• GreenPlum简单性能测试与分析--续

    版权声明：本文由黄辉原创文章，转载请注明出处: 
    文章原文链接：https://www.qcloud.com/community/article/259

    来源：腾云阁 https://www.qcloud.com/community

    之前对GreenPlum与Mysql进行了TPC-H类的对比测试，发现同等资源配比条件下，GreenPlum的性能远好于Mysql，有部分原因是得益于GreenPlum本身采用了更高效的算法，比如说做多表join时，采用的是hash join方式。如果采用同样高效的算法，两者的性能又如何？由于GreenPlum是由PostgreSQL演变而来，完全采用了PostgreSQL的优化算法，这次，我们将GreenPlum与PostgreSQL进行对比测试，在同等资源配比条件下，查看GreenPlum（分布式PostgreSQL）和单机版PostgreSQL的性能表现。

    一.目的

    1. 比较在同等资源条件下具有分布式属性的GreenPlum与PostgreSQL在进行TPC-H类测试的性能区别。
    2. 分析和总结两种DB造成性能区别的原因。

    二.测试环境与配置信息

    测试环境：腾讯云
    测试对象：GreenPlum、PostgreSQL，两者的配置信息统计如下：

    表1 GreenPlum集群服务器

     Master HostSegment HostSegment Host
    操作系统 CentOS 6.7 64位 CentOS 6.7 64位 CentOS 6.7 64位
    CPU Intel(R) Xeon(R) CPU E5-26xx v3 2核 Intel(R) Xeon(R) CPU E5-26xx v3 2核 Intel(R) Xeon(R) CPU E5-26xx v3 2核
    内存 8GB 8GB 8GB
    公网带宽 100Mbps 100Mbps 100Mbps
    IP 123.207.228.40 123.207.228.21 123.207.85.105
    Segment数量 0 2 2
    版本 greenplum-db-4.3.8.1-build-1-RHEL5-x86_64 greenplum-db-4.3.8.1-build-1-RHEL5-x86_64 greenplum-db-4.3.8.1-build-1-RHEL5-x86_64

    表2 PostgreSQL服务器

    指标参数
    操作系统 CentOS 6.7 64位
    cpu Intel(R) Xeon(R) CPU E5-26xx v3 8核
    内存 24GB
    公网带宽 100Mbps
    IP 119.29.229.209
    版本 PostgreSQL 9.5.4

    三.测试结果与分析

    1.总测试数据量为1G时
    结果统计信息如下：

    表3 总量为1GB时各测试表数据量统计

    表名称数据条数
    customer 150000
    lineitem 6001215
    nation 25
    orders 1500000
    part 200000
    partsupp 800000
    region 5
    supplier 10000

    表4 总量为1GB时22条sql执行时间统计

    执行的sqlGeenPlum执行时间（单位：秒）PostgreSQL执行时间（单位：秒）
    Q1 4.01 12.93
    Q2 0.50 0.62
    Q3 1.35 1.29
    Q4 0.11 0.52
    Q5 0.19 0.72
    Q6 0.01 0.79
    Q7 6.06 1.84
    Q8 1.46 0.59
    Q9 4.00 7.04
    Q10 0.14 2.19
    Q11 0.30 0.18
    Q12 0.08 2.15
    Q13 1.04 4.05
    Q14 0.04 0.42
    Q15 0.07 1.66
    Q16 0.51 0.80
    Q17 3.21 23.07
    Q18 14.23 5.86
    Q19 0.95 0.17
    Q20 0.16 3.10
    Q21 7.23 2.22
    Q22 0.96 0.28

    分析：从以上的表4可以看出，PostgreSQL在22条sql中有8条sql的执行时间比GreenPlum少，接近一半的比例，我们直接放大10倍的测试数据量进行下一步测试。

    2.总测试数据量为10G时
    结果统计如下：

    表5 总量为10GB时各测试表数据量统计

    表名称数据条数
    customer 1500000
    lineitem 59986052
    nation 25
    orders 15000000
    part 2000000
    partsupp 8000000
    region 5
    supplier 100000

