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PolarDB:Performance metrics

Last Updated:Oct 21, 2026

Complex analytical queries that involve multi-table joins, subqueries, aggregations, and sorting take a long time on the PostgreSQL row store: three of the 22 queries in this TPC-H SF100 test (Q9, Q17, and Q20) time out on the row store. The columnstore index (syntax name csi, also known as IMCI) is designed for such queries. This topic uses the data tables of TPC-H SF100 (100 GB) and 22 standard SQL queries as an example to describe the complete and reproducible procedure from data preparation and columnstore index creation to query execution and result comparison. In the test, the columnstore indexes take 14.784 seconds in total, whereas the PostgreSQL row store with default parameters takes more than 2006 seconds. The speedup calculated based on the total execution time is greater than 135x, and the speedup of a single query ranges from 7x to 1168x.

Test content and data volume

TPC-H is a widely used industry-standard performance benchmark developed and published by the TPC to evaluate the analytical capabilities of databases. The columnstore index query test uses 8 data tables and executes 22 complex SQL queries, covering single-table statistics, multi-table joins, subqueries, aggregations, and sorting. The test data volume is TPC-H SF100 (100 GB of data).

Note

The TPC-H implementation in this topic is based on TPC-H benchmarking. These test results cannot be compared with published TPC-H benchmark results because the tests do not fully meet all TPC-H requirements.

Test environment

The test environment is configured as follows:

  • PolarDB for PostgreSQL cluster:

    • Database engine: PostgreSQL 14.

    • Product edition: Enterprise Edition, dedicated specifications.

    • Node specification: 32 cores, 256 GB.

Environment preparation

Before you start the test, make sure that the following requirements are met. Generating the test data takes approximately 30 minutes, and creating the columnstore indexes in a single-threaded serial manner takes approximately 39 minutes. Reserve the test time accordingly.

Data preparation

Data preparation includes compiling the TPCH tool, generating the test data, and importing the data into the test database tpchdb. Perform the following steps in order:

  1. Decompress and compile the dbgen tool.

    # Decompress
    tar -zxvf dbgen.tar.gz
    # Compile
    cd./dbgen
    make -f makefile.suite
  2. Use the TPCH tool to generate 100 GB of test data. The expected execution time is approximately 30 minutes.

    # Change to the dbgen directory
    ./dbgen -s 100 -f
  3. Make sure that you are in the dbgen directory. pwd should return /<installation_path>/dbgen.

    # Confirm the current directory
    pwd
  4. On the ECS instance, use the database connection tool provided by PolarDB (PolarDB-Tools) to connect to your cluster from the command line. The target database is tpchdb.

    /u01/polardb_pg_tools/bin/psql  -h <cluster_endpoint> -p <port_for_cluster_endpoint> -U <privileged_account> -d tpchdb
  5. Import the test data.

    \i./dss.ddl
    \copy part from./part.tbl with delimiter as '|' NULL '';
    \copy region from./region.tbl with delimiter as '|' NULL '';
    \copy nation from./nation.tbl with delimiter as '|' NULL '';
    \copy orders from./orders.tbl with delimiter as '|' NULL '';
    \copy customer from./customer.tbl with delimiter as '|' NULL '';
    \copy lineitem from./lineitem.tbl with delimiter as '|' NULL '';
    \copy partsupp from./partsupp.tbl with delimiter as '|' NULL '';
    \copy supplier from./supplier.tbl with delimiter as '|' NULL '';
  6. Verify the import results of the eight tables. The row count of each table must match the row count listed in the Columnstore index disk space section (866,037,932 rows in total). If a table fails to be imported, re-import the data of that table before you perform the subsequent steps.

