NYC Yellow Taxi Data Analysis - Details for Query 8

Details for Query 8

Submitted Time: 2024/12/17 12:34:39
Duration: 49 s
Succeeded Jobs: 18 19

Show the Stage ID and Task ID that corresponds to the max metric

digraph G { 0 [labelType="html" label=" TakeOrderedAndProject "]; subgraph cluster1 { isCluster="true"; label="WholeStageCodegen (4)\n \nduration: total (min, med, max (stageId: taskId))\n593 ms (0 ms, 2 ms, 10 ms (stage 29.0: task 558))"; 2 [labelType="html" label="HashAggregate time in aggregation build total (min, med, max (stageId: taskId)) 58 ms (0 ms, 0 ms, 3 ms (stage 29.0: task 558)) peak memory total (min, med, max (stageId: taskId)) 10.5 GiB (256.0 KiB, 64.3 MiB, 64.3 MiB (stage 29.0: task 520)) number of output rows: 348 avg hash probe bucket list iters (min, med, max (stageId: taskId)): (1, 1, 1 (stage 29.0: task 520))"]; } 3 [labelType="html" label="Exchange shuffle records written: 1,048 shuffle write time total (min, med, max (stageId: taskId)) 125 ms (5 ms, 6 ms, 7 ms (stage 28.0: task 512)) records read: 1,048 local bytes read total (min, med, max (stageId: taskId)) 48.4 KiB (0.0 B, 204.0 B, 791.0 B (stage 29.0: task 584)) fetch wait time total (min, med, max (stageId: taskId)) 3 ms (0 ms, 0 ms, 1 ms (stage 29.0: task 558)) remote bytes read total (min, med, max (stageId: taskId)) 46.4 KiB (0.0 B, 203.0 B, 736.0 B (stage 29.0: task 669)) local blocks read: 481 remote blocks read: 456 data size total (min, med, max (stageId: taskId)) 63.9 KiB (2.7 KiB, 3.1 KiB, 5.6 KiB (stage 28.0: task 517)) shuffle bytes written total (min, med, max (stageId: taskId)) 94.8 KiB (3.9 KiB, 4.6 KiB, 8.1 KiB (stage 28.0: task 517))"]; subgraph cluster4 { isCluster="true"; label="WholeStageCodegen (3)\n \nduration: total (min, med, max (stageId: taskId))\n1.6 m (1.5 s, 5.1 s, 5.8 s (stage 28.0: task 507))"; 5 [labelType="html" label="HashAggregate time in aggregation build total (min, med, max (stageId: taskId)) 1.5 m (1.5 s, 5.1 s, 5.8 s (stage 28.0: task 507)) peak memory total (min, med, max (stageId: taskId)) 5.0 MiB (256.0 KiB, 256.0 KiB, 256.0 KiB (stage 28.0: task 500)) number of output rows: 1,048"]; 6 [labelType="html" label=" Project "]; 7 [labelType="html" label="BroadcastHashJoin number of output rows: 22,400,728"]; 8 [labelType="html" label=" Project "]; 9 [labelType="html" label="BroadcastHashJoin number of output rows: 22,400,728"]; } 10 [labelType="html" label="Scan csv number of files read: 7 metadata time: 0 ms size of files read: 2.2 GiB number of output rows: 22,400,728"]; 11 [labelType="html" label="BroadcastExchange data size: 1026.1 KiB time to collect: 121 ms time to build: 9 ms time to broadcast: 4 ms"]; subgraph cluster12 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: 50 ms"; 13 [labelType="html" label=" Project "]; 14 [labelType="html" label="Filter number of output rows: 265"]; } 15 [labelType="html" label="Scan csv number of files read: 1 metadata time: 0 ms size of files read: 10.5 KiB number of output rows: 265"]; 2->0; 3->2; 5->3; 6->5; 7->6; 8->7; 9->8; 10->9; 11->9; 13->11; 14->13; 15->14; 11->7; }

TakeOrderedAndProject(limit=11, orderBy=[average_tip_per_passenger#668 DESC NULLS LAST], output=[Month#739,route#477,total_tip_amount#741,total_passenger_count#742,average_tip_per_passenger#743])

HashAggregate(keys=[Month#500, route#477], functions=[sum(cast(tip_amount#71 as double)), sum(cast(passenger_count#63 as double))])

WholeStageCodegen (4)

Exchange hashpartitioning(Month#500, route#477, 200), true, [id=#522]

HashAggregate(keys=[Month#500, route#477], functions=[partial_sum(cast(tip_amount#71 as double)), partial_sum(cast(passenger_count#63 as double))])

