Description
CBO underestimates selectivity from filter which consequently results in under estimation throughout the plan.
8 rows, 0.0 cpu, 0.0 io}, id = 7808
HiveJoinRel(condition=[=($0, $12)], joinType=[inner]): rowcount = 11459.928208333333, cumulative cost = {5.50076555E8 rows, 0.0 cpu, 0.0 io}, id = 7426
HiveProjectRel(ss_item_sk=[$1], ss_customer_sk=[$2], ss_cdemo_sk=[$3], ss_hdemo_sk=[$4], ss_addr_sk=[$5], ss_store_sk=[$6], ss_promo_sk=[$7], ss_ticket_number=[$8], ss_wholesale_cost=[$10], ss_list_price=[$11], ss_coupon_amt=[$18], ss_sold_date_sk=[$22]): rowcount = 5.50076554E8, cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io}, id = 893
HiveTableScanRel(table=[[tpcds_bin_partitioned_orc_200_orig.store_sales]]): rowcount = 5.50076554E8, cumulative cost = {0}, id = 55
HiveProjectRel(i_item_sk=[$0], i_current_price=[$5], i_color=[$17], i_product_name=[$21]): rowcount = 1.0, cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io}, id = 1163
HiveFilterRel(condition=[AND(in($17, 'maroon', 'burnished', 'dim', 'steel', 'navajo', 'chocolate'), between(false, $5, 35, +(35, 10)), between(false, $5, +(35, 1), +(35, 15)))]): rowcount = 1.0, cumulative cost = {0.0 rows, 0.0 cpu, 0.0 io}, id = 1161
HiveTableScanRel(table=[[tpcds_bin_partitioned_orc_200_orig.item]]): rowcount = 48000.0, cumulative cost = {0}, id = 68
select count(*) from item where i_color in ('maroon','burnished','dim','steel','navajo','chocolate') and i_current_price between 35 and 35 + 10 and i_current_price between 35 + 1 and 35 + 15;
Attachments
Issue Links
- duplicates
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HIVE-8315 CBO : Negate condition underestimates selectivity which results in an in-efficient plan
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- Closed
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