Enable and create columnstore indexes

  1. Based on your PolarDB for PostgreSQL cluster version, enable the columnstore index feature.

  2. Create columnstore indexes for the eight test tables.

    -- partsupp table
    ALTER TABLE PARTSUPP ADD CONSTRAINT partsupp_pkey PRIMARY KEY (PS_PARTKEY, PS_SUPPKEY);
    CREATE INDEX imps ON partsupp USING csi(ps_partkey, ps_suppkey, ps_availqty, ps_supplycost, ps_comment);
    
    -- part table
    ALTER TABLE PART ADD CONSTRAINT part_kpey PRIMARY KEY (P_PARTKEY);
    CREATE INDEX im_p ON part USING csi(p_partkey, p_name, p_mfgr, p_brand, p_type, p_size, p_container, p_retailprice, p_comment);
    
    -- supplier table
    ALTER TABLE SUPPLIER ADD CONSTRAINT supplier_pkey PRIMARY KEY (S_SUPPKEY);
    CREATE INDEX im_s ON supplier USING csi(s_suppkey, s_name, s_address, s_nationkey, s_phone, s_acctbal, s_comment);
    
    -- customer table
    ALTER TABLE CUSTOMER ADD CONSTRAINT customer_pkey PRIMARY KEY (C_CUSTKEY);
    CREATE INDEX im_c ON customer USING csi(c_custkey, c_name, c_address, c_nationkey, c_phone, c_acctbal, c_mktsegment, c_comment);
    
    -- orders table
    ALTER TABLE ORDERS ADD CONSTRAINT orders_pkey PRIMARY KEY (O_ORDERKEY);
    CREATE INDEX im_o ON orders USING csi(o_orderkey, o_custkey, o_orderstatus, o_totalprice, o_orderdate, o_orderpriority, o_clerk, o_shippriority, o_comment);
    
    -- lineitem table
    ALTER TABLE LINEITEM ADD CONSTRAINT lineitem_pkey PRIMARY KEY (L_ORDERKEY, L_LINENUMBER);
    CREATE INDEX im_l ON lineitem USING csi(l_orderkey, l_partkey, l_suppkey, l_linenumber, l_quantity, l_extendedprice, l_discount, l_tax, l_returnflag, l_linestatus, l_shipdate, l_commitdate, l_receiptdate, l_shipinstruct, l_shipmode, l_comment);
    
    -- nation table
    ALTER TABLE NATION ADD CONSTRAINT nation_pkey PRIMARY KEY (N_NATIONKEY);
    CREATE INDEX im_n ON nation USING csi(n_nationkey, n_name, n_regionkey, n_comment);
    
    -- region table
    ALTER TABLE REGION ADD CONSTRAINT region_pkey PRIMARY KEY (R_REGIONKEY);
    CREATE INDEX im_r ON region USING csi(r_regionkey, r_name, r_comment);
  3. Make sure that the columnstore indexes of all the eight test tables are created before you execute the subsequent queries.

  4. Configure the columnstore index parameters for the subsequent queries. First, in the cluster parameter settings of the console, set polar_csi.max_parallel_workers to 32 and make the configuration take effect as prompted by the console. Then run the following commands in the session. For the values and take-effect methods of the parameters, see Columnstore index parameters.

    SET polar_csi.enable_query TO ON;
    SET polar_csi.cost_threshold TO 0;
    Note
    • polar_csi.memory_limit is a SIGHUP parameter. After it is modified, you must reload the configuration for the modification to take effect. You cannot modify it by using SET in the current session. To adjust the memory limit for the test, configure it in the console before you create the columnstore indexes and start the test, and complete the parameter reload or the restart of the related workers as prompted by the console.

    • polar_csi.max_parallel_workers was named polar_csi.exec_parallel in early engine versions. For older engine versions that do not support polar_csi.max_parallel_workers, use polar_csi.exec_parallel.

      • PostgreSQL 14:

        • For version 2.0.14.20.42.0 and earlier, use polar_csi.exec_parallel.

        • For version 2.0.14.20.43.0 and later, use polar_csi.max_parallel_workers.

      • PostgreSQL 16:

        • For version 2.0.16.11.15.0 and earlier, use polar_csi.exec_parallel.

        • For version 2.0.16.13.16.0 and later, use polar_csi.max_parallel_workers.

