Project\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(14) Scan parquet \nOutput [2]: [course_id#18, title#19]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_course.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<course_id:decimal(20,0),title:string>\n\n(15) Filter\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(16) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=123]\n\n(17) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(18) Project\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(19) Scan parquet \nOutput [2]: [lesson_id#26, course_id#27]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_lesson.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(20) Filter\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(21) HashAggregate\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(22) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=126]\n\n(23) HashAggregate\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(24) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=129]\n\n(25) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(26) Project\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(27) HashAggregate\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(28) HashAggregate\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(29) Project\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(30) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(31) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(32) AdaptiveSparkPlan\nOutput: []\nArguments: isFinalPlan=false\n\n","sparkPlanInfo":{"nodeName":"AdaptiveSparkPlan","simpleString":"AdaptiveSparkPlan isFinalPlan=false","children":[{"nodeName":"Execute InsertIntoHadoopFsRelationCommand","simpleString":"Execute InsertIntoHadoopFsRelationCommand s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]","children":[{"nodeName":"WriteFiles","simpleString":"WriteFiles","children":[{"nodeName":"Project","simpleString":"Project [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L], functions=[max(lessons_viewed#49L)])","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L], functions=[partial_max(lessons_viewed#49L)])","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [course_id#2], [course_id#27], Inner, BuildRight, false","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [course_id#2], [course_id#18], Inner, BuildRight, false","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [user_id#0], [user_id#8], Inner, BuildRight, false","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2], functions=[count(distinct lesson_id#1)])","children":[{"nodeName":"Exchange","simpleString":"Exchange hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=116]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2], functions=[partial_count(distinct lesson_id#1)])","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2, lesson_id#1], functions=[])","children":[{"nodeName":"Exchange","simpleString":"Exchange hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=112]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2, lesson_id#1], functions=[])","children":[{"nodeName":"Filter","simpleString":"Filter (isnotnull(user_id#0) AND isnotnull(course_id#2))","children":[{"nodeName":"Scan parquet ","simpleString":"FileScan parquet [user_id#0,lesson_id#1,course_id#2] Batched: true, DataFilters: [isnotnull(user_id#0), isnotnull(course_id#2)], Format: Parquet, Location: InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet], PartitionFilters: [], PushedFilters: [IsNotNull(user_id), IsNotNull(course_id)], ReadSchema: struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>","children":[],"metadata":{"Location":"InMemoryFileIndex(1 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paths)[s3a://apavlovets-bucket/ch_core/core_dim_user.parquet]","ReadSchema":"struct<user_id:decimal(20,0),name:string>","Format":"Parquet","Batched":"true","PartitionFilters":"[]","PushedFilters":"[IsNotNull(user_id)]","DataFilters":"[isnotnull(user_id#8)]"},"metrics":[{"name":"number of files read","accumulatorId":244,"metricType":"sum"},{"name":"scan time","accumulatorId":243,"metricType":"timing"},{"name":"metadata time","accumulatorId":245,"metricType":"timing"},{"name":"size of files read","accumulatorId":246,"metricType":"size"},{"name":"number of output rows","accumulatorId":242,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":241,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"time to broadcast","accumulatorId":240,"metricType":"timing"},{"name":"time to build","accumulatorId":239,"metricType":"timing"},{"name":"time to collect","accumulatorId":238,"metricType":"timing"},{"name":"number of output rows","accumulatorId":237,"metricType":"sum"},{"name":"data size","accumulatorId":236,"metricType":"size"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":161,"metricType":"sum"}]}],"metadata":{},"metrics":[]},{"nodeName":"BroadcastExchange","simpleString":"BroadcastExchange HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=123]","children":[{"nodeName":"Filter","simpleString":"Filter isnotnull(course_id#18)","children":[{"nodeName":"Scan parquet ","simpleString":"FileScan parquet [course_id#18,title#19] Batched: true, DataFilters: [isnotnull(course_id#18)], Format: Parquet, Location: InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_dim_course.parquet], PartitionFilters: [], PushedFilters: [IsNotNull(course_id)], ReadSchema: struct<course_id:decimal(20,0),title:string>","children":[],"metadata":{"Location":"InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_dim_course.parquet]","ReadSchema":"struct<course_id:decimal(20,0),title:string>","Format":"Parquet","Batched":"true","PartitionFilters":"[]","PushedFilters":"[IsNotNull(course_id)]","DataFilters":"[isnotnull(course_id#18)]"},"metrics":[{"name":"number of files read","accumulatorId":255,"metricType":"sum"},{"name":"scan time","accumulatorId":254,"metricType":"timing"},{"name":"metadata time","accumulatorId":256,"metricType":"timing"},{"name":"size of files read","accumulatorId":257,"metricType":"size"},{"name":"number of output rows","accumulatorId":253,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":252,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"time to broadcast","accumulatorId":251,"metricType":"timing"},{"name":"time to build","accumulatorId":250,"metricType":"timing"},{"name":"time to collect","accumulatorId":249,"metricType":"timing"},{"name":"number of output rows","accumulatorId":248,"metricType":"sum"},{"name":"data size","accumulatorId":247,"metricType":"size"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":160,"metricType":"sum"}]}],"metadata":{},"metrics":[]},{"nodeName":"BroadcastExchange","simpleString":"BroadcastExchange HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=129]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[course_id#27], functions=[count(lesson_id#26)])","children":[{"nodeName":"Exchange","simpleString":"Exchange hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=126]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[course_id#27], functions=[partial_count(lesson_id#26)])","children":[{"nodeName":"Filter","simpleString":"Filter isnotnull(course_id#27)","children":[{"nodeName":"Scan parquet ","simpleString":"FileScan parquet [lesson_id#26,course_id#27] Batched: true, DataFilters: [isnotnull(course_id#27)], Format: Parquet, Location: InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_dim_lesson.parquet], PartitionFilters: [], PushedFilters: [IsNotNull(course_id)], ReadSchema: struct<lesson_id:decimal(20,0),course_id:decimal(20,0)>","children":[],"metadata":{"Location":"InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_dim_lesson.parquet]","ReadSchema":"struct<lesson_id:decimal(20,0),course_id:decimal(20,0)>","Format":"Parquet","Batched":"true","PartitionFilters":"[]","PushedFilters":"[IsNotNull(course_id)]","DataFilters":"[isnotnull(course_id#27)]"},"metrics":[{"name":"number of files read","accumulatorId":300,"metricType":"sum"},{"name":"scan time","accumulatorId":299,"metricType":"timing"},{"name":"metadata time","accumulatorId":301,"metricType":"timing"},{"name":"size of files read","accumulatorId":302,"metricType":"size"},{"name":"number of output rows","accumulatorId":298,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":297,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"spill size","accumulatorId":293,"metricType":"size"},{"name":"time in aggregation build","accumulatorId":294,"metricType":"timing"},{"name":"peak memory","accumulatorId":292,"metricType":"size"},{"name":"number of output rows","accumulatorId":291,"metricType":"sum"},{"name":"number of sort fallback tasks","accumulatorId":296,"metricType":"sum"},{"name":"avg hash probes per key","accumulatorId":295,"metricType":"average"}]}],"metadata":{},"metrics":[{"name":"shuffle records written","accumulatorId":289,"metricType":"sum"},{"name":"local merged chunks fetched","accumulatorId":283,"metricType":"sum"},{"name":"shuffle write time","accumulatorId":290,"metricType":"nsTiming"},{"name":"remote merged bytes read","accumulatorId":284,"metricType":"size"},{"name":"local merged blocks fetched","accumulatorId":281,"metricType":"sum"},{"name":"corrupt merged block chunks","accumulatorId":278,"metricType":"sum"},{"name":"remote merged reqs duration","accumulatorId":287,"metricType":"timing"},{"name":"remote merged blocks fetched","accumulatorId":280,"metricType":"sum"},{"name":"records read","accumulatorId":277,"metricType":"sum"},{"name":"local bytes read","accumulatorId":275,"metricType":"size"},{"name":"fetch wait time","accumulatorId":276,"metricType":"timing"},{"name":"remote bytes read","accumulatorId":273,"metricType":"size"},{"name":"merged fetch fallback count","accumulatorId":279,"metricType":"sum"},{"name":"local blocks read","accumulatorId":272,"metricType":"sum"},{"name":"remote merged chunks fetched","accumulatorId":282,"metricType":"sum"},{"name":"remote blocks read","accumulatorId":271,"metricType":"sum"},{"name":"data size","accumulatorId":269,"metricType":"size"},{"name":"local merged bytes read","accumulatorId":285,"metricType":"size"},{"name":"number of partitions","accumulatorId":270,"metricType":"sum"},{"name":"remote reqs duration","accumulatorId":286,"metricType":"timing"},{"name":"remote bytes read to disk","accumulatorId":274,"metricType":"size"},{"name":"shuffle bytes written","accumulatorId":288,"metricType":"size"}]}],"metadata":{},"metrics":[{"name":"spill size","accumulatorId":265,"metricType":"size"},{"name":"time in aggregation build","accumulatorId":266,"metricType":"timing"},{"name":"peak memory","accumulatorId":264,"metricType":"size"},{"name":"number of output rows","accumulatorId":263,"metricType":"sum"},{"name":"number of sort fallback tasks","accumulatorId":268,"metricType":"sum"},{"name":"avg hash probes per key","accumulatorId":267,"metricType":"average"}]}],"metadata":{},"metrics":[{"name":"time to broadcast","accumulatorId":262,"metricType":"timing"},{"name":"time to build","accumulatorId":261,"metricType":"timing"},{"name":"time to collect","accumulatorId":260,"metricType":"timing"},{"name":"number of output rows","accumulatorId":259,"metricType":"sum"},{"name":"data size","accumulatorId":258,"metricType":"size"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":159,"metricType":"sum"}]}],"metadata":{},"metrics":[]}],"metadata":{},"metrics":[{"name":"spill size","accumulatorId":155,"metricType":"size"},{"name":"time in aggregation build","accumulatorId":156,"metricType":"timing"},{"name":"peak memory","accumulatorId":154,"metricType":"size"},{"name":"number of output rows","accumulatorId":153,"metricType":"sum"},{"name":"number of sort fallback tasks","accumulatorId":158,"metricType":"sum"},{"name":"avg hash probes per key","accumulatorId":157,"metricType":"average"}]}],"metadata":{},"metrics":[{"name":"spill size","accumulatorId":149,"metricType":"size"},{"name":"time in aggregation build","accumulatorId":150,"metricType":"timing"},{"name":"peak memory","accumulatorId":148,"metricType":"size"},{"name":"number of output rows","accumulatorId":147,"metricType":"sum"},{"name":"number of sort fallback tasks","accumulatorId":152,"metricType":"sum"},{"name":"avg hash probes per key","accumulatorId":151,"metricType":"average"}]}],"metadata":{},"metrics":[]}],"metadata":{},"metrics":[]}],"metadata":{},"metrics":[{"name":"task commit time","accumulatorId":145,"metricType":"timing"},{"name":"number of written files","accumulatorId":141,"metricType":"sum"},{"name":"job commit time","accumulatorId":146,"metricType":"timing"},{"name":"number of output rows","accumulatorId":143,"metricType":"sum"},{"name":"number of dynamic part","accumulatorId":144,"metricType":"sum"},{"name":"written output","accumulatorId":142,"metricType":"size"}]}],"metadata":{},"metrics":[]},"time":1783414880102,"modifiedConfigs":{},"jobTags":[]}
{"Event":"org.apache.spark.sql.execution.ui.SparkListenerSQLAdaptiveExecutionUpdate","executionId":0,"physicalPlanDescription":"== Physical Plan ==\nAdaptiveSparkPlan (67)\n+- == Current Plan ==\n   Execute InsertIntoHadoopFsRelationCommand (39)\n   +- WriteFiles (38)\n      +- Project (37)\n         +- HashAggregate (36)\n            +- HashAggregate (35)\n               +- Project (34)\n                  +- BroadcastHashJoin Inner BuildRight (33)\n                     :- Project (24)\n                     :  +- BroadcastHashJoin Inner BuildRight (23)\n                     :     :- Project (17)\n                     :     :  +- BroadcastHashJoin Inner BuildRight (16)\n                     :     :     :- HashAggregate (10)\n                     :     :     :  +- Exchange (9)\n                     :     :     :     +- HashAggregate (8)\n                     :     :     :        +- HashAggregate (7)\n                     :     :     :           +- ShuffleQueryStage (6)\n                     :     :     :              +- Exchange (5)\n                     :     :     :                 +- * HashAggregate (4)\n                     :     :     :                    +- * Filter (3)\n                     :     :     :                       +- * ColumnarToRow (2)\n                     :     :     :                          +- Scan parquet  (1)\n                     :     :     +- BroadcastQueryStage (15)\n                     :     :        +- BroadcastExchange (14)\n                     :     :           +- * Filter (13)\n                     :     :              +- * ColumnarToRow (12)\n                     :     :                 +- Scan parquet  (11)\n                     :     +- BroadcastQueryStage (22)\n                     :        +- BroadcastExchange (21)\n                     :           +- * Filter (20)\n                     :              +- * ColumnarToRow (19)\n                     :                 +- Scan parquet  (18)\n                     +- BroadcastExchange (32)\n                        +- HashAggregate (31)\n                           +- ShuffleQueryStage (30)\n                              +- Exchange (29)\n                                 +- * HashAggregate (28)\n                                    +- * Filter (27)\n                                       +- * ColumnarToRow (26)\n                                          +- Scan parquet  (25)\n+- == Initial Plan ==\n   Execute InsertIntoHadoopFsRelationCommand (66)\n   +- WriteFiles (65)\n      +- Project (64)\n         +- HashAggregate (63)\n            +- HashAggregate (62)\n               +- Project (61)\n                  +- BroadcastHashJoin Inner BuildRight (60)\n                     :- Project (54)\n                     :  +- BroadcastHashJoin Inner BuildRight (53)\n                     :     :- Project (50)\n                     :     :  +- BroadcastHashJoin Inner BuildRight (49)\n                     :     :     :- HashAggregate (46)\n                     :     :     :  +- Exchange (45)\n                     :     :     :     +- HashAggregate (44)\n                     :     :     :        +- HashAggregate (43)\n                     :     :     :           +- Exchange (42)\n                     :     :     :              +- HashAggregate (41)\n                     :     :     :                 +- Filter (40)\n                     :     :     :                    +- Scan parquet  (1)\n                     :     :     +- BroadcastExchange (48)\n                     :     :        +- Filter (47)\n                     :     :           +- Scan parquet  (11)\n                     :     +- BroadcastExchange (52)\n                     :        +- Filter (51)\n                     :           +- Scan parquet  (18)\n                     +- BroadcastExchange (59)\n                        +- HashAggregate (58)\n                           +- Exchange (57)\n                              +- HashAggregate (56)\n                                 +- Filter (55)\n                                    +- Scan parquet  (25)\n\n\n(1) Scan parquet \nOutput [3]: [user_id#0, lesson_id#1, course_id#2]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet]\nPushedFilters: [IsNotNull(user_id), IsNotNull(course_id)]\nReadSchema: struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(2) ColumnarToRow [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\n\n(3) Filter [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(4) HashAggregate [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(5) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=159]\n\n(6) ShuffleQueryStage\nOutput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: 0\n\n(7) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(8) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(9) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=172]\n\n(10) HashAggregate\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(11) Scan parquet \nOutput [2]: [user_id#8, name#9]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_user.parquet]\nPushedFilters: [IsNotNull(user_id)]\nReadSchema: struct<user_id:decimal(20,0),name:string>\n\n(12) ColumnarToRow [codegen id : 2]\nInput [2]: [user_id#8, name#9]\n\n(13) Filter [codegen id : 2]\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(14) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=185]\n\n(15) BroadcastQueryStage\nOutput [2]: [user_id#8, name#9]\nArguments: 1\n\n(16) BroadcastHashJoin\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(17) Project\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(18) Scan parquet \nOutput [2]: [course_id#18, title#19]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_course.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<course_id:decimal(20,0),title:string>\n\n(19) ColumnarToRow [codegen id : 3]\nInput [2]: [course_id#18, title#19]\n\n(20) Filter [codegen id : 3]\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(21) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=206]\n\n(22) BroadcastQueryStage\nOutput [2]: [course_id#18, title#19]\nArguments: 2\n\n(23) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(24) Project\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(25) Scan parquet \nOutput [2]: [lesson_id#26, course_id#27]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_lesson.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(26) ColumnarToRow [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\n\n(27) Filter [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(28) HashAggregate [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(29) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=235]\n\n(30) ShuffleQueryStage\nOutput [2]: [course_id#27, count#180L]\nArguments: 3\n\n(31) HashAggregate\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(32) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=247]\n\n(33) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(34) Project\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(35) HashAggregate\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(36) HashAggregate\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(37) Project\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(38) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(39) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(40) Filter\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(41) HashAggregate\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(42) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=112]\n\n(43) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(44) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(45) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=116]\n\n(46) HashAggregate\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(47) Filter\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(48) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=119]\n\n(49) BroadcastHashJoin\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(50) Project\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(51) Filter\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(52) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=123]\n\n(53) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(54) Project\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(55) Filter\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(56) HashAggregate\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(57) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=126]\n\n(58) HashAggregate\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(59) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=129]\n\n(60) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(61) Project\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(62) HashAggregate\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(63) HashAggregate\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(64) Project\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(65) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(66) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(67) AdaptiveSparkPlan\nOutput: []\nArguments: