Mostafa Mokhtar created HIVE-7723:
-------------------------------------
Summary: Explain plan for complex query with lots of partitions is
slow due to in-efficient collection used 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
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;
{code}
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