Execute SQL queries

In the PolarDB for PostgreSQL cluster, execute the 22 complex SQL queries in sequence and collect the execution time.

  1. Enable timing statistics before you execute the queries. \timing collects the total execution time of each SQL statement. You must enable it to collect execution time data.

    \timing
  2. Execute the 22 queries in sequence. Each query starts with EXPLAIN ANALYZE, which outputs the execution plan and the Execution Time. The total execution time collected by \timing includes the client round-trip overhead and differs from the Execution Time. Use a consistent metric when you collect and compare execution times, and do not mix these two metrics.

    Click to view the details of the 22 SQL queries

    Q1

    EXPLAIN ANALYZE
    SELECT
        l_returnflag,
        l_linestatus,
        sum(l_quantity) as sum_qty,
        sum(l_extendedprice) as sum_base_price,
        sum(l_extendedprice * (1 - l_discount)) as sum_disc_price,
        sum(l_extendedprice * (1 - l_discount) * (1 + l_tax)) as sum_charge,
        avg(l_quantity) as avg_qty,
        avg(l_extendedprice) as avg_price,
        avg(l_discount) as avg_disc,
        count(*) as count_order
    FROM
        lineitem
    WHERE l_shipdate <= date '1998-12-01' - '60 day'::interval
    GROUP BY
        l_returnflag,
        l_linestatus
    ORDER BY
        l_returnflag,
        l_linestatus;

    Q2

    EXPLAIN ANALYZE
    SELECT
        s_acctbal,
        s_name,
        n_name,
        p_partkey,
        p_mfgr,
        s_address,
        s_phone,
        s_comment
    FROM
        part,
        supplier,
        partsupp,
        nation,
        region
    WHERE
        p_partkey = ps_partkey
        and s_suppkey = ps_suppkey
        and p_size = 43
        and p_type like '%NICKEL'
        and s_nationkey = n_nationkey
        and n_regionkey = r_regionkey
        and r_name = 'MIDDLE EAST'
        and ps_supplycost = (
        SELECT
        min(ps_supplycost)
        FROM
        partsupp,
        supplier,
        nation,
        region
        WHERE
        p_partkey = ps_partkey
        and s_suppkey = ps_suppkey
        and s_nationkey = n_nationkey
        and n_regionkey = r_regionkey
        and r_name = 'MIDDLE EAST'
        )
    ORDER BY
        s_acctbal desc,
        n_name,
        s_name,
        p_partkey limit 100;

    Q3

    EXPLAIN ANALYZE
    SELECT
        l_orderkey,
        sum(l_extendedprice * (1 - l_discount)) as revenue,
        o_orderdate,
        o_shippriority
    FROM
        customer,
        orders,
        lineitem
    WHERE
        c_mktsegment = 'FURNITURE'
        and c_custkey = o_custkey
        and l_orderkey = o_orderkey
        and o_orderdate < date '1995-03-05'
        and l_shipdate > date '1995-03-05'
    GROUP BY
        l_orderkey,
        o_orderdate,
        o_shippriority
    ORDER BY
        revenue desc,
        o_orderdate limit 100;

    Q4

    EXPLAIN ANALYZE
    SELECT
        o_orderpriority,
        count(*) as order_count
    FROM
        orders
    WHERE
        o_orderdate >= date '1993-05-01'
        and o_orderdate < date '1993-05-01' + interval '3 month'::interval
        and exists (
        SELECT
        *
        FROM
        lineitem
        WHERE
        l_orderkey = o_orderkey
        and l_commitdate < l_receiptdate
        )
    GROUP BY
        o_orderpriority
    ORDER BY
        o_orderpriority;

