EVAL1_SPC1 - Details for Query 99

Submitted Time: 2026/02/19 14:00:36
Duration: 0.2 s
Succeeded Jobs: 106

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

digraph G { 0 [labelType="html" label=" CollectLimit "]; subgraph cluster1 { isCluster="true"; label="WholeStageCodegen (1)\n \nduration: 50 ms"; 2 [labelType="html" label=" Project "]; 3 [labelType="html" label="ColumnarToRow number of output rows: 717 number of input batches: 1"]; } 4 [labelType="html" label="Scan parquet number of files read: 1 scan time: 8 ms metadata time: 0 ms size of files read: 26.2 KiB number of output rows: 717"]; 2->0; 3->2; 4->3; }

CollectLimit 1500

Project [VISIT_ID_3343#9335 AS COL_EEA9697B_DB68_4A22_8733_70F35E85FA8C#9429, PATIENT_ID_3344#9333 AS COL_8859F9BF_E9D0_49C6_AD56_9C140D4C38A1#9430, IN_DATE_3345#9327 AS COL_AA4B3BC4_44A1_47D3_AC4B_C41D5CB3B3E9#9431, OUT_DATE_3346#9330 AS COL_F89F7AFE_9225_468C_A09B_7E0D4F0CD71B#9432, IN_MODE_3347#9328 AS COL_058F9F93_2D83_40ED_B3F6_4CAE6CD3C909#9433, OUT_MODE_3348#9331 AS COL_6514FE18_2F15_46F7_BE9B_8C8A1CDED5B0#9434, IN_UNIT_3349#9329 AS COL_0C85CE96_902F_49B0_8699_B1D8041E9741#9435, OUT_UNIT_3350#9332 AS COL_93D07A84_DAB1_4601_8776_58638D68C63B#9436, VISIT_TYPE_3351#9336 AS COL_69F7D2CB_3582_450F_B81C_F35E14BD2F3A#9437, CHAMP_PMSI_3352#9325 AS COL_8DD6299D_F88E_4923_BA4A_AA5963BBA243#9438, UNIT_PATH_3353#9334 AS COL_8F292832_9A81_4CB6_A3E8_AAF5E0E2B9D1#9439, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, EMERGENCY_3354#9326, 1, true, false, true) AS COL_119B8687_79BA_47AC_A253_99B3F514F94F#9440, CANCELED_3355#9324 AS COL_7A51C905_886C_4162_94AE_BCBA7820952A#9441, str_join(array(IN_UNIT_3349#9329, OUT_UNIT_3350#9332), >) AS COL_163AB4E6_D7B0_4397_BF6B_992AF7938586#9483]

ColumnarToRow

WholeStageCodegen (1)

FileScan parquet [CANCELED_3355#9324,CHAMP_PMSI_3352#9325,EMERGENCY_3354#9326,IN_DATE_3345#9327,IN_MODE_3347#9328,IN_UNIT_3349#9329,OUT_DATE_3346#9330,OUT_MODE_3348#9331,OUT_UNIT_3350#9332,PATIENT_ID_3344#9333,UNIT_PATH_3353#9334,VISIT_ID_3343#9335,VISIT_TYPE_3351#9336] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/data/output/cache/parquet/uet/VISIT_3342], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<CANCELED_3355:int,CHAMP_PMSI_3352:string,EMERGENCY_3354:string,IN_DATE_3345:timestamp,IN_M...

Details

== Physical Plan ==
CollectLimit (4)
+- * Project (3)
   +- * ColumnarToRow (2)
      +- Scan parquet  (1)


(1) Scan parquet 
Output [13]: [CANCELED_3355#9324, CHAMP_PMSI_3352#9325, EMERGENCY_3354#9326, IN_DATE_3345#9327, IN_MODE_3347#9328, IN_UNIT_3349#9329, OUT_DATE_3346#9330, OUT_MODE_3348#9331, OUT_UNIT_3350#9332, PATIENT_ID_3344#9333, UNIT_PATH_3353#9334, VISIT_ID_3343#9335, VISIT_TYPE_3351#9336]
Batched: true
Location: InMemoryFileIndex [file:/data/output/cache/parquet/uet/VISIT_3342]
ReadSchema: struct<CANCELED_3355:int,CHAMP_PMSI_3352:string,EMERGENCY_3354:string,IN_DATE_3345:timestamp,IN_MODE_3347:string,IN_UNIT_3349:string,OUT_DATE_3346:timestamp,OUT_MODE_3348:string,OUT_UNIT_3350:string,PATIENT_ID_3344:string,UNIT_PATH_3353:string,VISIT_ID_3343:string,VISIT_TYPE_3351:string>