Project [passenger_count#63, tip_amount#71, concat_ws( to , Pickup_Borough#230, Borough#17) AS route#477, month(cast(tpep_pickup_datetime#61 as date)) AS Month#500]

BroadcastHashJoin [cast(DOLocationID#66 as int)], [LocationID#16], LeftOuter, BuildRight

Project [tpep_pickup_datetime#61, passenger_count#63, DOLocationID#66, tip_amount#71, Borough#17 AS Pickup_Borough#230]

BroadcastHashJoin [cast(PULocationID#65 as int)], [LocationID#16], LeftOuter, BuildRight

WholeStageCodegen (3)

FileScan csv [tpep_pickup_datetime#61,passenger_count#63,PULocationID#65,DOLocationID#66,tip_amount#71] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex[s3a://data-repository-bkt/ECS765/nyc_taxi/yellow_tripdata/2023/yellow_tripdata_..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<tpep_pickup_datetime:string,passenger_count:string,PULocationID:string,DOLocationID:string...

BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint))), [id=#481]

Project [LocationID#16, Borough#17]

Filter isnotnull(LocationID#16)

WholeStageCodegen (1)

FileScan csv [LocationID#16,Borough#17] Batched: false, DataFilters: [isnotnull(LocationID#16)], Format: CSV, Location: InMemoryFileIndex[s3a://data-repository-bkt/ECS765/nyc_taxi/taxi_zone_lookup.csv], PartitionFilters: [], PushedFilters: [IsNotNull(LocationID)], ReadSchema: struct<LocationID:int,Borough:string>

Details

== Parsed Logical Plan ==
GlobalLimit 11
+- LocalLimit 11
   +- Project [cast(Month#500 as string) AS Month#739, cast(route#477 as string) AS route#740, cast(total_tip_amount#661 as string) AS total_tip_amount#741, cast(total_passenger_count#663 as string) AS total_passenger_count#742, cast(average_tip_per_passenger#668 as string) AS average_tip_per_passenger#743]
      +- Sort [average_tip_per_passenger#668 DESC NULLS LAST], true
         +- Project [Month#500, route#477, total_tip_amount#661, total_passenger_count#663, round((total_tip_amount#661 / total_passenger_count#663), 2) AS average_tip_per_passenger#668]
            +- Aggregate [Month#500, route#477], [Month#500, route#477, round(sum(cast(tip_amount#71 as double)), 2) AS total_tip_amount#661, sum(cast(passenger_count#63 as double)) AS total_passenger_count#663]
               +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, Dropoff_Borough#384, Dropoff_Zone#408, Dropoff_service_zone#432, route#477, month(cast(tpep_pickup_datetime#61 as date)) AS Month#500]
                  +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, Dropoff_Borough#384, Dropoff_Zone#408, Dropoff_service_zone#432, concat_ws( to , Pickup_Borough#230, Dropoff_Borough#384) AS route#477]
                     +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, Dropoff_Borough#384, Dropoff_Zone#408, Dropoff_service_zone#432]
                        +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, LocationID#16, Dropoff_Borough#384, Dropoff_Zone#408, service_zone#19 AS Dropoff_service_zone#432]
                           +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, LocationID#16, Dropoff_Borough#384, Zone#18 AS Dropoff_Zone#408, service_zone#19]
                              +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, LocationID#16, Borough#17 AS Dropoff_Borough#384, Zone#18, service_zone#19]
                                 +- Join LeftOuter, (cast(DOLocationID#66 as int) = LocationID#16)
                                    :- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274]
                                    :  +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, LocationID#16, Pickup_Borough#230, Pickup_Zone#252, service_zone#19 AS Pickup_service_zone#274]
                                    :     +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, LocationID#16, Pickup_Borough#230, Zone#18 AS Pickup_Zone#252, service_zone#19]
                                    :        +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, LocationID#16, Borough#17 AS Pickup_Borough#230, Zone#18, service_zone#19]
                                    :           +- Join LeftOuter, (cast(PULocationID#65 as int) = LocationID#16)
                                    :              :- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, date_format(cast(tpep_pickup_datetime#61 as timestamp), yyyy-MM-dd, Some(GMT)) AS trip_date#114]
                                    :              :  +- Relation[tpep_pickup_datetime#61,tpep_dropoff_datetime#62,passenger_count#63,trip_distance#64,PULocationID#65,DOLocationID#66,payment_type#67,fare_amount#68,extra#69,mta_tax#70,tip_amount#71,tolls_amount#72,total_amount#73,congestion_surcharge#74,airport_fee#75,taxi_type#76] csv
                                    :              +- Relation[LocationID#16,Borough#17,Zone#18,service_zone#19] csv
                                    +- Relation[LocationID#16,Borough#17,Zone#18,service_zone#19] csv

