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    PolarDB:Performance metrics

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    PolarDB:Performance metrics

    Last Updated:Sep 17, 2025

    The In-Memory Column Index (IMCI) significantly accelerates complex SQL query operations. It can improve query performance by more than 50 times compared to the row store engine. This topic uses data tables and SQL statements from the TPC-H benchmark to demonstrate the advantages of IMCI.

    Note

    The TPC-H performance test described in this topic is implemented based on the TPC-H benchmark test but cannot meet all requirements of the TPC-H benchmark test. Therefore, the test results cannot be compared with the published results of the TPC-H benchmark test.

    Test description

    TPC-H is a commonly used performance benchmark developed and released by the Transaction Processing Performance Council (TPC) to evaluate the analytical capabilities of databases. The dataset for this IMCI query test includes 8 data tables. The test executes 22 complex SQL queries that involve operations such as single-table statistics, multi-table joins, subqueries, aggregations, and sorting.

    • Test data size: 100 GB.

    • Test environment:

      • ECS:

        • Instance type: 16-core 32 GB (ecs.c5.4xlarge), with more than 150 GB of attached disk space.

        • Image: Alibaba Cloud Linux 3.2104 LTS 64-bit.

      • PolarDB for PostgreSQL cluster:

        • Database engine: PostgreSQL 14, with minor engine version 14.10.20.0 or later.

        • Edition: Enterprise Edition.

        • Series: Dedicated.

        • Specifications: 32-core 256 GB.

      Note

      Make sure that the ECS instance and the PolarDB cluster are in the same virtual private cloud (VPC).

    Data preparation

    1. On the PolarDB for PostgreSQL cluster, create a privileged account and create the test database tpchdb.

    2. Log on to the ECS instance and prepare the test data.

      1. Download the TPC-H tool dbgen.tar.gz, upload it to the ECS instance, and then decompress and compile it.

        --- Decompress the package
tar -zxvf dbgen.tar.gz
--- Compile the code
cd ./dbgen
make -f makefile.suite

      2. Use the TPC-H tool to generate 100 GB of test data. This operation takes about 30 minutes.

        --- Change the directory to dbgen
./dbgen -s 100 -f

    3. On the ECS instance, use the database connection tool provided by PolarDB (PolarDB-Tools) to connect to your cluster and import the test data into the tpchdb test database.

      1. Confirm that you are in the dbgen directory. The expected output is /<installation_path>/dbgen.

        --- Confirm the current directory
pwd

      2. Use PolarDB-Tools to connect to the cluster from the command line.

        /u01/polardb_pg_tools/bin/psql  -h <cluster_endpoint> -p <port_for_cluster_endpoint> -U <privileged_account> -d tpchdb

      3. 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 '';

    Enable and create the columnstore index

    1. Based on the version of your PolarDB for PostgreSQL cluster, enable the IMCI feature.

    2. Create an IMCI for the 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. Set the IMCI-related parameters for subsequent queries. For more information about the parameters, see Parameters.

      SET polar_csi.enable_pk TO ON;
SET polar_csi.enable_query TO ON;
SET polar_csi.exec_parallel TO 32;
SET polar_csi.cost_threshold TO 0;
SET polar_csi.memory_limit TO 65536;

    Execute SQL queries

    In your PolarDB for PostgreSQL cluster, execute the 22 complex SQL queries and record their execution times.

    1. You can use \timing to record the total execution time of an SQL statement.

      \timing

    2. Execute the following SQL statements in order.

      Query

      SQL

      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;
--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'
        );
--LIMIT -1

      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;
--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;
--LIMIT -1

    Test results

    Time consumed to create the columnstore index

    Conclusion: Single-threaded serial creation takes a total of 39 minutes.

    Storage space occupied by the columnstore index

    Conclusion:

    • The heap table in the row store engine uses 126 GB of storage space.

    • Columnstore index space usage:

      • If the primary key is not included (that is, polar_csi.enable_pk=false), the IMCI uses a total of 25 GB of storage space, which is 20% of the storage space used by the heap table in the row store engine. This mode is suitable for creating an IMCI for static data.

      • If the primary key is included (that is, polar_csi.enable_pk=true), the IMCI uses a total of 53 GB of storage space, which is 42% of the storage space used by the heap table in the row store engine. This mode is suitable for creating an IMCI for dynamic data.

      Table name

      Number of rows in the table

      PostgreSQL row store

      Columnstore index (excluding primary key)

      IMCI (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

    Query performance

    Conclusion:

    • Total execution time with IMCI: 23.92 seconds.

    • Total execution time with the row store engine: 2363.7 seconds (Q15 timed out and is calculated as 500 seconds).

    In conclusion, IMCI performs nearly 100 times faster than the row store engine.

    Query

    Time consumed by IMCI (seconds)

    Time consumed by PostgreSQL row store engine (seconds)

    Speedup ratio (times)

    Q1

    0.98

    41.629

    42.48

    Q2

    0.23

    78.402

    340.88

    Q3

    0.88

    18.376

    20.88

    Q4

    0.78

    3.929

    5.04

    Q5

    0.89

    14.801

    16.63

    Q6

    0.27

    4.782

    17.71

    Q7

    0.86

    17.661

    20.54

    Q8

    0.71

    21.952

    30.92

    Q9

    3.77

    362.42

    96.13

    Q10

    1.41

    18.313

    12.99

    Q11

    0.15

    8.307

    55.38

    Q12

    0.61

    7.146

    11.71

    Q13

    2.31

    308.555

    133.57

    Q14

    0.67

    10.658

    15.91

    Q15

    0.44

    Timed out, calculated as 500

    1136.36

    Q16

    0.44

    71.062

    161.50

    Q17

    0.84

    288

    342.86

    Q18

    2.58

    473.446

    183.51

    Q19

    1.42

    0.416

    0.29

    Q20

    0.54

    83

    153.70

    Q21

    2.68

    17.387

    6.49

    Q22

    0.46

    13.458

    29.26

    Summary

    23.92

    2363.7

    98.82

    image.png