isFinalPlan=false\n\n","sparkPlanInfo":{"nodeName":"AdaptiveSparkPlan","simpleString":"AdaptiveSparkPlan isFinalPlan=false","children":[{"nodeName":"Execute InsertIntoHadoopFsRelationCommand","simpleString":"Execute InsertIntoHadoopFsRelationCommand s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]","children":[{"nodeName":"WriteFiles","simpleString":"WriteFiles","children":[{"nodeName":"Project","simpleString":"Project [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS 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{"Event":"SparkListenerStageSubmitted","Stage Info":{"Stage ID":6,"Stage Attempt ID":0,"Stage Name":"parquet at NativeMethodAccessorImpl.java:0","Number of Tasks":1,"RDD Info":[{"RDD ID":19,"Name":"MapPartitionsRDD","Scope":"{\"id\":\"24\",\"name\":\"Exchange\"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[18],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk Size":0},{"RDD ID":9,"Name":"FileScanRDD","Scope":"{\"id\":\"38\",\"name\":\"Scan parquet \"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk 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{"Event":"SparkListenerTaskStart","Stage ID":4,"Stage Attempt ID":0,"Task Info":{"Task ID":4,"Index":0,"Attempt":0,"Partition ID":0,"Launch Time":1783414880393,"Executor ID":"0","Host":"172.28.0.49","Locality":"PROCESS_LOCAL","Speculative":false,"Getting Result Time":0,"Finish Time":0,"Failed":false,"Killed":false,"Accumulables":[]}}
{"Event":"SparkListenerTaskStart","Stage ID":5,"Stage Attempt ID":0,"Task Info":{"Task ID":5,"Index":0,"Attempt":0,"Partition ID":0,"Launch Time":1783414880401,"Executor ID":"0","Host":"172.28.0.49","Locality":"PROCESS_LOCAL","Speculative":false,"Getting Result Time":0,"Finish Time":0,"Failed":false,"Killed":false,"Accumulables":[]}}
{"Event":"SparkListenerTaskStart","Stage ID":6,"Stage Attempt ID":0,"Task Info":{"Task ID":6,"Index":0,"Attempt":0,"Partition ID":0,"Launch Time":1783414880428,"Executor ID":"0","Host":"172.28.0.49","Locality":"PROCESS_LOCAL","Speculative":false,"Getting Result Time":0,"Finish Time":0,"Failed":false,"Killed":false,"Accumulables":[]}}
{"Event":"org.apache.spark.sql.execution.ui.SparkListenerDriverAccumUpdates","executionId":0,"accumUpdates":[[300,1],[301,0],[302,2040]]}
{"Event":"org.apache.spark.sql.execution.ui.SparkListenerDriverAccumUpdates","executionId":0,"accumUpdates":[[420,200]]}
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{"Event":"SparkListenerStageCompleted","Stage Info":{"Stage ID":6,"Stage Attempt ID":0,"Stage Name":"parquet at NativeMethodAccessorImpl.java:0","Number of Tasks":1,"RDD Info":[{"RDD ID":19,"Name":"MapPartitionsRDD","Scope":"{\"id\":\"24\",\"name\":\"Exchange\"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[18],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk Size":0},{"RDD ID":9,"Name":"FileScanRDD","Scope":"{\"id\":\"38\",\"name\":\"Scan parquet \"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk 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{"Event":"SparkListenerJobEnd","Job ID":6,"Completion Time":1783414881263,"Job Result":{"Result":"JobSucceeded"}}
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{"Event":"SparkListenerStageCompleted","Stage Info":{"Stage ID":7,"Stage Attempt ID":0,"Stage Name":"parquet at NativeMethodAccessorImpl.java:0","Number of Tasks":1,"RDD Info":[{"RDD ID":23,"Name":"MapPartitionsRDD","Scope":"{\"id\":\"39\",\"name\":\"Exchange\"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[22],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk Size":0},{"RDD ID":20,"Name":"FileScanRDD","Scope":"{\"id\":\"45\",\"name\":\"Scan parquet \"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk 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IDs":[],"Details":"org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:792)\njava.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\njava.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:77)\njava.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\njava.base/java.lang.reflect.Method.invoke(Method.java:569)\npy4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)\npy4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)\npy4j.Gateway.invoke(Gateway.java:282)\npy4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)\npy4j.commands.CallCommand.execute(CallCommand.java:79)\npy4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)\npy4j.ClientServerConnection.run(ClientServerConnection.java:106)\njava.base/java.lang.Thread.run(Thread.java:840)","Submission Time":1783414880477,"Completion Time":1783414881265,"Accumulables":[{"ID":298,"Name":"number of output rows","Value":"18","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":299,"Name":"scan time","Value":"222","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":419,"Name":"data size","Value":"200","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":438,"Name":"shuffle bytes written","Value":"370","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":439,"Name":"shuffle records written","Value":"5","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":440,"Name":"shuffle write time","Value":"19383819","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":441,"Name":"duration","Value":"407","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":442,"Name":"number of output rows","Value":"5","Internal":true,"Count Failed Values":true,"Metadata":"sql"},{"ID":443,"Name":"peak memory","Value":"262144","Internal":true,"Count 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{"Event":"SparkListenerJobEnd","Job ID":7,"Completion Time":1783414881266,"Job Result":{"Result":"JobSucceeded"}}
{"Event":"org.apache.spark.sql.execution.ui.SparkListenerSQLAdaptiveExecutionUpdate","executionId":0,"physicalPlanDescription":"== Physical Plan ==\nAdaptiveSparkPlan (71)\n+- == Current Plan ==\n   Execute InsertIntoHadoopFsRelationCommand (43)\n   +- WriteFiles (42)\n      +- Project (41)\n         +- HashAggregate (40)\n            +- HashAggregate (39)\n               +- Project (38)\n                  +- BroadcastHashJoin Inner BuildRight (37)\n                     :- Project (26)\n                     :  +- BroadcastHashJoin Inner BuildRight (25)\n                     :     :- Project (19)\n                     :     :  +- BroadcastHashJoin Inner BuildRight (18)\n                     :     :     :- HashAggregate (12)\n                     :     :     :  +- ShuffleQueryStage (11)\n                     :     :     :     +- Exchange (10)\n                     :     :     :        +- * HashAggregate (9)\n                     :     :     :           +- * HashAggregate (8)\n                     :     :     :              +- AQEShuffleRead (7)\n                     :     :     :                 +- ShuffleQueryStage (6), Statistics(sizeInBytes=4.3 KiB, rowCount=55)\n                     :     :     :                    +- Exchange (5)\n                     :     :     :                       +- * HashAggregate (4)\n                     :     :     :                          +- * Filter (3)\n                     :     :     :                             +- * ColumnarToRow (2)\n                     :     :     :                                +- Scan parquet  (1)\n                     :     :     +- BroadcastQueryStage (17), Statistics(sizeInBytes=2.0 MiB, rowCount=22)\n                     :     :        +- BroadcastExchange (16)\n                     :     :           +- * Filter (15)\n                     :     :              +- * ColumnarToRow (14)\n                     :     :                 +- Scan parquet  (13)\n                     :     +- BroadcastQueryStage (24), Statistics(sizeInBytes=2.0 MiB, rowCount=5)\n                     :        +- BroadcastExchange (23)\n                     :           +- * Filter (22)\n                     :              +- * ColumnarToRow (21)\n                     :                 +- Scan parquet  (20)\n                     +- BroadcastQueryStage (36)\n                        +- BroadcastExchange (35)\n                           +- * HashAggregate (34)\n                              +- AQEShuffleRead (33)\n                                 +- ShuffleQueryStage (32), Statistics(sizeInBytes=200.0 B, rowCount=5)\n                                    +- Exchange (31)\n                                       +- * HashAggregate (30)\n                                          +- * Filter (29)\n                                             +- * ColumnarToRow (28)\n                                                +- Scan parquet  (27)\n+- == Initial Plan ==\n   Execute InsertIntoHadoopFsRelationCommand (70)\n   +- WriteFiles (69)\n      +- Project (68)\n         +- HashAggregate (67)\n            +- HashAggregate (66)\n               +- Project (65)\n                  +- BroadcastHashJoin Inner BuildRight (64)\n                     :- Project (58)\n                     :  +- BroadcastHashJoin Inner BuildRight (57)\n                     :     :- Project (54)\n                     :     :  +- BroadcastHashJoin Inner BuildRight (53)\n                     :     :     :- HashAggregate (50)\n                     :     :     :  +- Exchange (49)\n                     :     :     :     +- HashAggregate (48)\n                     :     :     :        +- HashAggregate (47)\n                     :     :     :           +- Exchange (46)\n                     :     :     :              +- HashAggregate (45)\n                     :     :     :                 +- Filter (44)\n                     :     :     :                    +- Scan parquet  (1)\n                     :     :     +- BroadcastExchange (52)\n                     :     :        +- Filter (51)\n                     :     :           +- Scan parquet  (13)\n                     :     +- BroadcastExchange (56)\n                     :        +- Filter (55)\n                     :           +- Scan parquet  (20)\n                     +- BroadcastExchange (63)\n                        +- HashAggregate (62)\n                           +- Exchange (61)\n                              +- HashAggregate (60)\n                                 +- Filter (59)\n                                    +- Scan parquet  (27)\n\n\n(1) Scan parquet \nOutput [3]: [user_id#0, lesson_id#1, course_id#2]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet]\nPushedFilters: [IsNotNull(user_id), IsNotNull(course_id)]\nReadSchema: struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(2) ColumnarToRow [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\n\n(3) Filter [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(4) HashAggregate [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(5) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=159]\n\n(6) ShuffleQueryStage\nOutput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: 0\n\n(7) AQEShuffleRead\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: coalesced\n\n(8) HashAggregate [codegen id : 5]\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(9) HashAggregate [codegen id : 5]\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(10) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=366]\n\n(11) ShuffleQueryStage\nOutput [3]: [user_id#0, course_id#2, count#177L]\nArguments: 4\n\n(12) HashAggregate\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(13) Scan parquet \nOutput [2]: [user_id#8, name#9]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_user.parquet]\nPushedFilters: [IsNotNull(user_id)]\nReadSchema: struct<user_id:decimal(20,0),name:string>\n\n(14) ColumnarToRow [codegen id : 2]\nInput [2]: [user_id#8, name#9]\n\n(15) Filter [codegen id : 2]\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(16) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=185]\n\n(17) BroadcastQueryStage\nOutput [2]: [user_id#8, name#9]\nArguments: 1\n\n(18) BroadcastHashJoin\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(19) Project\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(20) Scan parquet \nOutput [2]: [course_id#18, title#19]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_course.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<course_id:decimal(20,0),title:string>\n\n(21) ColumnarToRow [codegen id : 3]\nInput [2]: [course_id#18, title#19]\n\n(22) Filter [codegen id : 3]\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(23) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=206]\n\n(24) BroadcastQueryStage\nOutput [2]: [course_id#18, title#19]\nArguments: 2\n\n(25) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(26) Project\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(27) Scan parquet \nOutput [2]: [lesson_id#26, course_id#27]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_lesson.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(28) ColumnarToRow [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\n\n(29) Filter [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(30) HashAggregate [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(31) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=235]\n\n(32) ShuffleQueryStage\nOutput [2]: [course_id#27, count#180L]\nArguments: 3\n\n(33) AQEShuffleRead\nInput [2]: [course_id#27, count#180L]\nArguments: coalesced\n\n(34) HashAggregate [codegen id : 6]\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(35) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=388]\n\n(36) BroadcastQueryStage\nOutput [2]: [course_id#27, lesson_in_course#39L]\nArguments: 5\n\n(37) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(38) Project\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(39) HashAggregate\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(40) HashAggregate\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(41) Project\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(42) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(43) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(44) Filter\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(45) HashAggregate\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(46) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=112]\n\n(47) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(48) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(49) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=116]\n\n(50) HashAggregate\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(51) Filter\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(52) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=119]\n\n(53) BroadcastHashJoin\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(54) Project\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(55) Filter\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(56) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=123]\n\n(57) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(58) Project\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(59) Filter\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(60) HashAggregate\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(61) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=126]\n\n(62) HashAggregate\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(63) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=129]\n\n(64) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(65) Project\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(66) HashAggregate\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(67) HashAggregate\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(68) Project\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(69) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(70) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(71) AdaptiveSparkPlan\nOutput: []\nArguments: isFinalPlan=false\n\n","sparkPlanInfo":{"nodeName":"AdaptiveSparkPlan","simpleString":"AdaptiveSparkPlan isFinalPlan=false","children":[{"nodeName":"Execute InsertIntoHadoopFsRelationCommand","simpleString":"Execute InsertIntoHadoopFsRelationCommand s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]","children":[{"nodeName":"WriteFiles","simpleString":"WriteFiles","children":[{"nodeName":"Project","simpleString":"Project [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L], functions=[max(lessons_viewed#49L)])","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L], functions=[partial_max(lessons_viewed#49L)])","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [course_id#2], [course_id#27], Inner, BuildRight, false","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [course_id#2], [course_id#18], Inner, BuildRight, false","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [user_id#0], [user_id#8], Inner, BuildRight, false","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2], functions=[count(distinct lesson_id#1)])","children":[{"nodeName":"ShuffleQueryStage","simpleString":"ShuffleQueryStage 4","children":[{"nodeName":"Exchange","simpleString":"Exchange hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=366]","children":[{"nodeName":"WholeStageCodegen (5)","simpleString":"WholeStageCodegen (5)","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2], functions=[partial_count(distinct lesson_id#1)])","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2, lesson_id#1], functions=[])","children":[{"nodeName":"InputAdapter","simpleString":"InputAdapter","children":[{"nodeName":"AQEShuffleRead","simpleString":"AQEShuffleRead coalesced","children":[{"nodeName":"ShuffleQueryStage","simpleString":"ShuffleQueryStage 0","children":[{"nodeName":"Exchange","simpleString":"Exchange hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=159]","children":[{"nodeName":"WholeStageCodegen (1)","simpleString":"WholeStageCodegen (1)","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2, lesson_id#1], functions=[])","children":[{"nodeName":"Filter","simpleString":"Filter (isnotnull(user_id#0) AND isnotnull(course_id#2))","children":[{"nodeName":"ColumnarToRow","simpleString":"ColumnarToRow","children":[{"nodeName":"InputAdapter","simpleString":"InputAdapter","children":[{"nodeName":"Scan parquet ","simpleString":"FileScan parquet [user_id#0,lesson_id#1,course_id#2] Batched: true, DataFilters: [isnotnull(user_id#0), isnotnull(course_id#2)], Format: Parquet, Location: InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet], PartitionFilters: [], PushedFilters: [IsNotNull(user_id), IsNotNull(course_id)], ReadSchema: struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>","children":[],"metadata":{"Location":"InMemoryFileIndex(1 paths)[s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet]","ReadSchema":"struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>","Format":"Parquet","Batched":"true","PartitionFilters":"[]","PushedFilters":"[IsNotNull(user_id), IsNotNull(course_id)]","DataFilters":"[isnotnull(user_id#0), isnotnull(course_id#2)]"},"metrics":[{"name":"number of files read","accumulatorId":233,"metricType":"sum"},{"name":"scan time","accumulatorId":232,"metricType":"timing"},{"name":"metadata time","accumulatorId":234,"metricType":"timing"},{"name":"size of files read","accumulatorId":235,"metricType":"size"},{"name":"number of output rows","accumulatorId":231,"metricType":"sum"}]}],"metadata":{},"metrics":[]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":388,"metricType":"sum"},{"name":"number of input batches","accumulatorId":389,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"number of output rows","accumulatorId":387,"metricType":"sum"}]}],"metadata":{},"metrics":[{"name":"spill size","accumulatorId":383,"metricType":"size"},{"name":"time in aggregation build","accumulatorId":384,"metricType":"timing"},{"name":"peak memory","accumulatorId":382,"metricType":"size"},{"name":"number of output rows","accumulatorId":381,"metricType":"sum"},{"name":"number of sort fallback tasks","accumulatorId":386,"metricType":"sum"},{"name":"avg hash probes per key","accumulatorId":385,"metricType":"average"}]}],"metadata":{},"metrics":[{"name":"duration","accumulatorId":380,"metricType":"timing"}]}],"metadata":{},"metrics":[{"name":"shuffle records written","accumulatorId":378,"metricType":"sum"},{"name":"local merged chunks fetched","accumulatorId":372,"metricType":"sum"},{"name":"shuffle write time","accumulatorId":379,"metricType":"nsTiming"},{"name":"remote merged bytes read","accumulatorId":373,"metricType":"size"},{"name":"local merged blocks fetched","accumulatorId":370,"metricType":"sum"},{"name":"corrupt merged block chunks","accumulatorId":367,"metricType":"sum"},{"name":"remote merged reqs duration","accumulatorId":376,"metricType":"timing"},{"name":"remote merged blocks fetched","accumulatorId":369,"metricType":"sum"},{"name":"records read","accumulatorId":366,"metricType":"sum"},{"name":"local bytes read","accumulatorId":364,"metricType":"size"},{"name":"fetch wait time","accumulatorId":365,"metricType":"timing"},{"name":"remote 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{"Event":"SparkListenerJobStart","Job ID":9,"Submission Time":1783414881373,"Stage Infos":[{"Stage ID":10,"Stage Attempt ID":0,"Stage Name":"parquet at NativeMethodAccessorImpl.java:0","Number of Tasks":1,"RDD Info":[{"RDD ID":19,"Name":"MapPartitionsRDD","Scope":"{\"id\":\"24\",\"name\":\"Exchange\"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[18],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached Partitions":0,"Memory Size":0,"Disk Size":0},{"RDD ID":9,"Name":"FileScanRDD","Scope":"{\"id\":\"38\",\"name\":\"Scan parquet \"}","Callsite":"parquet at NativeMethodAccessorImpl.java:0","Parent IDs":[],"Storage Level":{"Use Disk":false,"Use Memory":false,"Use Off Heap":false,"Deserialized":false,"Replication":1},"Barrier":false,"DeterministicLevel":"DETERMINATE","Number of Partitions":1,"Number of Cached 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     :     :     :           +- * HashAggregate (9)\n                     :     :     :              +- * HashAggregate (8)\n                     :     :     :                 +- AQEShuffleRead (7)\n                     :     :     :                    +- ShuffleQueryStage (6), Statistics(sizeInBytes=4.3 