== Analyzed Logical Plan ==
Month: string, route: string, total_tip_amount: string, total_passenger_count: string, average_tip_per_passenger: string
GlobalLimit 11
+- LocalLimit 11
   +- Project [cast(Month#500 as string) AS Month#739, cast(route#477 as string) AS route#740, cast(total_tip_amount#661 as string) AS total_tip_amount#741, cast(total_passenger_count#663 as string) AS total_passenger_count#742, cast(average_tip_per_passenger#668 as string) AS average_tip_per_passenger#743]
      +- Sort [average_tip_per_passenger#668 DESC NULLS LAST], true
         +- Project [Month#500, route#477, total_tip_amount#661, total_passenger_count#663, round((total_tip_amount#661 / total_passenger_count#663), 2) AS average_tip_per_passenger#668]
            +- Aggregate [Month#500, route#477], [Month#500, route#477, round(sum(cast(tip_amount#71 as double)), 2) AS total_tip_amount#661, sum(cast(passenger_count#63 as double)) AS total_passenger_count#663]
               +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, Dropoff_Borough#384, Dropoff_Zone#408, Dropoff_service_zone#432, route#477, month(cast(tpep_pickup_datetime#61 as date)) AS Month#500]
                  +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, Dropoff_Borough#384, Dropoff_Zone#408, Dropoff_service_zone#432, concat_ws( to , Pickup_Borough#230, Dropoff_Borough#384) AS route#477]
                     +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, Dropoff_Borough#384, Dropoff_Zone#408, Dropoff_service_zone#432]
                        +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, LocationID#16, Dropoff_Borough#384, Dropoff_Zone#408, service_zone#19 AS Dropoff_service_zone#432]
                           +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, LocationID#16, Dropoff_Borough#384, Zone#18 AS Dropoff_Zone#408, service_zone#19]
                              +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274, LocationID#16, Borough#17 AS Dropoff_Borough#384, Zone#18, service_zone#19]
                                 +- Join LeftOuter, (cast(DOLocationID#66 as int) = LocationID#16)
                                    :- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, Pickup_Borough#230, Pickup_Zone#252, Pickup_service_zone#274]
                                    :  +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, LocationID#16, Pickup_Borough#230, Pickup_Zone#252, service_zone#19 AS Pickup_service_zone#274]
                                    :     +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, LocationID#16, Pickup_Borough#230, Zone#18 AS Pickup_Zone#252, service_zone#19]
                                    :        +- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, trip_date#114, LocationID#16, Borough#17 AS Pickup_Borough#230, Zone#18, service_zone#19]
                                    :           +- Join LeftOuter, (cast(PULocationID#65 as int) = LocationID#16)
                                    :              :- Project [tpep_pickup_datetime#61, tpep_dropoff_datetime#62, passenger_count#63, trip_distance#64, PULocationID#65, DOLocationID#66, payment_type#67, fare_amount#68, extra#69, mta_tax#70, tip_amount#71, tolls_amount#72, total_amount#73, congestion_surcharge#74, airport_fee#75, taxi_type#76, date_format(cast(tpep_pickup_datetime#61 as timestamp), yyyy-MM-dd, Some(GMT)) AS trip_date#114]
                                    :              :  +- Relation[tpep_pickup_datetime#61,tpep_dropoff_datetime#62,passenger_count#63,trip_distance#64,PULocationID#65,DOLocationID#66,payment_type#67,fare_amount#68,extra#69,mta_tax#70,tip_amount#71,tolls_amount#72,total_amount#73,congestion_surcharge#74,airport_fee#75,taxi_type#76] csv
                                    :              +- Relation[LocationID#16,Borough#17,Zone#18,service_zone#19] csv
                                    +- Relation[LocationID#16,Borough#17,Zone#18,service_zone#19] csv

