测试方案介绍

TPC-H简介

以下文字描述引用自TPC Benchmark™ H (TPC-H)规范：

TPC-H是一个决策支持基准，由一套面向业务的临时查询和并发数据修改组成。选择的查询和填充数据库的数据具有广泛的行业相关性。该基准测试说明了决策支持系统可以检查大量数据，执行高度复杂的查询，并解答关键的业务问题。

详情请参见TPCH Specification。

数据集简介

TPC-H（商业智能计算测试）是美国交易处理效能委员会（TPC,Transaction Processing Performance Council）组织制定的用来模拟决策支持类应用的一个测试集。目前在学术界和工业界普遍采用它来评价决策支持技术方面应用的性能。

TPC-H是根据真实的生产运行环境来建模，模拟了一套销售系统的数据仓库。其共包含8张表，数据量可设定从1 GB~3 TB不等。其基准测试共包含了22个查询，主要评价指标各个查询的响应时间，即从提交查询到结果返回所需时间。其测试结果可综合反映系统处理查询时的能力。详情请参见TPC-H基准。

场景说明

注意事项

为了减少可能对测试结果有影响的变量，建议每次新建实例进行测试，请勿使用升或降配的实例。

准备工作

1. 基础环境准备：您需要准备OLAP查询场景所需的基础环境。

   1. 创建Hologres实例，详情请参见购买Hologres。本次测试环境使用了独享（按量付费）的实例，由于该实例仅用于测试使用，计算资源配置选择96核384GB。您可以根据实际业务需求，选择计算资源的规格。

   2. 创建ECS实例，详情请参见创建ECS实例。本文使用的ECS实例规格如下：

      参数	规格
      实例规格	ecs.g6.4xlarge
      镜像	Alibaba Cloud Linux 3.2104 LTS 64位
      数据盘	类型为ESSD云盘，具体数据容量需根据测试的数据量大小决定。

2. 配置工具包参数。

   1. 登录ECS实例，详情请参见连接ECS实例。

   2. 在ECS实例中执行以下命令。

      1. 安装PSQL客户端。

         yum update -y
         yum install postgresql-server -y
         yum install postgresql-contrib -y

      2. 下载Hologres Benchmark测试工具包并解压。

         wget https://oss-tpch.oss-cn-hangzhou.aliyuncs.com/hologres_benchmark_for_tpch.tar
         tar xvf hologres_benchmark_for_tpch.tar

OLAP查询场景测试

OLAP查询场景测试，您可直接使用准备工作中下载的Hologres Benchmark测试工具，进行全流程自动化TPC-H测试。

• 操作步骤

  在ECS实例中执行以下命令。

  1. 进入Hologres Benchmark目录。

     cd hologres_benchmark_for_tpch/benchmark

  2. 进行全流程自动化TPC-H测试。

     python tpch_1t_dbgen.py --psql "PGUSER=<AccessKey_ID> PGPASSWORD=<AccessKey_Secret> psql -h <Endpoint> -p <Port>" --init_and_run --scale_factor <Scale_Factor>

     说明

     考虑到全流程自动化TPC-H测试执行时间可能较长，推荐使用后台运行模式，命令如下：

     nohup python tpch_1t_dbgen.py --psql "PGUSER=<AccessKey_ID> PGPASSWORD=<AccessKey_Secret> psql -h <Endpoint> -p <Port>" --init_and_run --scale_factor 1000 &

• 参数说明

  参数	说明
  AccessKey_ID	当前阿里云账号的AccessKey ID。 您可以单击AccessKey 管理，获取AccessKey ID。
  AccessKey_Secret	当前阿里云账号的AccessKey Secret。 您可以单击AccessKey 管理，获取AccessKey Secret。
  Endpoint	Hologres实例的网络地址（Endpoint）。 您可以进入Hologres管理控制台的实例详情页，从网络信息区域获取网络地址。
  Port	Hologres实例的网络端口。 进入Hologres管理控制台的实例详情页获取网络端口。
  Scale_Factor	数据集的比例因子，控制生成数据量的大小，单位为GB。 例如，本文由于测试数据量为1 TB，因此该参数设置为1000即可。

• 使用说明

  在全流程自动化TPC-H测试过程中，Hologres Benchmark测试工具会自动在Hologres实例中完成如下工作：

  1. 创建名称为hologres_tpch的数据库。

  2. 生成用于测试的TPC-H数据。

  3. 创建表并导入数据。

  4. 执行TPC-H 22条SQL查询语句，详情请参见TPC-H 22条查询语句。

TPC-H性能测试成功后，您可以切换至hologres_benchmark_for_tpch/tpch_test_log目录下查看相关的测试结果（包含查询语句、执行计划以及执行时间等详细信息）。目录结构如下所示：