    Q5

    EXPLAIN ANALYZE
    SELECT
            n_name,
            sum(l_extendedprice * (1 - l_discount)) as revenue
    FROM
            customer,
            orders,
            lineitem,
            supplier,
            nation,
            region
    WHERE
            c_custkey = o_custkey
            and l_orderkey = o_orderkey
            and l_suppkey = s_suppkey
            and c_nationkey = s_nationkey
            and s_nationkey = n_nationkey
            and n_regionkey = r_regionkey
            and r_name = 'MIDDLE EAST'
            and o_orderdate >= date '1995-01-01'
            and o_orderdate < date '1995-01-01' + '1 year'::interval
    GROUP BY
            n_name
    ORDER BY
            revenue desc;

    Q6

    EXPLAIN ANALYZE
    SELECT
            sum(l_extendedprice * l_discount) as revenue
    FROM
            lineitem
    WHERE
            l_shipdate >= date '1993-01-01'
            and l_shipdate < date '1993-01-01' + '1 year'::interval
            and l_discount between 0.03 - 0.01 and 0.03 + 0.01
            and l_quantity < 24;

    Q7

    EXPLAIN ANALYZE
    SELECT
        supp_nation,
        cust_nation,
        l_year,
        sum(volume) AS revenue
    FROM (
        SELECT
            n1.n_name AS supp_nation,
            n2.n_name AS cust_nation,
            extract(year FROM l_shipdate) AS l_year,
            l_extendedprice * (1 - l_discount) AS volume
        FROM
            supplier,
            lineitem,
            orders,
            customer,
            nation n1,
            nation n2
        WHERE
            s_suppkey = l_suppkey
            AND o_orderkey = l_orderkey
            AND c_custkey = o_custkey
            AND s_nationkey = n1.n_nationkey
            AND c_nationkey = n2.n_nationkey
            AND ((n1.n_name = 'FRANCE'
                    AND n2.n_name = 'GERMANY')
                OR (n1.n_name = 'GERMANY'
                    AND n2.n_name = 'FRANCE'))
            AND l_shipdate BETWEEN CAST('1995-01-01' AS date)
            AND CAST('1996-12-31' AS date)) AS shipping
    GROUP BY
        supp_nation,
        cust_nation,
        l_year
    ORDER BY
        supp_nation,
        cust_nation,
        l_year;

    Q8

    EXPLAIN ANALYZE
    SELECT
            o_year,
            sum(case
                    when nation = 'INDONESIA' then volume
                    else 0
            end) / sum(volume) as mkt_share
    FROM
            (
                    SELECT
                            extract(year from o_orderdate) as o_year,
                            l_extendedprice * (1 - l_discount) as volume,
                            n2.n_name as nation
                    FROM
                            part,
                            supplier,
                            lineitem,
                            orders,
                            customer,
                            nation n1,
                            nation n2,
                            region
                    WHERE
                            p_partkey = l_partkey
                            and s_suppkey = l_suppkey
                            and l_orderkey = o_orderkey
                            and o_custkey = c_custkey
                            and c_nationkey = n1.n_nationkey
                            and n1.n_regionkey = r_regionkey
                            and r_name = 'ASIA'
                            and s_nationkey = n2.n_nationkey
                            and o_orderdate between '1995-01-01'::date and '1996-12-31'::date
                            and p_type = 'PROMO POLISHED NICKEL'
            ) as all_nations
    GROUP BY
            o_year
    ORDER BY
            o_year;

    Q9

    EXPLAIN ANALYZE
    SELECT
            nation,
            o_year,
            sum(amount) as sum_profit
    FROM
            (
                    SELECT
                            n_name as nation,
                            extract(year from o_orderdate) as o_year,
                            l_extendedprice * (1 - l_discount) - ps_supplycost * l_quantity as amount
                    FROM
                            part,
                            supplier,
                            lineitem,
                            partsupp,
                            orders,
                            nation
                    WHERE
                            s_suppkey = l_suppkey
                            and ps_suppkey = l_suppkey
                            and ps_partkey = l_partkey
                            and p_partkey = l_partkey
                            and o_orderkey = l_orderkey
                            and s_nationkey = n_nationkey
                            and p_name like '%navajo%'
            ) as profit
    GROUP BY
            nation,
            o_year
    ORDER BY
            nation,
            o_year desc limit 100;

    Q10

    EXPLAIN ANALYZE
    SELECT
            c_custkey,
            c_name,
            sum(l_extendedprice * (1 - l_discount)) as revenue,
            c_acctbal,
            n_name,
            c_address,
            c_phone,
            c_comment
    FROM
            customer,
            orders,
            lineitem,
            nation
    WHERE
            c_custkey = o_custkey
            and l_orderkey = o_orderkey
            and o_orderdate >= date '1993-08-01'
            and o_orderdate < date '1993-08-01' + '3 month'::interval
            and l_returnflag = 'R'
            and c_nationkey = n_nationkey
    GROUP BY
            c_custkey,
            c_name,
            c_acctbal,
            c_phone,
            n_name,
            c_address,
            c_comment
    ORDER BY
            revenue desc
            LIMIT 20;

    Q11

    EXPLAIN ANALYZE
    SELECT
            ps_partkey,
            sum(ps_supplycost * ps_availqty) as value
    FROM
            partsupp,
            supplier,
            nation
    WHERE
            ps_suppkey = s_suppkey
            and s_nationkey = n_nationkey
            and n_name = 'ALGERIA'
    GROUP BY
            ps_partkey having
                    sum(ps_supplycost * ps_availqty) > (
                            SELECT
                                    sum(ps_supplycost * ps_availqty) * 0.0001000000
                            FROM
                                    partsupp,
                                    supplier,
                                    nation
                            WHERE
                                    ps_suppkey = s_suppkey
                                    and s_nationkey = n_nationkey
                                    and n_name = 'ALGERIA'
                    )
    ORDER BY
            value desc;

    Q12

    EXPLAIN ANALYZE
    SELECT
            l_shipmode,
            sum(case
                    when o_orderpriority = '1-URGENT'
                            or o_orderpriority = '2-HIGH'
                            then 1
                    else 0
            end) as high_line_count,
            sum(case
                    when o_orderpriority <> '1-URGENT'
                            and o_orderpriority <> '2-HIGH'
                            then 1
                    else 0
            end) as low_line_count
    FROM
            orders,
            lineitem
    WHERE
            o_orderkey = l_orderkey
            and l_shipmode in ('AIR', 'FOB')
            and l_commitdate < l_receiptdate
            and l_shipdate < l_commitdate
            and l_receiptdate >= date '1996-01-01'
            and l_receiptdate < date '1996-01-01' + '1 year'::interval
    GROUP BY
            l_shipmode
    ORDER BY
            l_shipmode;

    Q13

    EXPLAIN ANALYZE
    SELECT
            c_count,
            count(*) as custdist
    FROM
            (
                    SELECT
                            c_custkey,
                            count(o_orderkey)
                    FROM
                            customer left outer join orders on
                                    c_custkey = o_custkey
                                    and o_comment not like '%pending%requests%'
                    GROUP BY
                            c_custkey
            ) as c_orders (c_custkey, c_count)
    GROUP BY
            c_count
    ORDER BY
            custdist desc,
            c_count desc;

    Q14

    EXPLAIN ANALYZE
    SELECT
            100.00 * sum(case
                    when p_type like 'PROMO%'
                            then l_extendedprice * (1 - l_discount)
                    else 0
            end) / sum(l_extendedprice * (1 - l_discount)) as promo_revenue
    FROM
            lineitem,
            part
    WHERE
            l_partkey = p_partkey
            and l_shipdate >= date '1995-02-01'
            and l_shipdate < date '1995-02-01' + interval '1 month'::interval;

    Q15

    EXPLAIN ANALYZE
    WITH revenue0 as (
        SELECT
        l_suppkey as supplier_no,
        sum(l_extendedprice * (1 - l_discount)) as total_revenue
        FROM
        lineitem
        WHERE
        l_shipdate >= date '1995-08-01'
        and l_shipdate < date '1995-08-01' + '3 month'::interval
        GROUP BY
        l_suppkey)
    SELECT
        s_suppkey,
        s_name,
        s_address,
        s_phone,
        total_revenue
    FROM
        supplier,
        revenue0
    WHERE
        s_suppkey = supplier_no
        and total_revenue = (
        SELECT
        max(total_revenue)
        FROM
        revenue0
        )
    ORDER BY
        s_suppkey;