KiB, rowCount=55)\n                     :     :     :                       +- Exchange (5)\n                     :     :     :                          +- * HashAggregate (4)\n                     :     :     :                             +- * Filter (3)\n                     :     :     :                                +- * ColumnarToRow (2)\n                     :     :     :                                   +- Scan parquet  (1)\n                     :     :     +- BroadcastQueryStage (18), Statistics(sizeInBytes=2.0 MiB, rowCount=22)\n                     :     :        +- BroadcastExchange (17)\n                     :     :           +- * Filter (16)\n                     :     :              +- * ColumnarToRow (15)\n                     :     :                 +- Scan parquet  (14)\n                     :     +- BroadcastQueryStage (25), Statistics(sizeInBytes=2.0 MiB, rowCount=5)\n                     :        +- BroadcastExchange (24)\n                     :           +- * Filter (23)\n                     :              +- * ColumnarToRow (22)\n                     :                 +- Scan parquet  (21)\n                     +- BroadcastQueryStage (37), Statistics(sizeInBytes=2.0 MiB, rowCount=5)\n                        +- BroadcastExchange (36)\n                           +- * HashAggregate (35)\n                              +- AQEShuffleRead (34)\n                                 +- ShuffleQueryStage (33), Statistics(sizeInBytes=200.0 B, rowCount=5)\n                                    +- Exchange (32)\n                                       +- * HashAggregate (31)\n                                          +- * Filter (30)\n                                             +- * ColumnarToRow (29)\n                                                +- Scan parquet  (28)\n+- == Initial Plan ==\n   Execute InsertIntoHadoopFsRelationCommand (71)\n   +- WriteFiles (70)\n      +- Project (69)\n         +- HashAggregate (68)\n            +- HashAggregate (67)\n               +- Project (66)\n                  +- BroadcastHashJoin Inner BuildRight (65)\n                     :- Project (59)\n                     :  +- BroadcastHashJoin Inner BuildRight (58)\n                     :     :- Project (55)\n                     :     :  +- BroadcastHashJoin Inner BuildRight (54)\n                     :     :     :- HashAggregate (51)\n                     :     :     :  +- Exchange (50)\n                     :     :     :     +- HashAggregate (49)\n                     :     :     :        +- HashAggregate (48)\n                     :     :     :           +- Exchange (47)\n                     :     :     :              +- HashAggregate (46)\n                     :     :     :                 +- Filter (45)\n                     :     :     :                    +- Scan parquet  (1)\n                     :     :     +- BroadcastExchange (53)\n                     :     :        +- Filter (52)\n                     :     :           +- Scan parquet  (14)\n                     :     +- BroadcastExchange (57)\n                     :        +- Filter (56)\n                     :           +- Scan parquet  (21)\n                     +- BroadcastExchange (64)\n                        +- HashAggregate (63)\n                           +- Exchange (62)\n                              +- HashAggregate (61)\n                                 +- Filter (60)\n                                    +- Scan parquet  (28)\n\n\n(1) Scan parquet \nOutput [3]: [user_id#0, lesson_id#1, course_id#2]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_fact_lesson_views.parquet]\nPushedFilters: [IsNotNull(user_id), IsNotNull(course_id)]\nReadSchema: struct<user_id:decimal(20,0),lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(2) ColumnarToRow [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\n\n(3) Filter [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(4) HashAggregate [codegen id : 1]\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(5) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=159]\n\n(6) ShuffleQueryStage\nOutput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: 0\n\n(7) AQEShuffleRead\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: coalesced\n\n(8) HashAggregate [codegen id : 5]\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(9) HashAggregate [codegen id : 5]\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(10) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=366]\n\n(11) ShuffleQueryStage\nOutput [3]: [user_id#0, course_id#2, count#177L]\nArguments: 4\n\n(12) AQEShuffleRead\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: coalesced\n\n(13) HashAggregate [codegen id : 7]\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(14) Scan parquet \nOutput [2]: [user_id#8, name#9]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_user.parquet]\nPushedFilters: [IsNotNull(user_id)]\nReadSchema: struct<user_id:decimal(20,0),name:string>\n\n(15) ColumnarToRow [codegen id : 2]\nInput [2]: [user_id#8, name#9]\n\n(16) Filter [codegen id : 2]\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(17) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=185]\n\n(18) BroadcastQueryStage\nOutput [2]: [user_id#8, name#9]\nArguments: 1\n\n(19) BroadcastHashJoin [codegen id : 7]\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(20) Project [codegen id : 7]\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(21) Scan parquet \nOutput [2]: [course_id#18, title#19]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_course.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<course_id:decimal(20,0),title:string>\n\n(22) ColumnarToRow [codegen id : 3]\nInput [2]: [course_id#18, title#19]\n\n(23) Filter [codegen id : 3]\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(24) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=206]\n\n(25) BroadcastQueryStage\nOutput [2]: [course_id#18, title#19]\nArguments: 2\n\n(26) BroadcastHashJoin [codegen id : 7]\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(27) Project [codegen id : 7]\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(28) Scan parquet \nOutput [2]: [lesson_id#26, course_id#27]\nBatched: true\nLocation: InMemoryFileIndex [s3a://apavlovets-bucket/ch_core/core_dim_lesson.parquet]\nPushedFilters: [IsNotNull(course_id)]\nReadSchema: struct<lesson_id:decimal(20,0),course_id:decimal(20,0)>\n\n(29) ColumnarToRow [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\n\n(30) Filter [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(31) HashAggregate [codegen id : 4]\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(32) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=235]\n\n(33) ShuffleQueryStage\nOutput [2]: [course_id#27, count#180L]\nArguments: 3\n\n(34) AQEShuffleRead\nInput [2]: [course_id#27, count#180L]\nArguments: coalesced\n\n(35) HashAggregate [codegen id : 6]\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(36) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=388]\n\n(37) BroadcastQueryStage\nOutput [2]: [course_id#27, lesson_in_course#39L]\nArguments: 5\n\n(38) BroadcastHashJoin [codegen id : 7]\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(39) Project [codegen id : 7]\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(40) HashAggregate [codegen id : 7]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(41) HashAggregate [codegen id : 7]\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(42) Project [codegen id : 7]\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(43) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(44) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(45) Filter\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nCondition : (isnotnull(user_id#0) AND isnotnull(course_id#2))\n\n(46) HashAggregate\nInput [3]: [user_id#0, lesson_id#1, course_id#2]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(47) Exchange\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nArguments: hashpartitioning(user_id#0, course_id#2, lesson_id#1, 200), ENSURE_REQUIREMENTS, [plan_id=112]\n\n(48) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [3]: [user_id#0, course_id#2, lesson_id#1]\nFunctions: []\nAggregate Attributes: []\nResults [3]: [user_id#0, course_id#2, lesson_id#1]\n\n(49) HashAggregate\nInput [3]: [user_id#0, course_id#2, lesson_id#1]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [partial_count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [user_id#0, course_id#2, count#177L]\n\n(50) Exchange\nInput [3]: [user_id#0, course_id#2, count#177L]\nArguments: hashpartitioning(user_id#0, course_id#2, 200), ENSURE_REQUIREMENTS, [plan_id=116]\n\n(51) HashAggregate\nInput [3]: [user_id#0, course_id#2, count#177L]\nKeys [2]: [user_id#0, course_id#2]\nFunctions [1]: [count(distinct lesson_id#1)]\nAggregate Attributes [1]: [count(lesson_id#1)#50L]\nResults [3]: [course_id#2, user_id#0, count(lesson_id#1)#50L AS lessons_viewed#49L]\n\n(52) Filter\nInput [2]: [user_id#8, name#9]\nCondition : isnotnull(user_id#8)\n\n(53) BroadcastExchange\nInput [2]: [user_id#8, name#9]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=119]\n\n(54) BroadcastHashJoin\nLeft keys [1]: [user_id#0]\nRight keys [1]: [user_id#8]\nJoin type: Inner\nJoin condition: None\n\n(55) Project\nOutput [4]: [course_id#2, user_id#0, lessons_viewed#49L, name#9]\nInput [5]: [course_id#2, user_id#0, lessons_viewed#49L, user_id#8, name#9]\n\n(56) Filter\nInput [2]: [course_id#18, title#19]\nCondition : isnotnull(course_id#18)\n\n(57) BroadcastExchange\nInput [2]: [course_id#18, title#19]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), false]),false), [plan_id=123]\n\n(58) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#18]\nJoin type: Inner\nJoin condition: None\n\n(59) Project\nOutput [5]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, course_id#18, title#19]\n\n(60) Filter\nInput [2]: [lesson_id#26, course_id#27]\nCondition : isnotnull(course_id#27)\n\n(61) HashAggregate\nInput [2]: [lesson_id#26, course_id#27]\nKeys [1]: [course_id#27]\nFunctions [1]: [partial_count(lesson_id#26)]\nAggregate Attributes [1]: [count#179L]\nResults [2]: [course_id#27, count#180L]\n\n(62) Exchange\nInput [2]: [course_id#27, count#180L]\nArguments: hashpartitioning(course_id#27, 200), ENSURE_REQUIREMENTS, [plan_id=126]\n\n(63) HashAggregate\nInput [2]: [course_id#27, count#180L]\nKeys [1]: [course_id#27]\nFunctions [1]: [count(lesson_id#26)]\nAggregate Attributes [1]: [count(lesson_id#26)#38L]\nResults [2]: [course_id#27, count(lesson_id#26)#38L AS lesson_in_course#39L]\n\n(64) BroadcastExchange\nInput [2]: [course_id#27, lesson_in_course#39L]\nArguments: HashedRelationBroadcastMode(List(input[0, decimal(20,0), true]),false), [plan_id=129]\n\n(65) BroadcastHashJoin\nLeft keys [1]: [course_id#2]\nRight keys [1]: [course_id#27]\nJoin type: Inner\nJoin condition: None\n\n(66) Project\nOutput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nInput [7]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, course_id#27, lesson_in_course#39L]\n\n(67) HashAggregate\nInput [6]: [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [partial_max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max#173L]\nResults [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\n\n(68) HashAggregate\nInput [6]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L, max#174L]\nKeys [5]: [user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L]\nFunctions [1]: [max(lessons_viewed#49L)]\nAggregate Attributes [1]: [max(lessons_viewed#49L)#142L]\nResults [6]: [user_id#0, name#9 AS user_name#150, course_id#2, title#19 AS course_title#151, lesson_in_course#39L, max(lessons_viewed#49L)#142L AS lessons_viewed#143L]\n\n(69) Project\nOutput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]\nInput [6]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L]\n\n(70) WriteFiles\nInput [7]: [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, completion_rate#158]\n\n(71) Execute InsertIntoHadoopFsRelationCommand\nInput: []\nArguments: s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]\n\n(72) AdaptiveSparkPlan\nOutput: []\nArguments: isFinalPlan=true\n\n","sparkPlanInfo":{"nodeName":"AdaptiveSparkPlan","simpleString":"AdaptiveSparkPlan isFinalPlan=true","children":[{"nodeName":"Execute InsertIntoHadoopFsRelationCommand","simpleString":"Execute InsertIntoHadoopFsRelationCommand s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet, false, Parquet, [path=s3a://apavlovets-bucket/marts_ch/course_completion_rate.parquet], Overwrite, [user_id, user_name, course_id, course_title, lesson_in_course, lessons_viewed, completion_rate]","children":[{"nodeName":"WriteFiles","simpleString":"WriteFiles","children":[{"nodeName":"WholeStageCodegen (7)","simpleString":"WholeStageCodegen (7)","children":[{"nodeName":"Project","simpleString":"Project [user_id#0, user_name#150, course_id#2, course_title#151, lesson_in_course#39L, lessons_viewed#143L, CASE WHEN NOT (lesson_in_course#39L = 0) THEN cast(round(((cast(lessons_viewed#143L as double) * 1.0) / cast(lesson_in_course#39L as double)), 2) as decimal(3,2)) ELSE 0.00 END AS completion_rate#158]","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L], functions=[max(lessons_viewed#49L)])","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, name#9, course_id#2, title#19, lesson_in_course#39L], functions=[partial_max(lessons_viewed#49L)])","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19, lesson_in_course#39L]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [course_id#2], [course_id#27], Inner, BuildRight, false","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9, title#19]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [course_id#2], [course_id#18], Inner, BuildRight, false","children":[{"nodeName":"Project","simpleString":"Project [course_id#2, user_id#0, lessons_viewed#49L, name#9]","children":[{"nodeName":"BroadcastHashJoin","simpleString":"BroadcastHashJoin [user_id#0], [user_id#8], Inner, BuildRight, false","children":[{"nodeName":"HashAggregate","simpleString":"HashAggregate(keys=[user_id#0, course_id#2], functions=[count(distinct lesson_id#1)])","children":[{"nodeName":"InputAdapter","simpleString":"InputAdapter","children":[{"nodeName":"AQEShuffleRead","simpleString":"AQEShuffleRead 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{"Event":"SparkListenerJobEnd","Job ID":10,"Completion Time":1783414882415,"Job Result":{"Result":"JobSucceeded"}}
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{"Event":"org.apache.spark.sql.execution.ui.SparkListenerSQLExecutionEnd","executionId":0,"time":1783414882592,"errorMessage":""}
{"Event":"SparkListenerApplicationEnd","Timestamp":1783414882594}