SP1 - Details for Query 288

Submitted Time: 2026/04/21 11:40:55
Duration: 0.1 s
Succeeded Jobs: 314

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: 6 ms"; 2 [labelType="html" label=" Project "]; } 3 [labelType="html" label="Scan csv number of output rows: 0 number of files read: 1 metadata time: 0 ms size of files read: 2.0 B"]; 2->0; 3->2; }

CollectLimit 1500

Project [c0#65741 AS COL_COLONNE_390645#66349, c0#65741 AS COL_DTYPE_PANDAS_390646#66350, c0#65741 AS COL_TYPE_INFERE_390647#66351, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_TOTA_390648#66352L, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_NULL_390649#66353L, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_PCT_NUL_390650#66354, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_NON__390651#66355L, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_DIST_390652#66356L, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MIN_390653#66357, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MAX_390654#66358, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ETENDUE_390655#66359, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MOYENNE_390656#66360, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MEDIANE_390657#66361, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_VARIANC_390658#66362, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ECART_T_390659#66363, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_SKEWNES_390660#66364, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_KURTOSI_390661#66365, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_Q1_390662#66366, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MEDIANE_390663#66367, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_Q3_390664#66368, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_IQR_390665#66369, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_OUTL_390666#66370, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_PCT_OUT_390667#66371, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_ZERO_390668#66372, ... 36 more fields]

WholeStageCodegen (1)

FileScan csv [c0#65741] Batched: false, DataFilters: [], Format: CSV, Location: InMemoryFileIndex(1 paths)[file:/data/input/depot/csv/execution/empty.csv], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<c0:string>

Details

== Physical Plan ==
CollectLimit (3)
+- * Project (2)
   +- Scan csv  (1)


(1) Scan csv 
Output [1]: [c0#65741]
Batched: false
Location: InMemoryFileIndex [file:/data/input/depot/csv/execution/empty.csv]
ReadSchema: struct<c0:string>

(2) Project [codegen id : 1]
Output [60]: [c0#65741 AS COL_COLONNE_390645#66349, c0#65741 AS COL_DTYPE_PANDAS_390646#66350, c0#65741 AS COL_TYPE_INFERE_390647#66351, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_TOTA_390648#66352L, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_NULL_390649#66353L, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_PCT_NUL_390650#66354, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_NON__390651#66355L, cast(c0#65741 as bigint) AS COL_ANALYSE_NB_DIST_390652#66356L, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MIN_390653#66357, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MAX_390654#66358, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ETENDUE_390655#66359, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MOYENNE_390656#66360, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MEDIANE_390657#66361, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_VARIANC_390658#66362, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ECART_T_390659#66363, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_SKEWNES_390660#66364, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_KURTOSI_390661#66365, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_Q1_390662#66366, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_MEDIANE_390663#66367, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_Q3_390664#66368, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_IQR_390665#66369, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_OUTL_390666#66370, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_PCT_OUT_390667#66371, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_ZERO_390668#66372, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_NEGA_390669#66373, c0#65741 AS COL_ANALYSE_TOP_10__390670#66374, c0#65741 AS COL_ANALYSE_DISTRIB_390671#66375, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_VIDE_390672#66376, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_PCT_VID_390673#66377, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_WHIT_390674#66378, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_LEAD_390675#66379, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_TRAI_390676#66380, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_LEAD_390677#66381, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_LONGUEU_390678#66382, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_LONGUEU_390679#66383, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_LONGUEU_390680#66384, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_LONGUEU_390681#66385, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_LONGUEU_390682#66386, c0#65741 AS COL_ANALYSE_VALEUR__390683#66387, c0#65741 AS COL_ANALYSE_VALEUR__390684#66388, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_AVEC_390685#66389, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_AVEC_390686#66390, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_UPPE_390687#66391, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_LOWE_390688#66392, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_MIXT_390689#66393, c0#65741 AS COL_ANALYSE_DATETIM_390690#66394, c0#65741 AS COL_ANALYSE_DATETIM_390691#66395, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ETENDUE_390692#66396, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ETENDUE_390693#66397, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ANNEE_M_390694#66398, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_ANNEE_M_390695#66399, c0#65741 AS COL_ANALYSE_TIMEZON_390696#66400, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_WEEK_390697#66401, cast(REFORMAT_FOR_DOUBLE(c0#65741) as double) AS COL_ANALYSE_NB_SEMA_390698#66402, c0#65741 AS COL_ANALYSE_DISTRIB_390699#66403, c0#65741 AS COL_ANALYSE_DISTRIB_390700#66404, c0#65741 AS COL_ANALYSE_DISTRIB_390701#66405, c0#65741 AS COL_ANALYSE_DISTRIB_390702#66406, c0#65741 AS COL_SOURCE_390703#66407, c0#65741 AS COL_HORODATAGE_TRAI_390704#66408]
Input [1]: [c0#65741]

