Optimizing Statistics

Context

GaussDB generates optimal execution plans based on the cost estimation. Optimizers need to estimate the number of data rows and the cost based on statistics collected using ANALYZE. Therefore, the statistics is vital for the estimation of the number of rows and cost. Global statistics are collected using ANALYZE: relpages and reltuples in pg_class; stadistinct, stanullfrac, stanumbersN, stavaluesN, and histogram_bounds in pg_statistic.

Example 1: Poor Query Performance Due to the Lack of Statistics

In most cases, the lack of statistics about tables or columns involved in the query greatly affects the query performance.

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
);

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
);

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;

If such an issue occurs, you can use the following methods to check whether statistics in tables or columns has been collected using ANALYZE:

1. Execute EXPLAIN VERBOSE to analyze the execution plan and check the warning information:

   WARNING:Statistics in some tables or columns(public.lineitem.l_receiptdate, public.lineitem.l_commitdate, public.lineitem.l_orderkey, public.lineitem.l_suppkey, public.orders.o_orderstatus, public.orders.o_orderkey) are not collected.
   HINT:Do analyze for them in order to generate optimized plan.

2. Check whether the following information exists in the log file in the gs_log directory; if it does, the poor query performance was caused by the lack of statistics in some tables or columns:

   2017-06-14 17:28:30.336 CST 140644024579856 20971684 [BACKEND] LOG:Statistics in some tables or columns(public.lineitem.l_receiptdate, public.lineitem.l_commitdate, public.lineitem.l_orderkey, public.linei
   tem.l_suppkey, public.orders.o_orderstatus, public.orders.o_orderkey) are not collected.
   2017-06-14 17:28:30.336 CST 140644024579856 20971684 [BACKEND] HINT:Do analyze for them in order to generate optimized plan.

By using any of the preceding methods, you can identify tables or columns whose statistics have not been collected using ANALYZE. You can execute ANALYZE to warnings or tables and columns recorded in logs to resolve the problem.