    Q16

    EXPLAIN ANALYZE
    SELECT
            p_brand,
            p_type,
            p_size,
            count(distinct ps_suppkey) as supplier_cnt
    FROM
            partsupp,
            part
    WHERE
            p_partkey = ps_partkey
            and p_brand <> 'Brand#13'
            and p_type not like 'ECONOMY BRUSHED%'
            and p_size in (11, 8, 10, 31, 21, 13, 32, 28)
            and ps_suppkey not in (
                    SELECT
                            s_suppkey
                    FROM
                            supplier
                    WHERE
                            s_comment like '%Customer%Complaints%'
            )
    GROUP BY
            p_brand,
            p_type,
            p_size
    ORDER BY
            supplier_cnt desc,
            p_brand,
            p_type,
            p_size limit 100;

    Q17

    EXPLAIN ANALYZE
    SELECT
            sum(l_extendedprice) / 7.0 as avg_yearly
    FROM
            lineitem,
            part
    where
            p_partkey = l_partkey
            and p_brand = 'Brand#44'
            and p_container = 'MED PKG'
            and l_quantity < (
                    SELECT
                            0.2 * avg(l_quantity)
                    FROM
                            lineitem
                    WHERE
                            l_partkey = p_partkey
            );

    Q18

    EXPLAIN ANALYZE
    SELECT
            c_name,
            c_custkey,
            o_orderkey,
            o_orderdate,
            o_totalprice,
            sum(l_quantity)
    FROM
            customer,
            orders,
            lineitem
    WHERE
            o_orderkey in (
                    SELECT
                            l_orderkey
                    FROM
                            lineitem
                    GROUP BY
                            l_orderkey having
                                    sum(l_quantity) > 313
            )
            and c_custkey = o_custkey
            and o_orderkey = l_orderkey
    GROUP BY
            c_name,
            c_custkey,
            o_orderkey,
            o_orderdate,
            o_totalprice
    ORDER BY
            o_totalprice desc,
            o_orderdate limit 100;

    Q19

    EXPLAIN ANALYZE
    SELECT
            sum(l_extendedprice* (1 - l_discount)) as revenue
    FROM
            lineitem,
            part
    WHERE
            (
                    p_partkey = l_partkey
                    and p_brand = 'Brand#15'
                    and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
                    and l_quantity >= 10 and l_quantity <= 10 + 10
                    and p_size between 1 and 5
                    and l_shipmode in ('AIR', 'AIR REG')
                    and l_shipinstruct = 'DELIVER IN PERSON'
            )
            or
            (
                    p_partkey = l_partkey
                    and p_brand = 'Brand#45'
                    and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
                    and l_quantity >= 18 and l_quantity <= 18 + 10
                    and p_size between 1 and 10
                    and l_shipmode in ('AIR', 'AIR REG')
                    and l_shipinstruct = 'DELIVER IN PERSON'
            )
            or
            (
                    p_partkey = l_partkey
                    and p_brand = 'Brand#21'
                    and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
                    and l_quantity >= 30 and l_quantity <= 30 + 10
                    and p_size between 1 and 15
                    and l_shipmode in ('AIR', 'AIR REG')
                    and l_shipinstruct = 'DELIVER IN PERSON'
            );