    表6 总量为10GB时22条sql执行时间统计

    执行的sqlGeenPlum执行时间（单位：秒）PostgreSQL执行时间（单位：秒）
    Q1 36.98 130.61
    Q2 3.10 17.08
    Q3 14.39 117.83
    Q4 0.11 6.81
    Q5 0.20 114.46
    Q6 0.01 11.08
    Q7 80.12 42.96
    Q8 6.61 45.13
    Q9 49.72 118.36
    Q10 0.16 40.51
    Q11 2.28 3.06
    Q12 0.08 21.47
    Q13 19.29 68.83
    Q14 0.05 36.28
    Q15 0.09 23.16
    Q16 6.30 12.77
    Q17 134.22 127.79
    Q18 168.03 199.48
    Q19 6.25 1.96
    Q20 0.54 52.10
    Q21 84.68 190.59
    Q22 17.93 2.98

    分析：放大数据量到10G后可以明显看出，PostgreSQL执行测试sql的时间大幅度增多，性能下降比较厉害，但仍有3条测试sql快于GreenPlum，我们选取其中一条对比查看下两者的性能区别原因。
    这里我们以Q7为例，Greenplum的执行时间大约是PostgreSQL的两倍，Q7如下：

    图1 Q7表示的sql语句

    在PostgreSQL上执行explain Q7，得到结果如下：

    图2 数据量为10G时PostgreSQL上执行explain Q7的结果

    对执行进行分析，可以看出，整个过程最耗时的部分如上图红色框部分标识,对应的条件查询操作分别是：
    1).在lineitem表上对l_shipdata字段按条件查询，因为在字段有索引，采用了高效的Bitmap索引查询（Bitmap索引查询分两步：1.建位图；2.扫表。详细了解可看http://kb.cnblogs.com/page/515258/ ）。
    2).lineitem和orders表hash join操作。
    为了方便进一步分析，我们加上analyze参数，获取详细的执行时间，由于内容过多，这里只截取部分重要信息如下：

    图3 数据量为10G时PostgreSQL上执行explain analyze Q7的部分结果

    根据以上信息，我们可以得出这两部分操作的具体执行时间，但由于PostgreSQL采取多任务并行，因此，我们需要对每步操作计算出一个滞留时间（该时间段内系统只执行该步操作），缩短滞留时间可直接提升执行速度，每步的滞留时间为前步的结束时间与该步结束时间之差。两部分的滞留时间分别为：

    1).Bitmap Heap Scan:20197-2233=17964ms
    2).Hash join:42889-26200=16689ms

    PostgreSQL执行Q7的总时间为42963ms，因此，可以印证系统的耗时主要集中在上述两步操作上。
    接下来，我们在GreenPlum上执行explain Q7，结果如下：


    图4 数据量为10G时GreenPlum上执行explain Q7的结果

    与PostgreSQL不同的是，GreenPlum的耗时多了数据重分布部分。同样，我们通过analyze参数得到详细的执行时间如下：

    图5 数据量为10G时GreenPlum上执行explain analyze Q7的部分结果

    根据执行计划信息，选出耗时最长的三步操作，计算出在一个segment（耗时最长的）上这三部分的滞留时间为：
    1).Scan lineitem: 6216ms
    2).Redistribute: 36273ms
    3).Hash join: 29885ms

    GreenPlum执行Q7的总时间为80121ms，可见数据重分布的时间占据了整个执行时间的一半，进行Hash join操作的时间占比也较多，主要是segment的内存不足，引起了磁盘的IO。

    小结：对比PostgreSQL和GreenPlum在Q7的执行计划，GreenPlum的耗时较多的原因主要是数据重分布的大量时间消耗和hash join时超出内存引起磁盘IO。虽然GreenPlum各segment并行扫lineitem表节省了时间，但占比较小，对总时间的消耗影响较小。

    基于此，是否可以减少数据重分布操作的耗时占比？我们尝试进一步增加测试的数据量，比较10G的测试数据对于真实的OLAP场景还是过少，扩大5倍的测试量，继续查看耗时情况是否有所改变。

    3. 总测试数据量为50G时
    表7 总量为50GB时各测试表数据量统计

    表名称数据条数
    customer 7500000
    lineitem 300005811
    nation 25
    orders 75000000
    part 10000000
    partsupp 40000000
    region 5
    supplier 500000