== Optimized Logical Plan ==
GlobalLimit 11
+- LocalLimit 11
   +- Project [cast(Month#500 as string) AS Month#739, route#477, cast(total_tip_amount#661 as string) AS total_tip_amount#741, cast(total_passenger_count#663 as string) AS total_passenger_count#742, cast(average_tip_per_passenger#668 as string) AS average_tip_per_passenger#743]
      +- Sort [average_tip_per_passenger#668 DESC NULLS LAST], true
         +- Aggregate [Month#500, route#477], [Month#500, route#477, round(sum(cast(tip_amount#71 as double)), 2) AS total_tip_amount#661, sum(cast(passenger_count#63 as double)) AS total_passenger_count#663, round((round(sum(cast(tip_amount#71 as double)), 2) / sum(cast(passenger_count#63 as double))), 2) AS average_tip_per_passenger#668]
            +- Project [passenger_count#63, tip_amount#71, concat_ws( to , Pickup_Borough#230, Borough#17) AS route#477, month(cast(tpep_pickup_datetime#61 as date)) AS Month#500]
               +- Join LeftOuter, (cast(DOLocationID#66 as int) = LocationID#16)
                  :- Project [tpep_pickup_datetime#61, passenger_count#63, DOLocationID#66, tip_amount#71, Borough#17 AS Pickup_Borough#230]
                  :  +- Join LeftOuter, (cast(PULocationID#65 as int) = LocationID#16)
                  :     :- Project [tpep_pickup_datetime#61, passenger_count#63, PULocationID#65, DOLocationID#66, tip_amount#71]
                  :     :  +- Relation[tpep_pickup_datetime#61,tpep_dropoff_datetime#62,passenger_count#63,trip_distance#64,PULocationID#65,DOLocationID#66,payment_type#67,fare_amount#68,extra#69,mta_tax#70,tip_amount#71,tolls_amount#72,total_amount#73,congestion_surcharge#74,airport_fee#75,taxi_type#76] csv
                  :     +- Project [LocationID#16, Borough#17]
                  :        +- Filter isnotnull(LocationID#16)
                  :           +- Relation[LocationID#16,Borough#17,Zone#18,service_zone#19] csv
                  +- Project [LocationID#16, Borough#17]
                     +- Filter isnotnull(LocationID#16)
                        +- Relation[LocationID#16,Borough#17,Zone#18,service_zone#19] csv

== Physical Plan ==
TakeOrderedAndProject(limit=11, orderBy=[average_tip_per_passenger#668 DESC NULLS LAST], output=[Month#739,route#477,total_tip_amount#741,total_passenger_count#742,average_tip_per_passenger#743])
+- *(4) HashAggregate(keys=[Month#500, route#477], functions=[sum(cast(tip_amount#71 as double)), sum(cast(passenger_count#63 as double))], output=[Month#500, route#477, total_tip_amount#661, total_passenger_count#663, average_tip_per_passenger#668])
   +- Exchange hashpartitioning(Month#500, route#477, 200), true, [id=#522]
      +- *(3) HashAggregate(keys=[Month#500, route#477], functions=[partial_sum(cast(tip_amount#71 as double)), partial_sum(cast(passenger_count#63 as double))], output=[Month#500, route#477, sum#691, sum#692])
         +- *(3) Project [passenger_count#63, tip_amount#71, concat_ws( to , Pickup_Borough#230, Borough#17) AS route#477, month(cast(tpep_pickup_datetime#61 as date)) AS Month#500]
            +- *(3) BroadcastHashJoin [cast(DOLocationID#66 as int)], [LocationID#16], LeftOuter, BuildRight
               :- *(3) Project [tpep_pickup_datetime#61, passenger_count#63, DOLocationID#66, tip_amount#71, Borough#17 AS Pickup_Borough#230]
               :  +- *(3) BroadcastHashJoin [cast(PULocationID#65 as int)], [LocationID#16], LeftOuter, BuildRight
               :     :- FileScan csv [tpep_pickup_datetime#61,passenger_count#63,PULocationID#65,DOLocationID#66,tip_amount#71] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex[s3a://data-repository-bkt/ECS765/nyc_taxi/yellow_tripdata/2023/yellow_tripdata_..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<tpep_pickup_datetime:string,passenger_count:string,PULocationID:string,DOLocationID:string...
               :     +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint))), [id=#481]
               :        +- *(1) Project [LocationID#16, Borough#17]
               :           +- *(1) Filter isnotnull(LocationID#16)
               :              +- FileScan csv [LocationID#16,Borough#17] Batched: false, DataFilters: [isnotnull(LocationID#16)], Format: CSV, Location: InMemoryFileIndex[s3a://data-repository-bkt/ECS765/nyc_taxi/taxi_zone_lookup.csv], PartitionFilters: [], PushedFilters: [IsNotNull(LocationID)], ReadSchema: struct<LocationID:int,Borough:string>
               +- ReusedExchange [LocationID#16, Borough#17], BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, true] as bigint))), [id=#481]