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Nattavut Sutyanyong edited comment on SPARK-18814 at 12/10/16 3:50 AM: ----------------------------------------------------------------------- It looks like the {{Project}} between {{Aggregate}} and {{Filter scalar-subquery}} maps {{cs_item_sk#39}} to {{cs_item_sk#39#111}}. The logic in the code is not robust enough to recognize that the two symbols are equivalent. I tried to simplify the problem to {code} Seq[(java.lang.Integer, scalar.lang.BigDecimal)]((1,BigDecimal(1.0))).toDF("k","v").createOrReplaceTempView("P") Seq[(java.lang.Integer, scala.math.BigDecimal)]((1,BigDecimal(1.0))).toDF("k1","v1").createOrReplaceTempView("C") sql("select * from p where v = (select 1.1 * avg(v1) from c where c.k1=p.k)").explain(true) {code} This should have all the elements required to reproduce the problem but somehow I could not get the required `Project` operator so there is no mapping of the column p.k as it is in the TPCDS-Q32. I will keep trying. was (Author: nsyca): It looks like the `Project` between `Aggregate` and `Filter scalar-subquery` maps `cs_item_sk#39` to `cs_item_sk#39#111`. The logic in the code is not robust enough to recognize that the two symbols are equivalent. I tried to simplify the problem to {code} Seq[(java.lang.Integer, scalar.lang.BigDecimal)]((1,BigDecimal(1.0))).toDF("k","v").createOrReplaceTempView("P") Seq[(java.lang.Integer, scala.math.BigDecimal)]((1,BigDecimal(1.0))).toDF("k1","v1").createOrReplaceTempView("C") sql("select * from p where v = (select 1.1 * avg(v1) from c where c.k1=p.k)").explain(true) {code} This should have all the elements required to reproduce the problem but somehow I could not get the required `Project` operator so there is no mapping of the column p.k as it is in the TPCDS-Q32. I will keep trying. > CheckAnalysis rejects TPCDS query 32 > ------------------------------------ > > Key: SPARK-18814 > URL: https://issues.apache.org/jira/browse/SPARK-18814 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.1.0 > Reporter: Eric Liang > Priority: Blocker > > It seems the CheckAnalysis rule introduced by SPARK-18504 is incorrect > rejecting this TPCDS query, which ran fine in Spark 2.0. There doesn't seem > to be any obvious error in the query or the check rule though: in the plan > below, the scalar subquery's condition field is "scalar-subquery#24 > [(cs_item_sk#39#111 = i_item_sk#59)] ", which should reference cs_item_sk#39. > Nonetheless CheckAnalysis complains that cs_item_sk#39 is not referenced by > the scalar subquery predicates. > analysis error: > {code} > == Query: q32-v1.4 == > Can't be analyzed: org.apache.spark.sql.AnalysisException: a GROUP BY clause > in a scalar correlated subquery cannot contain non-correlated columns: > cs_item_sk#39;; > GlobalLimit 100 > +- LocalLimit 100 > +- Aggregate [sum(cs_ext_discount_amt#46) AS excess discount amount#23] > +- Filter ((((i_manufact_id#72 = 977) && (i_item_sk#59 = > cs_item_sk#39)) && ((d_date#83 >= 2000-01-27) && (d_date#83 <= > cast(cast(cast(cast(2000-01-27 as date) as timestamp) + interval 12 weeks 6 > days as date) as string)))) && ((d_date_sk#81 = cs_sold_date_sk#58) && > (cast(cs_ext_discount_amt#46 as decimal(14,7)) > cast(scalar-subquery#24 > [(cs_item_sk#39#111 = i_item_sk#59)] as decimal(14,7))))) > : +- Project [(CAST(1.3 AS DECIMAL(11,6)) * > CAST(avg(cs_ext_discount_amt) AS DECIMAL(11,6)))#110, cs_item_sk#39 AS > cs_item_sk#39#111] > : +- Aggregate [cs_item_sk#39], > [CheckOverflow((promote_precision(cast(1.3 as decimal(11,6))) * > promote_precision(cast(avg(cs_ext_discount_amt#46) as decimal(11,6)))), > DecimalType(14,7)) AS (CAST(1.3 AS DECIMAL(11,6)) * > CAST(avg(cs_ext_discount_amt) AS DECIMAL(11,6)))#110, cs_item_sk#39] > : +- Filter (((d_date#83 >= 2000-01-27]) && (d_date#83 <= > cast(cast(cast(cast(2000-01-27 as date) as timestamp) + interval 12 weeks 6 > days as date) as string))) && (d_date_sk#81 = cs_sold_date_sk#58)) > : +- Join Inner > : :- SubqueryAlias catalog_sales > : : +- > Relation[cs_sold_time_sk#25,cs_ship_date_sk#26,cs_bill_customer_sk#27,cs_bill_cdemo_sk#28,cs_bill_hdemo_sk#29,cs_bill_addr_sk#30,cs_ship_customer_sk#31,cs_ship_cdemo_sk#32,cs_ship_hdemo_sk#33,cs_ship_addr_sk#34,cs_call_center_sk#35,cs_catalog_page_sk#36,cs_ship_mode_sk#37,cs_warehouse_sk#38,cs_item_sk#39,cs_promo_sk#40,cs_order_number#41,cs_quantity#42,cs_wholesale_cost#43,cs_list_price#44,cs_sales_price#45,cs_ext_discount_amt#46,cs_ext_sales_price#47,cs_ext_wholesale_cost#48,... > 10 more fields] parquet > : +- SubqueryAlias date_dim > : +- > Relation[d_date_sk#81,d_date_id#82,d_date#83,d_month_seq#84,d_week_seq#85,d_quarter_seq#86,d_year#87,d_dow#88,d_moy#89,d_dom#90,d_qoy#91,d_fy_year#92,d_fy_quarter_seq#93,d_fy_week_seq#94,d_day_name#95,d_quarter_name#96,d_holiday#97,d_weekend#98,d_following_holiday#99,d_first_dom#100,d_last_dom#101,d_same_day_ly#102,d_same_day_lq#103,d_current_day#104,... > 4 more fields] parquet > +- Join Inner > :- Join Inner > : :- SubqueryAlias catalog_sales > : : +- > Relation[cs_sold_time_sk#25,cs_ship_date_sk#26,cs_bill_customer_sk#27,cs_bill_cdemo_sk#28,cs_bill_hdemo_sk#29,cs_bill_addr_sk#30,cs_ship_customer_sk#31,cs_ship_cdemo_sk#32,cs_ship_hdemo_sk#33,cs_ship_addr_sk#34,cs_call_center_sk#35,cs_catalog_page_sk#36,cs_ship_mode_sk#37,cs_warehouse_sk#38,cs_item_sk#39,cs_promo_sk#40,cs_order_number#41,cs_quantity#42,cs_wholesale_cost#43,cs_list_price#44,cs_sales_price#45,cs_ext_discount_amt#46,cs_ext_sales_price#47,cs_ext_wholesale_cost#48,... > 10 more fields] parquet > : +- SubqueryAlias item > : +- > Relation[i_item_sk#59,i_item_id#60,i_rec_start_date#61,i_rec_end_date#62,i_item_desc#63,i_current_price#64,i_wholesale_cost#65,i_brand_id#66,i_brand#67,i_class_id#68,i_class#69,i_category_id#70,i_category#71,i_manufact_id#72,i_manufact#73,i_size#74,i_formulation#75,i_color#76,i_units#77,i_container#78,i_manager_id#79,i_product_name#80] > parquet > +- SubqueryAlias date_dim > +- > Relation[d_date_sk#81,d_date_id#82,d_date#83,d_month_seq#84,d_week_seq#85,d_quarter_seq#86,d_year#87,d_dow#88,d_moy#89,d_dom#90,d_qoy#91,d_fy_year#92,d_fy_quarter_seq#93,d_fy_week_seq#94,d_day_name#95,d_quarter_name#96,d_holiday#97,d_weekend#98,d_following_holiday#99,d_first_dom#100,d_last_dom#101,d_same_day_ly#102,d_same_day_lq#103,d_current_day#104,... > 4 more fields] parquet > {code} > query text: > {code} > select sum(cs_ext_discount_amt) as `excess discount amount` > from > catalog_sales, item, date_dim > where > i_manufact_id = 977 > and i_item_sk = cs_item_sk > and d_date between '2000-01-27' and (cast('2000-01-27' as date) + interval > 90 days) > and d_date_sk = cs_sold_date_sk > and cs_ext_discount_amt > ( > select 1.3 * avg(cs_ext_discount_amt) > from catalog_sales, date_dim > where cs_item_sk = i_item_sk > and d_date between '2000-01-27]' and (cast('2000-01-27' as date) + > interval 90 days) > and d_date_sk = cs_sold_date_sk) > limit 100 > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org