(3) CollectLimit
Input [60]: [COL_COLONNE_390645#66349, COL_DTYPE_PANDAS_390646#66350, COL_TYPE_INFERE_390647#66351, COL_ANALYSE_NB_TOTA_390648#66352L, COL_ANALYSE_NB_NULL_390649#66353L, COL_ANALYSE_PCT_NUL_390650#66354, COL_ANALYSE_NB_NON__390651#66355L, COL_ANALYSE_NB_DIST_390652#66356L, COL_ANALYSE_MIN_390653#66357, COL_ANALYSE_MAX_390654#66358, COL_ANALYSE_ETENDUE_390655#66359, COL_ANALYSE_MOYENNE_390656#66360, COL_ANALYSE_MEDIANE_390657#66361, COL_ANALYSE_VARIANC_390658#66362, COL_ANALYSE_ECART_T_390659#66363, COL_ANALYSE_SKEWNES_390660#66364, COL_ANALYSE_KURTOSI_390661#66365, COL_ANALYSE_Q1_390662#66366, COL_ANALYSE_MEDIANE_390663#66367, COL_ANALYSE_Q3_390664#66368, COL_ANALYSE_IQR_390665#66369, COL_ANALYSE_NB_OUTL_390666#66370, COL_ANALYSE_PCT_OUT_390667#66371, COL_ANALYSE_NB_ZERO_390668#66372, COL_ANALYSE_NB_NEGA_390669#66373, COL_ANALYSE_TOP_10__390670#66374, COL_ANALYSE_DISTRIB_390671#66375, COL_ANALYSE_NB_VIDE_390672#66376, COL_ANALYSE_PCT_VID_390673#66377, COL_ANALYSE_NB_WHIT_390674#66378, COL_ANALYSE_NB_LEAD_390675#66379, COL_ANALYSE_NB_TRAI_390676#66380, COL_ANALYSE_NB_LEAD_390677#66381, COL_ANALYSE_LONGUEU_390678#66382, COL_ANALYSE_LONGUEU_390679#66383, COL_ANALYSE_LONGUEU_390680#66384, COL_ANALYSE_LONGUEU_390681#66385, COL_ANALYSE_LONGUEU_390682#66386, COL_ANALYSE_VALEUR__390683#66387, COL_ANALYSE_VALEUR__390684#66388, COL_ANALYSE_NB_AVEC_390685#66389, COL_ANALYSE_NB_AVEC_390686#66390, COL_ANALYSE_NB_UPPE_390687#66391, COL_ANALYSE_NB_LOWE_390688#66392, COL_ANALYSE_NB_MIXT_390689#66393, COL_ANALYSE_DATETIM_390690#66394, COL_ANALYSE_DATETIM_390691#66395, COL_ANALYSE_ETENDUE_390692#66396, COL_ANALYSE_ETENDUE_390693#66397, COL_ANALYSE_ANNEE_M_390694#66398, COL_ANALYSE_ANNEE_M_390695#66399, COL_ANALYSE_TIMEZON_390696#66400, COL_ANALYSE_NB_WEEK_390697#66401, COL_ANALYSE_NB_SEMA_390698#66402, COL_ANALYSE_DISTRIB_390699#66403, COL_ANALYSE_DISTRIB_390700#66404, COL_ANALYSE_DISTRIB_390701#66405, COL_ANALYSE_DISTRIB_390702#66406, COL_SOURCE_390703#66407, COL_HORODATAGE_TRAI_390704#66408]
Arguments: 1500

SQL / DataFrame Properties

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