(2) ColumnarToRow [codegen id : 1]
Input [13]: [CANCELED_3355#9324, CHAMP_PMSI_3352#9325, EMERGENCY_3354#9326, IN_DATE_3345#9327, IN_MODE_3347#9328, IN_UNIT_3349#9329, OUT_DATE_3346#9330, OUT_MODE_3348#9331, OUT_UNIT_3350#9332, PATIENT_ID_3344#9333, UNIT_PATH_3353#9334, VISIT_ID_3343#9335, VISIT_TYPE_3351#9336]

(3) Project [codegen id : 1]
Output [14]: [VISIT_ID_3343#9335 AS COL_EEA9697B_DB68_4A22_8733_70F35E85FA8C#9429, PATIENT_ID_3344#9333 AS COL_8859F9BF_E9D0_49C6_AD56_9C140D4C38A1#9430, IN_DATE_3345#9327 AS COL_AA4B3BC4_44A1_47D3_AC4B_C41D5CB3B3E9#9431, OUT_DATE_3346#9330 AS COL_F89F7AFE_9225_468C_A09B_7E0D4F0CD71B#9432, IN_MODE_3347#9328 AS COL_058F9F93_2D83_40ED_B3F6_4CAE6CD3C909#9433, OUT_MODE_3348#9331 AS COL_6514FE18_2F15_46F7_BE9B_8C8A1CDED5B0#9434, IN_UNIT_3349#9329 AS COL_0C85CE96_902F_49B0_8699_B1D8041E9741#9435, OUT_UNIT_3350#9332 AS COL_93D07A84_DAB1_4601_8776_58638D68C63B#9436, VISIT_TYPE_3351#9336 AS COL_69F7D2CB_3582_450F_B81C_F35E14BD2F3A#9437, CHAMP_PMSI_3352#9325 AS COL_8DD6299D_F88E_4923_BA4A_AA5963BBA243#9438, UNIT_PATH_3353#9334 AS COL_8F292832_9A81_4CB6_A3E8_AAF5E0E2B9D1#9439, staticinvoke(class org.apache.spark.sql.catalyst.util.CharVarcharCodegenUtils, StringType, readSidePadding, EMERGENCY_3354#9326, 1, true, false, true) AS COL_119B8687_79BA_47AC_A253_99B3F514F94F#9440, CANCELED_3355#9324 AS COL_7A51C905_886C_4162_94AE_BCBA7820952A#9441, str_join(array(IN_UNIT_3349#9329, OUT_UNIT_3350#9332), >) AS COL_163AB4E6_D7B0_4397_BF6B_992AF7938586#9483]
Input [13]: [CANCELED_3355#9324, CHAMP_PMSI_3352#9325, EMERGENCY_3354#9326, IN_DATE_3345#9327, IN_MODE_3347#9328, IN_UNIT_3349#9329, OUT_DATE_3346#9330, OUT_MODE_3348#9331, OUT_UNIT_3350#9332, PATIENT_ID_3344#9333, UNIT_PATH_3353#9334, VISIT_ID_3343#9335, VISIT_TYPE_3351#9336]

(4) CollectLimit
Input [14]: [COL_EEA9697B_DB68_4A22_8733_70F35E85FA8C#9429, COL_8859F9BF_E9D0_49C6_AD56_9C140D4C38A1#9430, COL_AA4B3BC4_44A1_47D3_AC4B_C41D5CB3B3E9#9431, COL_F89F7AFE_9225_468C_A09B_7E0D4F0CD71B#9432, COL_058F9F93_2D83_40ED_B3F6_4CAE6CD3C909#9433, COL_6514FE18_2F15_46F7_BE9B_8C8A1CDED5B0#9434, COL_0C85CE96_902F_49B0_8699_B1D8041E9741#9435, COL_93D07A84_DAB1_4601_8776_58638D68C63B#9436, COL_69F7D2CB_3582_450F_B81C_F35E14BD2F3A#9437, COL_8DD6299D_F88E_4923_BA4A_AA5963BBA243#9438, COL_8F292832_9A81_4CB6_A3E8_AAF5E0E2B9D1#9439, COL_119B8687_79BA_47AC_A253_99B3F514F94F#9440, COL_7A51C905_886C_4162_94AE_BCBA7820952A#9441, COL_163AB4E6_D7B0_4397_BF6B_992AF7938586#9483]
Arguments: 1500

SQL / DataFrame Properties

Name	Value
spark.sql.optimizer.nestedPredicatePushdown.supportedFileSources	parquet,orc,geoparquet