Help Center/ GaussDB(DWS)/ Performance Tuning/ Optimization Cases/ Case: Configuring cost_param for Better Query Performance
Updated on 2024-04-28 GMT+08:00

Case: Configuring cost_param for Better Query Performance

The cost_param parameter is used to control use of different estimation methods in specific customer scenarios, allowing estimated values to be close to onsite values. This parameter can control various methods simultaneously by performing AND (&) operations on the bit for each method. A method is selected if its value is not 0.

Scenario 1: Before Optimization

If bit0 of cost_param is set to 1, an improved mechanism is used for estimating the selection rate of non-equi-joins. This method is more accurate for estimating the selection rate of joins between two identical tables. The following example describes the optimization scenario when bit0 of cost_param is set to 1. In V300R002C00 and later, cost_param & 1=0 is not used. That is, an optimized formula is selected for calculation.

The selection rate indicates the percentage for which the number of rows meeting the join conditions account of the JOIN results when the JOIN relationship is established between two tables.

The table structure is as follows:

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CREATE TABLE LINEITEM
(
L_ORDERKEY BIGINT NOT NULL
, L_PARTKEY BIGINT NOT NULL
, L_SUPPKEY BIGINT NOT NULL
, L_LINENUMBER BIGINT NOT NULL
, L_QUANTITY DECIMAL(15,2) NOT NULL
, L_EXTENDEDPRICE DECIMAL(15,2) NOT NULL
, L_DISCOUNT DECIMAL(15,2) NOT NULL
, L_TAX DECIMAL(15,2) NOT NULL
, L_RETURNFLAG CHAR(1) NOT NULL
, L_LINESTATUS CHAR(1) NOT NULL
, L_SHIPDATE DATE NOT NULL
, L_COMMITDATE DATE NOT NULL
, L_RECEIPTDATE DATE NOT NULL
, L_SHIPINSTRUCT CHAR(25) NOT NULL
, L_SHIPMODE CHAR(10) NOT NULL
, L_COMMENT VARCHAR(44) NOT NULL
) with (orientation = column, COMPRESSION = MIDDLE) distribute by hash(L_ORDERKEY);

CREATE TABLE ORDERS
(
O_ORDERKEY BIGINT NOT NULL
, O_CUSTKEY BIGINT NOT NULL
, O_ORDERSTATUS CHAR(1) NOT NULL
, O_TOTALPRICE DECIMAL(15,2) NOT NULL
, O_ORDERDATE DATE NOT NULL
, O_ORDERPRIORITY CHAR(15) NOT NULL
, O_CLERK CHAR(15) NOT NULL
, O_SHIPPRIORITY BIGINT NOT NULL
, O_COMMENT VARCHAR(79) NOT NULL
)with (orientation = column, COMPRESSION = MIDDLE) distribute by hash(O_ORDERKEY);

The query statements are as follows:

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explain verbose select
count(*) as numwait 
from
lineitem l1,
orders 
where
o_orderkey = l1.l_orderkey
and o_orderstatus = 'F'
and l1.l_receiptdate > l1.l_commitdate
and not exists (
select
*
from
lineitem l3
where
l3.l_orderkey = l1.l_orderkey
and l3.l_suppkey <> l1.l_suppkey
and l3.l_receiptdate > l3.l_commitdate
)
order by
numwait desc;

The following figure shows the execution plan. (When verbose is used, distinct is added for column selection which is controlled by cost off/on. The hash join rows show the estimated number of distinct values and the other rows do not.)

Scenario 1: After Optimization

These queries are from Anti Join connected in the lineitem table. When cost_param & bit0 is 0, the estimated number of Anti Join rows greatly differs from that of the actual number of rows, compromising the query performance. You can estimate the number of Anti Join rows more accurately by setting cost_param & bit0 to 1 to improve the query performance. The optimized execution plan is as follows:

Scenario 2: Before Optimization

If bit1 is set to 1 (set cost_param=2), the selection rate is estimated based on multiple filter criteria. The lowest selection rate among all filter criteria, but not the product of the selection rates for two tables under a specific filter criterion, is used as the total selection rate. This method is more accurate when a close correlation exists between the columns to be filtered. The following example describes the optimization scenario when bit1 of cost_param is set to 1.

The table structure is as follows:

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CREATE TABLE NATION
(
N_NATIONKEYINT NOT NULL
, N_NAMECHAR(25) NOT NULL
, N_REGIONKEYINT NOT NULL
, N_COMMENTVARCHAR(152)
) distribute by replication;
CREATE TABLE SUPPLIER
(
S_SUPPKEYBIGINT NOT NULL
, S_NAMECHAR(25) NOT NULL
, S_ADDRESSVARCHAR(40) NOT NULL
, S_NATIONKEYINT NOT NULL
, S_PHONECHAR(15) NOT NULL
, S_ACCTBALDECIMAL(15,2) NOT NULL
, S_COMMENTVARCHAR(101) NOT NULL
) distribute by hash(S_SUPPKEY);
CREATE TABLE PARTSUPP
(
PS_PARTKEYBIGINT NOT NULL
, PS_SUPPKEYBIGINT NOT NULL
, PS_AVAILQTYBIGINT NOT NULL
, PS_SUPPLYCOSTDECIMAL(15,2)NOT NULL
, PS_COMMENTVARCHAR(199) NOT NULL
)distribute by hash(PS_PARTKEY);

The query statements are as follows:

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set cost_param=2;
explain verbose select
nation,
sum(amount) as sum_profit 
from
(
select
n_name as nation,
l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity as amount
from
supplier,
lineitem,
partsupp,
nation
where
s_suppkey = l_suppkey
and ps_suppkey = l_suppkey
and ps_partkey = l_partkey
and s_nationkey = n_nationkey
) as profit 
group by nation 
order by nation;

When bit1 of cost_param is 0, the execution plan is shown as follows:

Scenario 2: After Optimization

In the preceding queries, the hash join criteria of the supplier, lineitem, and partsupp tables are setting lineitem.l_suppkey to supplier.s_suppkey and lineitem.l_partkey to partsupp.ps_partkey. Two filter criteria exist in the hash join conditions. lineitem.l_suppkey in the first filter criteria and lineitem.l_partkey in the second filter criteria are two columns with strong relationship of the lineitem table. In this situation, when you estimate the rate of the hash join conditions, if cost_param & bit1 is 0, the selection rate is estimated based on multiple filter criteria. The lowest selection rate among all filter criteria, but not the product of the selection rates for two tables under a specific filter criterion, is used as the total selection rate. This method is more accurate when a close correlation exists between the columns to be filtered. The plan after optimization is shown as follows: