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Gopal V commented on HIVE-7723: ------------------------------- [~mmokhtar]: Can you open a review ticket on reviews.apache.org? > Explain plan for complex query with lots of partitions is slow due to > in-efficient collection used to find a matching ReadEntity > -------------------------------------------------------------------------------------------------------------------------------- > > Key: HIVE-7723 > URL: https://issues.apache.org/jira/browse/HIVE-7723 > Project: Hive > Issue Type: Bug > Components: CLI, Physical Optimizer > Affects Versions: 0.13.1 > Reporter: Mostafa Mokhtar > Assignee: Mostafa Mokhtar > Fix For: 0.14.0 > > Attachments: HIVE-7723.1.patch, HIVE-7723.2.patch, HIVE-7723.3.patch > > > Explain on TPC-DS query 64 took 11 seconds, when the CLI was profiled it > showed that ReadEntity.equals is taking ~40% of the CPU. > ReadEntity.equals is called from the snippet below. > Again and again the set is iterated over to get the actual match, a HashMap > is a better option for this case as Set doesn't have a Get method. > Also for ReadEntity equals is case-insensitive while hash is , which is an > undesired behavior. > {code} > public static ReadEntity addInput(Set<ReadEntity> inputs, ReadEntity > newInput) { > // If the input is already present, make sure the new parent is added to > the input. > if (inputs.contains(newInput)) { > for (ReadEntity input : inputs) { > if (input.equals(newInput)) { > if ((newInput.getParents() != null) && > (!newInput.getParents().isEmpty())) { > input.getParents().addAll(newInput.getParents()); > input.setDirect(input.isDirect() || newInput.isDirect()); > } > return input; > } > } > assert false; > } else { > inputs.add(newInput); > return newInput; > } > // make compile happy > return null; > } > {code} > This is the query used : > {code} > select cs1.product_name ,cs1.store_name ,cs1.store_zip ,cs1.b_street_number > ,cs1.b_streen_name ,cs1.b_city > ,cs1.b_zip ,cs1.c_street_number ,cs1.c_street_name ,cs1.c_city > ,cs1.c_zip ,cs1.syear ,cs1.cnt > ,cs1.s1 ,cs1.s2 ,cs1.s3 > ,cs2.s1 ,cs2.s2 ,cs2.s3 ,cs2.syear ,cs2.cnt > from > (select i_product_name as product_name ,i_item_sk as item_sk ,s_store_name as > store_name > ,s_zip as store_zip ,ad1.ca_street_number as b_street_number > ,ad1.ca_street_name as b_streen_name > ,ad1.ca_city as b_city ,ad1.ca_zip as b_zip ,ad2.ca_street_number as > c_street_number > ,ad2.ca_street_name as c_street_name ,ad2.ca_city as c_city ,ad2.ca_zip > as c_zip > ,d1.d_year as syear ,d2.d_year as fsyear ,d3.d_year as s2year ,count(*) > as cnt > ,sum(ss_wholesale_cost) as s1 ,sum(ss_list_price) as s2 > ,sum(ss_coupon_amt) as s3 > FROM store_sales > JOIN store_returns ON store_sales.ss_item_sk = > store_returns.sr_item_sk and store_sales.ss_ticket_number = > store_returns.sr_ticket_number > JOIN customer ON store_sales.ss_customer_sk = customer.c_customer_sk > JOIN date_dim d1 ON store_sales.ss_sold_date_sk = d1.d_date_sk > JOIN date_dim d2 ON customer.c_first_sales_date_sk = d2.d_date_sk > JOIN date_dim d3 ON customer.c_first_shipto_date_sk = d3.d_date_sk > JOIN store ON store_sales.ss_store_sk = store.s_store_sk > JOIN customer_demographics cd1 ON store_sales.ss_cdemo_sk= > cd1.cd_demo_sk > JOIN customer_demographics cd2 ON customer.c_current_cdemo_sk = > cd2.cd_demo_sk > JOIN promotion ON store_sales.ss_promo_sk = promotion.p_promo_sk > JOIN household_demographics hd1 ON store_sales.ss_hdemo_sk = > hd1.hd_demo_sk > JOIN household_demographics hd2 ON customer.c_current_hdemo_sk = > hd2.hd_demo_sk > JOIN customer_address ad1 ON store_sales.ss_addr_sk = > ad1.ca_address_sk > JOIN customer_address ad2 ON customer.c_current_addr_sk = > ad2.ca_address_sk > JOIN income_band ib1 ON hd1.hd_income_band_sk = ib1.ib_income_band_sk > JOIN income_band ib2 ON hd2.hd_income_band_sk = ib2.ib_income_band_sk > JOIN item ON store_sales.ss_item_sk = item.i_item_sk > JOIN > (select cs_item_sk > ,sum(cs_ext_list_price) as > sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund > from catalog_sales JOIN catalog_returns > ON catalog_sales.cs_item_sk = catalog_returns.cr_item_sk > and catalog_sales.cs_order_number = catalog_returns.cr_order_number > group by cs_item_sk > having > sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)) > cs_ui > ON store_sales.ss_item_sk = cs_ui.cs_item_sk > WHERE > cd1.cd_marital_status <> cd2.cd_marital_status and > 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 > and ss_sold_date between '2000-01-01' and '2000-12-31' > group by i_product_name ,i_item_sk ,s_store_name ,s_zip ,ad1.ca_street_number > ,ad1.ca_street_name ,ad1.ca_city ,ad1.ca_zip ,ad2.ca_street_number > ,ad2.ca_street_name ,ad2.ca_city ,ad2.ca_zip ,d1.d_year ,d2.d_year > ,d3.d_year > ) cs1 > JOIN > (select i_product_name as product_name ,i_item_sk as item_sk ,s_store_name as > store_name > ,s_zip as store_zip ,ad1.ca_street_number as b_street_number > ,ad1.ca_street_name as b_streen_name > ,ad1.ca_city as b_city ,ad1.ca_zip as b_zip ,ad2.ca_street_number as > c_street_number > ,ad2.ca_street_name as c_street_name ,ad2.ca_city as c_city ,ad2.ca_zip > as c_zip > ,d1.d_year as syear ,d2.d_year as fsyear ,d3.d_year as s2year ,count(*) > as cnt > ,sum(ss_wholesale_cost) as s1 ,sum(ss_list_price) as s2 > ,sum(ss_coupon_amt) as s3 > FROM store_sales > JOIN store_returns ON store_sales.ss_item_sk = > store_returns.sr_item_sk and store_sales.ss_ticket_number = > store_returns.sr_ticket_number > JOIN customer ON store_sales.ss_customer_sk = customer.c_customer_sk > JOIN date_dim d1 ON store_sales.ss_sold_date_sk = d1.d_date_sk > JOIN date_dim d2 ON customer.c_first_sales_date_sk = d2.d_date_sk > JOIN date_dim d3 ON customer.c_first_shipto_date_sk = d3.d_date_sk > JOIN store ON store_sales.ss_store_sk = store.s_store_sk > JOIN customer_demographics cd1 ON store_sales.ss_cdemo_sk= > cd1.cd_demo_sk > JOIN customer_demographics cd2 ON customer.c_current_cdemo_sk = > cd2.cd_demo_sk > JOIN promotion ON store_sales.ss_promo_sk = promotion.p_promo_sk > JOIN household_demographics hd1 ON store_sales.ss_hdemo_sk = > hd1.hd_demo_sk > JOIN household_demographics hd2 ON customer.c_current_hdemo_sk = > hd2.hd_demo_sk > JOIN customer_address ad1 ON store_sales.ss_addr_sk = > ad1.ca_address_sk > JOIN customer_address ad2 ON customer.c_current_addr_sk = > ad2.ca_address_sk > JOIN income_band ib1 ON hd1.hd_income_band_sk = ib1.ib_income_band_sk > JOIN income_band ib2 ON hd2.hd_income_band_sk = ib2.ib_income_band_sk > JOIN item ON store_sales.ss_item_sk = item.i_item_sk > JOIN > (select cs_item_sk > ,sum(cs_ext_list_price) as > sale,sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit) as refund > from catalog_sales JOIN catalog_returns > ON catalog_sales.cs_item_sk = catalog_returns.cr_item_sk > and catalog_sales.cs_order_number = catalog_returns.cr_order_number > group by cs_item_sk > having > sum(cs_ext_list_price)>2*sum(cr_refunded_cash+cr_reversed_charge+cr_store_credit)) > cs_ui > ON store_sales.ss_item_sk = cs_ui.cs_item_sk > WHERE > cd1.cd_marital_status <> cd2.cd_marital_status and > 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 > and ss_sold_date between '2001-01-01' and '2001-12-31' > group by i_product_name ,i_item_sk ,s_store_name ,s_zip ,ad1.ca_street_number > ,ad1.ca_street_name ,ad1.ca_city ,ad1.ca_zip ,ad2.ca_street_number > ,ad2.ca_street_name ,ad2.ca_city ,ad2.ca_zip ,d1.d_year ,d2.d_year > ,d3.d_year > ) cs2 > ON cs1.item_sk=cs2.item_sk > where > cs1.syear = 2000 and > cs2.syear = 2000 + 1 and > cs2.cnt <= cs1.cnt and > cs1.store_name = cs2.store_name and > cs1.store_zip = cs2.store_zip > order by cs1.product_name ,cs1.store_name ,cs2.cnt; > 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