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Weizhong commented on SPARK-9066: --------------------------------- Yes, the root reaason is same, that is cause by scan HDFS too many times, in [PR#6454|https://github.com/apache/spark/pull/6454] use coalesce to decrease partitions, but add two shuffles, but if we change the cartesian order also can decrease the scan times, which I have done in [PR#7417|https://github.com/apache/spark/pull/7417] > Improve cartesian performance > ------------------------------ > > Key: SPARK-9066 > URL: https://issues.apache.org/jira/browse/SPARK-9066 > Project: Spark > Issue Type: Improvement > Components: SQL > Reporter: Weizhong > Priority: Minor > > Currently, for CartesianProduct, if right plan partition record number are > small than left partition record number, then the performance is bad as need > do many times scan for right plan. > For example: > {noformat} > with single_value as ( > select max(1) tpcds_val from date_dim > ) > select sum(ss_quantity * ss_sales_price) ssales, tpcds_val > from store_sales, single_value > group by tpcds_val > {noformat} > above SQL clause, right plan only have 1 record, left plan have 1823 > partiton(in our test) and each partition has more than 4000 records, then for > each left plan partition record we need scan data from hdfs for right plan. > That is, for left plan we need scan _left_plan_partition_num_ times, for > right plan we need scan _left_plan_partition_num * right_plan_partition_num_ > times, total is _left_plan_partition_num * (1 + right_plan_partition_num)_ > times -- 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