    表8 总量为50GB时22条sql执行时间统计

    执行的sqlGeenPlum执行时间（单位：秒）PostgreSQL执行时间（单位：秒）
    Q1 212.27 802.24
    Q2 16.53 164.20
    Q3 156.31 2142.18
    Q4 0.13 2934.76
    Q5 0.23 2322.92
    Q6 0.01 6439.26
    Q7 535.66 11906.74
    Q8 76.76 9171.83
    Q9 313.91 >26060.36
    Q10 0.41 1905.13
    Q11 7.71 17.65
    Q12 0.19 >3948.07
    Q13 108.05 354.59
    Q14 0.05 8054.72
    Q15 0.07 >2036.03
    Q16 34.74 221.49
    Q17 862.90 >9010.56
    Q18 913.97 3174.24
    Q19 129.14 8666.38
    Q20 2.28 9389.21
    Q21 1064.67 >26868.31
    Q22 90.90 1066.44

    分析：从结果表可明显看出，在22条SQL中，GreenPlum的执行效率都比PostgreSQL高出很多，我们还是以Q7为例，查看两种数据量下执行效率不一致的直接原因。

    经过对执行计划的分析，发现区别还是集中在步骤2提到的几个部分，这里就不再重复给出整体的查询计划，直接查看耗时较多的部分如下：


    图6 数据量为50G时PostgreSQL上执行explain analyze Q7的部分结果

    图7 数据量为50G时GreenPlum上执行explain analyze Q7的部分结果

    PostgreSQL的主要滞留时间有：
    1).Bitmap Heap Scan: 9290197ms
    2).Hash join: 713138ms

    总执行时间为10219009ms，可见主要的耗时集中在Bitmap Heap Scan上，
    GreenPlum的主要滞留时间有：
    1).Scan lineitem: 130397ms
    2).Redistribute: 140685ms
    3).Hash join: 211456ms

    总的执行时间为537134ms，相比步骤2的10G测试数据量，数据重分布的耗时占比明显下降，主要耗时已集中在hash join操作上。

    GreenPlum和PostgreSQL在执行同样的wheret条件时，扫表的方式不一样，原因在于GreenPlum里的lineitem表为列存储，直接扫表更方便更快。

    对比PostgreSQL两次的测试结果，发现Bitmao Heap Scan操作的性能下降比较明显，第一次扫18188314 行用时17秒，而第二次扫90522811行用时9190秒。

    小结：增大数据量，会减少数据重分布耗时对整体执行时间的影响比重，主要耗时集中在内部数据的计算上。由于扫表涉及到磁盘IO，GreenPlum将扫表任务分割给多个segment同时进行，减少了单个节点要执行的扫表量，相当于并行IO操作，对整体的性能提升较大。

    四.总结

    通过对不同数据量（1G，10G，50G）的测试对比以及分析，可以看出，在TPC-H类的测试时，数据量越大，GreenPlum性能越好于单机版的PostgreSQL。由于GreenPlum采用分布式架构，为了实现各节点并行计算能力，需要在节点间进行广播或者数据重分布，对整体的性能有一定影响，当数据量较小时，计算量小，广播或者重分布耗时占总耗时比例大，影响整体的执行效率，可能会出现GreenPlum不如单机版PostgreSQL效率高；当数据量较大时，整体计算的量很大，广播或者重分布耗时不再是影响性能的关键因素，分布式属性的GreenPlum在关于复杂语句执行查询效率较高，原因在于，一是多节点同时进行计算（hash join、sort等），提升计算速度，且可以充分利用系统CPU资源；二是扫表时，将任务分派到多节点，减少了单个节点的IO次数，达到并行IO的目的，更适用于OLAP场景。

    五.其他事项

    1. 由于原生的TPC-H的测试用例不直接支持GreenPlum和PostgreSQL，因此需要修改测试脚本，生成新的建表语句如《附录一》所示，测试sql如《附录二》。

    2. GreenPlum的数据导入可以使用GreenPlum自带的gpfdist工具，搭建多个gpfdsit文件服务器并行导入，但文件服务器的数量不能多于segment数量，这点官方文档并未说明。

    附录一：建表语句

    GreenPlum：
BEGIN;
        CREATE TABLE PART (
                P_PARTKEY               SERIAL8,
                P_NAME                  VARCHAR(55),
                P_MFGR                  CHAR(25),
                P_BRAND                 CHAR(10),
                P_TYPE                  VARCHAR(25),
                P_SIZE                  INTEGER,
                P_CONTAINER             CHAR(10),
                P_RETAILPRICE   DECIMAL,
                P_COMMENT               VARCHAR(23)
        ) with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (p_partkey);