./
|-- analyze.sql.result
|-- benchmark_result # 最近一次TPC-H SQL 的执行计划和结果
|   |-- query10.sql.result
|   |-- query10.sql.resultdata
|   |-- query11.sql.result
|   |-- query11.sql.resultdata
|   |-- query12.sql.result
|   |-- query12.sql.resultdata
|   |-- query13.sql.result
|   |-- query13.sql.resultdata
|   |-- query14.sql.result
|   |-- query14.sql.resultdata
|   |-- query15.sql.result
|   |-- query15.sql.resultdata
|   |-- query16.sql.result
|   |-- query16.sql.resultdata
|   |-- query17.sql.result
|   |-- query17.sql.resultdata
|   |-- query18.sql.result
|   |-- query18.sql.resultdata
|   |-- query19.sql.result
|   |-- query19.sql.resultdata
|   |-- query1.sql.result
|   |-- query1.sql.resultdata
|   |-- query20.sql.result
|   |-- query20.sql.resultdata
|   |-- query21.sql.result
|   |-- query21.sql.resultdata
|   |-- query22.sql.result
|   |-- query22.sql.resultdata
|   |-- query2.sql.result
|   |-- query2.sql.resultdata
|   |-- query3.sql.result
|   |-- query3.sql.resultdata
|   |-- query4.sql.result
|   |-- query4.sql.resultdata
|   |-- query5.sql.result
|   |-- query5.sql.resultdata
|   |-- query6.sql.result
|   |-- query6.sql.resultdata
|   |-- query7.sql.result
|   |-- query7.sql.resultdata
|   |-- query8.sql.result
|   |-- query8.sql.resultdata
|   |-- query9.sql.result
|   `-- query9.sql.resultdata
|-- copy_dbgen.sql.result
|-- init_holo.sql.result
|-- init.sql.result
|-- online_config.result
|-- reset_config.result
|-- tmp # TPC-H涉及的22条SQL Query。
|   |-- query10.sql
|   |-- query11.sql
|   |-- query12.sql
|   |-- query13.sql
|   |-- query14.sql
|   |-- query15.sql
|   |-- query17.sql
|   |-- query18.sql
|   |-- query19.sql
|   |-- query1.sql
|   |-- query21.sql
|   |-- query22.sql
|   |-- query2.sql
|   |-- query3.sql
|   |-- query4.sql
|   |-- query5.sql
|   |-- query6.sql
|   |-- query7.sql
|   |-- query8.sql
|   `-- query9.sql
|-- tmp_normalize_file.sql
`-- total.result # TPC-H涉及的22条SQL的执行时间总结

Key/Value点查场景测试

Key/Value点查场景测试，可继续使用OLAP查询场景测试创建的数据库hologres_tpch以及orders表进行Key/Value点查场景测试。具体步骤如下：

1. 创建表

   由于Key/Value点查场景使用行存表，因此不能直接使用OLAP查询场景测试中的order表，需新建表。您可使用PSQL客户端连接Hologres，并运行如下命令新建orders_row表。

   说明

   PSQL客户端连接Hologres，详情请参见连接Hologres并开发。

   DROP TABLE IF EXISTS public.orders_row;
   
   BEGIN;
   CREATE TABLE public.orders_row(
       O_ORDERKEY       BIGINT         NOT NULL PRIMARY KEY
       ,O_CUSTKEY       INT            NOT NULL
       ,O_ORDERSTATUS   TEXT           NOT NULL
       ,O_TOTALPRICE    DECIMAL(15,2)  NOT NULL
       ,O_ORDERDATE     TIMESTAMPTZ    NOT NULL
       ,O_ORDERPRIORITY TEXT           NOT NULL
       ,O_CLERK         TEXT           NOT NULL
       ,O_SHIPPRIORITY  INT            NOT NULL
       ,O_COMMENT       TEXT           NOT NULL
   );
   CALL SET_TABLE_PROPERTY('public.orders_row', 'orientation', 'row');
   CALL SET_TABLE_PROPERTY('public.orders_row', 'clustering_key', 'o_orderkey');
   CALL SET_TABLE_PROPERTY('public.orders_row', 'distribution_key', 'o_orderkey');
   COMMIT;

2. 导入数据

   您可以使用如下INSERT INTO语句，将TPC-H数据集中的orders表数据导入至orders_row表。

   INSERT INTO public.orders_row SELECT * FROM public.orders;