    Q20

    EXPLAIN ANALYZE
    SELECT
            s_name,
            s_address
    FROM
            supplier,
            nation
    WHERE
            s_suppkey in (
                    SELECT
                            ps_suppkey
                    FROM
                            partsupp
                    WHERE
                            ps_partkey in (
                                    SELECT
                                            p_partkey
                                    FROM
                                            part
                                    WHERE
                                            p_name like 'lemon%'
                            )
                            AND ps_availqty > (
                                    SELECT
                                            0.5 * sum(l_quantity)
                                    FROM
                                            lineitem
                                    WHERE
                                            l_partkey = ps_partkey
                                            and l_suppkey = ps_suppkey
                                            and l_shipdate >= date '1997-01-01'
                                            and l_shipdate < date '1997-01-01' + '1 year'::interval
                            )
            )
            and s_nationkey = n_nationkey
            and n_name = 'INDONESIA'
    ORDER BY
            s_name limit 100;

    Q21

    EXPLAIN ANALYZE
    SELECT
            s_name,
            count(*) as numwait
    FROM
            supplier,
            lineitem l1,
            orders,
            nation
    WHERE
            s_suppkey = l1.l_suppkey
            and o_orderkey = l1.l_orderkey
            and o_orderstatus = 'F'
            and l1.l_receiptdate > l1.l_commitdate
            and exists (
                    SELECT
                            *
                    FROM
                            lineitem l2
                    WHERE
                            l2.l_orderkey = l1.l_orderkey
                            and l2.l_suppkey <> l1.l_suppkey
            )
            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
            )
            and s_nationkey = n_nationkey
            and n_name = 'INDIA'
    GROUP BY
            s_name
    ORDER BY
            numwait desc,
            s_name limit 100;

    Q22

    EXPLAIN ANALYZE
    SELECT
            cntrycode,
            count(*) as numcust,
            sum(c_acctbal) as totacctbal
    FROM
            (
                    SELECT
                            substring(c_phone from 1 for 2) as cntrycode,
                            c_acctbal
                    FROM
                            customer
                    WHERE
                            substring(c_phone from 1 for 2) in
                                    ('16', '17', '24', '21', '19', '22', '15')
                            and c_acctbal > (
                                    SELECT
                                            avg(c_acctbal)
                                    FROM
                                            customer
                                    WHERE
                                            c_acctbal > 0.00
                                            and substring(c_phone from 1 for 2) in
                                                    ('16', '17', '24', '21', '19', '22', '15')
                            )
                            and not exists (
                                    SELECT
                                            *
                                    FROM
                                            orders
                                    WHERE
                                            o_custkey = c_custkey
                            )
            ) as custsale
    GROUP BY
            cntrycode
    ORDER BY
            cntrycode;

Test results

Columnstore index creation time

Test conclusion: the columnstore indexes of the eight tables are created in a single-threaded serial manner, and the total time consumption is 39 minutes. This value is the total of all the eight tables. The data volumes of the tables differ significantly (LINEITEM has 600,037,902 rows and REGION has 5 rows). Therefore, the per-table time consumption cannot be extrapolated proportionally based on the number of tables.

Columnstore index disk space

Test conclusion:

  • The PostgreSQL row store (Heap tables) occupies 126 GB.

  • Columnstore index disk space:

    • If the primary key is not included (polar_csi.enable_pk=false), the total disk space is 25 GB, which is 20% of the PostgreSQL row store Heap tables. This mode is suitable for building columnstore indexes on static data.

    • If the primary key is included (polar_csi.enable_pk=true), the total disk space is 53 GB, which is 42% of the PostgreSQL row store Heap tables. This mode is suitable for columnstore indexes on dynamic data.

    Table

    Row count

    PostgreSQL row store

    Columnstore index (without primary key)

    Columnstore index (with primary key)

    LINEITEM

    600,037,902

    86 GB

    17 GB

    36 GB

    ORDERS

    150,000,000

    20 GB

    4406 MB

    9052 MB

    PARTSUPP

    80,000,000

    13 GB

    3452 MB

    6689 MB

    PART

    20,000,000

    3204 MB

    487 MB

    634 MB

    CUSTOMER

    15,000,000

    2808 MB

    992 MB

    1108 MB

    SUPPLIER

    1,000,000

    176 MB

    63 MB

    72 MB

    NATION

    25

    8 KB

    528 KB

    528 KB

    REGION

    5

    8 KB

    528 KB

    528 KB

    Total

    866,037,932

    126 GB

    25 GB

    53 GB

    The itemized values in the table retain the original units of the test output (GB, MB, and KB) and are rounded. The totals are calculated based on the unrounded original values. Therefore, the sum of the itemized values may differ from the total.