        COPY part FROM '/tmp/dss-data/part.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE REGION (
                R_REGIONKEY     SERIAL8,
                R_NAME          CHAR(25),
                R_COMMENT       VARCHAR(152)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (r_regionkey);

        COPY region FROM '/tmp/dss-data/region.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE NATION (
                N_NATIONKEY             SERIAL8,
                N_NAME                  CHAR(25),
                N_REGIONKEY             BIGINT NOT NULL,  -- references R_REGIONKEY
                N_COMMENT               VARCHAR(152)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (n_nationkey);

        COPY nation FROM '/tmp/dss-data/nation.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE SUPPLIER (
                S_SUPPKEY               SERIAL8,
                S_NAME                  CHAR(25),
                S_ADDRESS               VARCHAR(40),
                S_NATIONKEY             BIGINT NOT NULL, -- references N_NATIONKEY
                S_PHONE                 CHAR(15),
                S_ACCTBAL               DECIMAL,
                S_COMMENT               VARCHAR(101)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (s_suppkey);

        COPY supplier FROM '/tmp/dss-data/supplier.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE CUSTOMER (
                C_CUSTKEY               SERIAL8,
                C_NAME                  VARCHAR(25),
                C_ADDRESS               VARCHAR(40),
                C_NATIONKEY             BIGINT NOT NULL, -- references N_NATIONKEY
                C_PHONE                 CHAR(15),
                C_ACCTBAL               DECIMAL,
                C_MKTSEGMENT    CHAR(10),
                C_COMMENT               VARCHAR(117)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (c_custkey);

        COPY customer FROM '/tmp/dss-data/customer.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE PARTSUPP (
                PS_PARTKEY              BIGINT NOT NULL, -- references P_PARTKEY
                PS_SUPPKEY              BIGINT NOT NULL, -- references S_SUPPKEY
                PS_AVAILQTY             INTEGER,
                PS_SUPPLYCOST   DECIMAL,
                PS_COMMENT              VARCHAR(199)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (ps_partkey,ps_suppkey);

        COPY partsupp FROM '/tmp/dss-data/partsupp.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE ORDERS (
                O_ORDERKEY              SERIAL8,
                O_CUSTKEY               BIGINT NOT NULL, -- references C_CUSTKEY
                O_ORDERSTATUS   CHAR(1),
                O_TOTALPRICE    DECIMAL,
                O_ORDERDATE             DATE,
                O_ORDERPRIORITY CHAR(15),
                O_CLERK                 CHAR(15),
                O_SHIPPRIORITY  INTEGER,
                O_COMMENT               VARCHAR(79)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (o_orderkey);

        COPY orders FROM '/tmp/dss-data/orders.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE LINEITEM (
                L_ORDERKEY              BIGINT NOT NULL, -- references O_ORDERKEY
                L_PARTKEY               BIGINT NOT NULL, -- references P_PARTKEY (compound fk to PARTSUPP)
                L_SUPPKEY               BIGINT NOT NULL, -- references S_SUPPKEY (compound fk to PARTSUPP)
                L_LINENUMBER    INTEGER,
                L_QUANTITY              DECIMAL,
                L_EXTENDEDPRICE DECIMAL,
                L_DISCOUNT              DECIMAL,
                L_TAX                   DECIMAL,
                L_RETURNFLAG    CHAR(1),
                L_LINESTATUS    CHAR(1),
                L_SHIPDATE              DATE,
                L_COMMITDATE    DATE,
                L_RECEIPTDATE   DATE,
                L_SHIPINSTRUCT  CHAR(25),
                L_SHIPMODE              CHAR(10),
                L_COMMENT               VARCHAR(44)
        )  with (APPENDONLY=true,BLOCKSIZE=2097152,ORIENTATION=COLUMN,CHECKSUM=true,OIDS=false) DISTRIBUTED BY (l_orderkey, l_linenumber);

        COPY lineitem FROM '/tmp/dss-data/lineitem.csv' WITH csv DELIMITER '|';
COMMIT;

PostgreSQL:
BEGIN;