3. 执行查询

   1. 生成查询语句。

      Key/Value点查场景主要有两种查询场景，具体查询语句如下：

      查询方式	查询语句	说明
      单值筛选	SELECT column_a ,column_b ,... ,column_x FROM table_x WHERE pk = value_x ;	此查询语句主要用于单值筛选，即WHERE的SQL语句取值唯一。
      多值筛选	SELECT column_a ,column_b ,... ,column_x FROM table_x WHERE pk IN ( value_a, value_b,..., value_x ) ;	此查询语句主要用于多值筛选，即WHERE的SQL语句可以取多个值。

      您可以使用如下脚本生成所需的SQL语句。

      rm -rf kv_query
      mkdir kv_query
      cd kv_query
      echo "
      \set column_values random(1,99999999)
      select O_ORDERKEY,O_CUSTKEY,O_ORDERSTATUS,O_TOTALPRICE,O_ORDERDATE,O_ORDERPRIORITY,O_CLERK,O_SHIPPRIORITY,O_COMMENT from public.orders_row WHERE o_orderkey =:column_values;
      " >> kv_query_single.sql
      echo "
      \set column_values1 random(1,99999999)
      \set column_values2 random(1,99999999)
      \set column_values3 random(1,99999999)
      \set column_values4 random(1,99999999)
      \set column_values5 random(1,99999999)
      \set column_values6 random(1,99999999)
      \set column_values7 random(1,99999999)
      \set column_values8 random(1,99999999)
      \set column_values9 random(1,99999999)
      select O_ORDERKEY,O_CUSTKEY,O_ORDERSTATUS,O_TOTALPRICE,O_ORDERDATE,O_ORDERPRIORITY,O_CLERK,O_SHIPPRIORITY,O_COMMENT from public.orders_row WHERE o_orderkey in(:column_values1,:column_values2,:column_values3,:column_values4,:column_values5,:column_values6,:column_values7,:column_values8,:column_values9);
      " >> kv_query_in.sql

      脚本执行完成后，会生成2个SQL文件：

      • kv_query_single.sql表示单值筛选的SQL。

      • kv_query_in.sql表示多值筛选的SQL，该脚本会随机生成一个针对10个值筛选的SQL。

   2. 为了方便统计查询信息，您需要使用pgbench工具。您可以使用如下命令安装pgbench工具。

      yum install postgresql-contrib -y

      为了避免因工具兼容性问题影响测试，建议您安装版本为13及以上的pgbench工具。如果您本地已经安装pgbench工具，请确保其版本为9.6以上。您可以通过执行如下命令查看当前工具版本。

      pgbench --version

   3. 执行测试语句。

      说明

      以下命令需在生成查询语句的目录下执行。

      • 针对单值筛选的场景，使用pgbench工具进行压测。

        PGUSER=<AccessKey_ID> PGPASSWORD=<AccessKey_Secret> PGDATABASE=<Database> pgbench -h <Endpoint> -p <Port> -c <Client_Num> -T <Query_Seconds> -M prepared -n -f kv_query_single.sql

      • 针对多值筛选的场景，使用pgbench工具进行压测。

        PGUSER=<AccessKey_ID> PGPASSWORD=<AccessKey_Secret> PGDATABASE=<Database> pgbench -h <Endpoint> -p <Port> -c <Client_Num> -T <Query_Seconds> -M prepared -n -f kv_query_in.sql

      参数说明如下表所示。

      参数	说明
      AccessKey_ID	当前阿里云账号的AccessKey ID。 您可以单击AccessKey 管理，获取AccessKey ID。
      AccessKey_Secret	当前阿里云账号的AccessKey Secret。 您可以单击AccessKey 管理，获取AccessKey Secret。
      Database	Hologres的数据库名称。 开通Hologres实例后，系统自动创建postgres数据库。 您可以使用postgres数据库链接Hologres，但是该数据库分配到的资源较少，开发实际业务建议您新建数据库。详情请参见创建数据库。
      Endpoint	Hologres实例的网络地址（Endpoint）。 您可以进入Hologres管理控制台的实例详情页，从网络信息区域获取网络地址。
      Port	Hologres实例的网络端口。 进入Hologres管理控制台的实例详情页获取网络端口。
      Client_Num	客户端数目，即并发度。 例如，本文由于该测试仅测试查询性能，不测试并发，将并发度置为1即可。
      Query_Seconds	每个客户端需要执行的每个Query的压测时长（Query_Seconds，秒）。例如，本文该参数取值为300。