Query performance

The unit is seconds. The speedup is calculated by dividing the execution time of the PostgreSQL row store with default parameters by that of the columnstore indexes. A value greater than 1 indicates that the columnstore indexes are faster. Three queries (Q9, Q17, and Q20) time out on the row store and are uniformly counted as 500 seconds in the total execution time. Therefore, the row store execution times of these three queries, the corresponding speedups, and the values in the total row are lower bounds, which are marked with ≥ in the table.

  • The parameter settings compared between the two sides are as follows:

    • Columnstore index side: polar_csi.max_parallel_workers is set to 32 (corresponding to the 32 threads in the table header), and polar_csi.enable_query=ON and polar_csi.cost_threshold=0 are set in the session.

    • PostgreSQL row store side: default parameters, which means that no database parameters are adjusted. The actual value of each parameter is subject to the product default.

  • Test conclusion:

    • Total execution time of the columnstore indexes: 14.784 seconds

    • Total execution time of the PostgreSQL row store with default parameters: ≥2006.269 seconds

    • Speedup calculated based on the total execution time: ≥135.7x

    Query

    Columnstore index (32 threads)

    PostgreSQL row store (default parameters)

    Speedup

    Q1

    0.863

    35.638

    41.30

    Q2

    0.162

    27.512

    169.83

    Q3

    0.544

    34.368

    63.18

    Q4

    0.432

    3.084

    7.14

    Q5

    0.617

    36.919

    59.84

    Q6

    0.144

    4.191

    29.10

    Q7

    0.429

    10.061

    23.45

    Q8

    0.420

    9.587

    22.83

    Q9

    1.883

    ≥500

    ≥265.53

    Q10

    0.833

    33.632

    40.37

    Q11

    0.183

    3.980

    21.75

    Q12

    0.486

    6.395

    13.16

    Q13

    1.429

    136.754

    95.70

    Q14

    0.393

    6.452

    16.42

    Q15

    0.808

    9.364

    11.59

    Q16

    0.318

    23.039

    72.45

    Q17

    0.483

    ≥500

    ≥1035.19

    Q18

    1.267

    98.083

    77.41

    Q19

    0.579

    7.447

    12.86

    Q20

    0.428

    ≥500

    ≥1168.22

    Q21

    1.723

    13.109

    7.61

    Q22

    0.360

    6.654

    18.48

    Total

    14.784

    ≥2006.269

    ≥135.7

    The speedups of the 22 queries span two orders of magnitude, and the benefit is directly related to the magnitude of the row store execution time. The eight queries whose row store execution time exceeds 23 seconds (Q1, Q2, Q3, Q5, Q10, Q13, Q16, and Q18) achieve speedups of more than 40x, and Q9, Q17, and Q20 time out on the row store. The 11 queries whose row store execution time is less than 14 seconds achieve speedups between 7.14x and 29.10x. Analytical queries that scan large volumes of data and involve large-scale joins and aggregations benefit the most, whereas queries that the row store can return in about ten seconds benefit relatively less. To evaluate the benefit for your business, check which of the preceding ranges the row store execution time of your business queries falls into.

    performance-01-YdbNAA87

Follow-up steps

After the test, the cluster retains 100 GB of TPC-H test data (the PostgreSQL row store occupies 126 GB) and up to 53 GB of columnstore indexes, and the ECS instance retains the .tbl data files generated by dbgen. These data continuously occupy storage space and incur fees. Clean up the data as needed:

  • Delete the TPC-H data tables and columnstore indexes from the test database tpchdb to release the storage space occupied by the row store data and the columnstore indexes.

  • In the dbgen directory on the ECS instance, delete the .tbl files to release disk space.