        CREATE TABLE PART (

                P_PARTKEY               SERIAL,
                P_NAME                  VARCHAR(55),
                P_MFGR                  CHAR(25),
                P_BRAND                 CHAR(10),
                P_TYPE                  VARCHAR(25),
                P_SIZE                  INTEGER,
                P_CONTAINER             CHAR(10),
                P_RETAILPRICE   DECIMAL,
                P_COMMENT               VARCHAR(23)
        );

        COPY part FROM '/tmp/dss-data-copy/part.csv' WITH csv DELIMITER '|';

COMMIT;

BEGIN;

        CREATE TABLE REGION (
                R_REGIONKEY     SERIAL,
                R_NAME          CHAR(25),
                R_COMMENT       VARCHAR(152)
        );

        COPY region FROM '/tmp/dss-data-copy/region.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

BEGIN;

        CREATE TABLE NATION (
                N_NATIONKEY             SERIAL,
                N_NAME                  CHAR(25),
                N_REGIONKEY             BIGINT NOT NULL,  -- references R_REGIONKEY
                N_COMMENT               VARCHAR(152)
        );

        COPY nation FROM '/tmp/dss-data-copy/nation.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

BEGIN;

        CREATE TABLE SUPPLIER (
                S_SUPPKEY               SERIAL,
                S_NAME                  CHAR(25),
                S_ADDRESS               VARCHAR(40),
                S_NATIONKEY             BIGINT NOT NULL, -- references N_NATIONKEY
                S_PHONE                 CHAR(15),
                S_ACCTBAL               DECIMAL,
                S_COMMENT               VARCHAR(101)
        );

        COPY supplier FROM '/tmp/dss-data-copy/supplier.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

BEGIN;

        CREATE TABLE CUSTOMER (
                C_CUSTKEY               SERIAL,
                C_NAME                  VARCHAR(25),
                C_ADDRESS               VARCHAR(40),
                C_NATIONKEY             BIGINT NOT NULL, -- references N_NATIONKEY
                C_PHONE                 CHAR(15),
                C_ACCTBAL               DECIMAL,
                C_MKTSEGMENT    CHAR(10),
                C_COMMENT               VARCHAR(117)
        );

        COPY customer FROM '/tmp/dss-data-copy/customer.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

BEGIN;

        CREATE TABLE PARTSUPP (
                PS_PARTKEY              BIGINT NOT NULL, -- references P_PARTKEY
                PS_SUPPKEY              BIGINT NOT NULL, -- references S_SUPPKEY
                PS_AVAILQTY             INTEGER,
                PS_SUPPLYCOST   DECIMAL,
                PS_COMMENT              VARCHAR(199)
        );

        COPY partsupp FROM '/tmp/dss-data-copy/partsupp.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

BEGIN;

        CREATE TABLE ORDERS (
                O_ORDERKEY              SERIAL,
                O_CUSTKEY               BIGINT NOT NULL, -- references C_CUSTKEY
                O_ORDERSTATUS   CHAR(1),
                O_TOTALPRICE    DECIMAL,
                O_ORDERDATE             DATE,
                O_ORDERPRIORITY CHAR(15),
                O_CLERK                 CHAR(15),
                O_SHIPPRIORITY  INTEGER,
                O_COMMENT               VARCHAR(79)
        );

        COPY orders FROM '/tmp/dss-data-copy/orders.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

BEGIN;

        CREATE TABLE LINEITEM (
                L_ORDERKEY              BIGINT NOT NULL, -- references O_ORDERKEY
                L_PARTKEY               BIGINT NOT NULL, -- references P_PARTKEY (compound fk to PARTSUPP)
                L_SUPPKEY               BIGINT NOT NULL, -- references S_SUPPKEY (compound fk to PARTSUPP)
                L_LINENUMBER    INTEGER,
                L_QUANTITY              DECIMAL,
                L_EXTENDEDPRICE DECIMAL,
                L_DISCOUNT              DECIMAL,
                L_TAX                   DECIMAL,
                L_RETURNFLAG    CHAR(1),
                L_LINESTATUS    CHAR(1),
                L_SHIPDATE              DATE,
                L_COMMITDATE    DATE,
                L_RECEIPTDATE   DATE,
                L_SHIPINSTRUCT  CHAR(25),
                L_SHIPMODE              CHAR(10),
                L_COMMENT               VARCHAR(44)
        );

        COPY lineitem FROM '/tmp/dss-data-copy/lineitem.csv' WITH (FORMAT csv, DELIMITER '|');

COMMIT;

    附录二：查询语句

    Q1:
-- using 1471398061 as a seed to the RNG
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' - interval '85' day
group by
        l_returnflag,
        l_linestatus
order by
        l_returnflag,
        l_linestatus
LIMIT 1;

Q2:
-- using 1471398061 as a seed to the RNG


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 = 48
        and p_type like '%STEEL'
        and s_nationkey = n_nationkey
        and n_regionkey = r_regionkey
        and r_name = 'AFRICA'
        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 = 'AFRICA'
        )
order by
        s_acctbal desc,
        n_name,
        s_name,
        p_partkey
LIMIT 100;

Q3:
-- using 1471398061 as a seed to the RNG


select
        l_orderkey,
        sum(l_extendedprice * (1 - l_discount)) as revenue,
        o_orderdate,
        o_shippriority
from
        customer,
        orders,
        lineitem
where
        c_mktsegment = 'HOUSEHOLD'
        and c_custkey = o_custkey
        and l_orderkey = o_orderkey
        and o_orderdate < date '1995-03-03'
        and l_shipdate > date '1995-03-03'
group by
        l_orderkey,
        o_orderdate,
        o_shippriority
order by
        revenue desc,
        o_orderdate
LIMIT 10;

Q4:
-- using 1471398061 as a seed to the RNG

select
        o_orderpriority,
        count(*) as order_count
from
        orders
where
        o_orderdate >= date '1993-06-01'
        and o_orderdate < date '1993-06-01' + interval '3' month
        and exists (
                select
                        *
                from
                        lineitem
                where
                        l_orderkey = o_orderkey
                        and l_commitdate < l_receiptdate
        )
group by
        o_orderpriority
order by
        o_orderpriority
LIMIT 1;

Q5:
-- using 1471398061 as a seed to the RNG


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 = 'AMERICA'
        and o_orderdate >= date '1993-01-01'
        and o_orderdate < date '1993-01-01' + interval '1' year
group by
        n_name
order by
        revenue desc
LIMIT 1;

Q6:
-- using 1471398061 as a seed to the RNG


select
        sum(l_extendedprice * l_discount) as revenue
from
        lineitem
where
        l_shipdate >= date '1993-01-01'
        and l_shipdate < date '1993-01-01' + interval '1' year
        and l_discount between 0.02 - 0.01 and 0.02 + 0.01
        and l_quantity < 24
LIMIT 1;

Q7:
-- using 1471398061 as a seed to the RNG


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 = 'BRAZIL' and n2.n_name = 'INDONESIA')
                                or (n1.n_name = 'INDONESIA' and n2.n_name = 'BRAZIL')
                        )
                        and l_shipdate between date '1995-01-01' and date '1996-12-31'
        ) as shipping
group by
        supp_nation,
        cust_nation,
        l_year
order by
        supp_nation,
        cust_nation,
        l_year
LIMIT 1;

Q8:
-- using 1471398061 as a seed to the RNG


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 date '1995-01-01' and date '1996-12-31'
                        and p_type = 'ECONOMY BURNISHED BRASS'
        ) as all_nations
group by
        o_year
order by
        o_year
LIMIT 1;

Q9:
-- using 1471398061 as a seed to the RNG


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 '%powder%'
        ) as profit
group by
        nation,
        o_year
order by
        nation,
        o_year desc
LIMIT 1;-- using 1471398061 as a seed to the RNG

Q10
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 '1993-06-01'
        and o_orderdate < date '1993-06-01' + interval '3' month
        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
-- using 1471398061 as a seed to the RNG


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 = 'PERU'
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 = 'PERU'
                )
order by
        value desc
LIMIT 1;-- using 1471398061 as a seed to the RNG

Q12
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 ('REG AIR', 'RAIL')
        and l_commitdate < l_receiptdate
        and l_shipdate < l_commitdate
        and l_receiptdate >= date '1993-01-01'
        and l_receiptdate < date '1993-01-01' + interval '1' year
group by
        l_shipmode
order by
        l_shipmode
LIMIT 1;-- using 1471398061 as a seed to the RNG

Q13
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%packages%'
                group by
                        c_custkey
        ) as c_orders (c_custkey, c_count)
group by
        c_count
order by
        custdist desc,
        c_count desc

Q14
LIMIT 1;-- using 1471398061 as a seed to the RNG


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 '1993-09-01'
        and l_shipdate < date '1993-09-01' + interval '1' month
LIMIT 1;

Q15
-- using 1471398061 as a seed to the RNG

create view revenue0 (supplier_no, total_revenue) as
        select
                l_suppkey,
                sum(l_extendedprice * (1 - l_discount))
        from
                lineitem
        where
                l_shipdate >= date '1994-11-01'
                and l_shipdate < date '1994-11-01' + interval '3' month
        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
LIMIT 1;

Q16
drop view revenue0;-- using 1471398061 as a seed to the RNG


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#22'
        and p_type not like 'STANDARD PLATED%'
        and p_size in (34, 17, 18, 16, 15, 49, 1, 48)
        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 1;

Q17:
-- using 1471398061 as a seed to the RNG
select
        sum(l_extendedprice) / 7.0 as avg_yearly
from
        lineitem,
        part,
        (SELECT l_partkey AS agg_partkey, 0.2 * avg(l_quantity) AS avg_quantity FROM lineitem GROUP BY l_partkey) part_agg
where
        p_partkey = l_partkey
        and agg_partkey = l_partkey
        and p_brand = 'Brand#21'
        and p_container = 'JUMBO JAR'
        and l_quantity < avg_quantity
LIMIT 1;

Q18
-- using 1471398061 as a seed to the RNG
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) > 312
        )
        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;-- using 1471398061 as a seed to the RNG

Q19
select
        sum(l_extendedprice* (1 - l_discount)) as revenue
from
        lineitem,
        part
where
        (
                p_partkey = l_partkey
                and p_brand = 'Brand#42'
                and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
                and l_quantity >= 7 and l_quantity <= 7 + 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#22'
                and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
                and l_quantity >= 20 and l_quantity <= 20 + 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#25'
                and p_container in ('LG CASE', 'LG BOX', 'LG PACK', 'LG PKG')
                and l_quantity >= 21 and l_quantity <= 21 + 10
                and p_size between 1 and 15
                and l_shipmode in ('AIR', 'AIR REG')
                and l_shipinstruct = 'DELIVER IN PERSON'
        )
LIMIT 1;

Q20
-- using 1471398061 as a seed to the RNG
select
        s_name,
        s_address
from
        supplier,
        nation
where
        s_suppkey in (
                select
                        ps_suppkey
                from
                        partsupp,
                        (
                                select
                                        l_partkey agg_partkey,
                                        l_suppkey agg_suppkey,
                                        0.5 * sum(l_quantity) AS agg_quantity
                                from
                                        lineitem
                                where
                                        l_shipdate >= date '1994-01-01'
                                        and l_shipdate < date '1994-01-01' + interval '1' year
                                group by
                                        l_partkey,
                                        l_suppkey
                        ) agg_lineitem
                where
                        agg_partkey = ps_partkey
                        and agg_suppkey = ps_suppkey
                        and ps_partkey in (
                                select
                                        p_partkey
                                from
                                        part
                                where
                                        p_name like 'forest%'
                        )
                        and ps_availqty > agg_quantity
        )
        and s_nationkey = n_nationkey
        and n_name = 'FRANCE'
order by
        s_name
LIMIT 1;

Q21
-- using 1471398061 as a seed to the RNG
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 = 'GERMANY'
group by
        s_name
order by
        numwait desc,
        s_name
LIMIT 100;
Q22
-- using 1471398061 as a seed to the RNG
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', '10', '34', '26', '33', '18', '11')
                        and c_acctbal > (
                                select
                                        avg(c_acctbal)
                                from
                                        customer
                                where
                                        c_acctbal > 0.00
                                        and substring(c_phone from 1 for 2) in
                                                ('16', '10', '34', '26', '33', '18', '11')
                        )
                        and not exists (
                                select
                                        *
                                from
                                        orders
                                where
                                        o_custkey = c_custkey
                        )
        ) as custsale
group by
        cntrycode
order by
        cntrycode
LIMIT 1;
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  • 原文地址：https://www.cnblogs.com/purpleraintear/p/6165610.html
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