数据更新场景

该场景用于测试OLAP引擎在有主键情况下数据更新的性能，以及在主键冲突时更新整行数据。

• 生成查询

  echo "
  \set O_ORDERKEY random(1,99999999)
  INSERT INTO public.orders_row(o_orderkey,o_custkey,o_orderstatus,o_totalprice,o_orderdate,o_orderpriority,o_clerk,o_shippriority,o_comment) VALUES (:O_ORDERKEY,1,'demo',1.1,'2021-01-01','demo','demo',1,'demo') on conflict(o_orderkey) do update set (o_orderkey,o_custkey,o_orderstatus,o_totalprice,o_orderdate,o_orderpriority,o_clerk,o_shippriority,o_comment)= ROW(excluded.*);
  " > /root/insert_on_conflict.sql

• 插入及更新，更对参数说明请参见参数说明。

  PGUSER=<AccessKey_ID> PGPASSWORD=<AccessKey_Secret> PGDATABASE=<Database> pgbench -h <Endpoint> -p <Port> -c <Client_Num> -T <Query_Seconds> -M prepared -n -f /root/insert_on_conflict.sql

• 示例结果

  transaction type: Custom query
  scaling factor: 1
  query mode: prepared
  number of clients: 249
  number of threads: 1
  duration: 60 s
  number of transactions actually processed: 1923038
  tps = 32005.850214 (including connections establishing)
  tps = 36403.145722 (excluding connections establishing)

Flink实时写入场景

该场景用于测试实时数据写入能力。

• Hologres DDL

  该场景Hologres的表拥有10列，其中key列为主键，Hologres DDL如下。

  DROP TABLE IF EXISTS flink_insert;
  
  BEGIN ;
  CREATE TABLE IF NOT EXISTS flink_insert(
    key INT PRIMARY KEY
    ,value1 TEXT
    ,value2 TEXT
    ,value3 TEXT
    ,value4 TEXT
    ,value5 TEXT
    ,value6 TEXT
    ,value7 TEXT
    ,value8 TEXT
    ,value9 TEXT
  );
  CALL SET_TABLE_PROPERTY('flink_insert', 'orientation', 'row');
  CALL SET_TABLE_PROPERTY('flink_insert', 'clustering_key', 'key');
  CALL SET_TABLE_PROPERTY('flink_insert', 'distribution_key', 'key');
  COMMIT;

• Flink作业脚本

  使用Flink全托管自带的随机数发生器向Hologres写入数据，当主键冲突时选择整行更新，单行数据量超过512 B，Flink作业脚本如下。

  CREATE TEMPORARY TABLE flink_case_1_source (
      key INT,
      value1 VARCHAR,
      value2 VARCHAR,
      value3 VARCHAR,
      value4 VARCHAR,
      value5 VARCHAR,
      value6 VARCHAR,
      value7 VARCHAR,
      value8 VARCHAR,
      value9 VARCHAR
    )
  WITH (
      'connector' = 'datagen',
       -- optional options --
      'rows-per-second' = '1000000000',
      'fields.key.min'='1',
      'fields.key.max'='2147483647',
      'fields.value1.length' = '57',
      'fields.value2.length' = '57',
      'fields.value3.length' = '57',
      'fields.value4.length' = '57',
      'fields.value5.length' = '57',
      'fields.value6.length' = '57',
      'fields.value7.length' = '57',
      'fields.value8.length' = '57',
      'fields.value9.length' = '57'
    );
  
  -- 创建 Hologres 结果表
  CREATE TEMPORARY TABLE flink_case_1_sink (
      key INT,
      value1 VARCHAR,
      value2 VARCHAR,
      value3 VARCHAR,
      value4 VARCHAR,
      value5 VARCHAR,
      value6 VARCHAR,
      value7 VARCHAR,
      value8 VARCHAR,
      value9 VARCHAR
    )
  WITH (
      'connector' = 'hologres',
      'dbname'='<yourDbname>',  --Hologres的数据库名称。
      'tablename'='<yourTablename>',  --Hologres用于接收数据的表名称。
      'username'='<yourUsername>',  --当前阿里云账号的AccessKey ID。
      'password'='<yourPassword>',  --当前阿里云账号的AccessKey Secret。
      'endpoint'='<yourEndpoint>',  --当前Hologres实例VPC网络的Endpoint。
      'connectionSize' = '10',  --默认为3
      'jdbcWriteBatchSize' = '1024',  --默认为256
      'jdbcWriteBatchByteSize' = '2147483647',  --默认为20971520
      'mutatetype'='insertorreplace'  --插入或整行替换已有数据
    );
  
  -- 进行 ETL 操作并写入数据
  insert into flink_case_1_sink
  select key,
    value1,
    value2,
    value3,
    value4,
    value5,
    value6,
    value7,
    value8,
    value9
  from
    flink_case_1_source
  ;

  参数说明请参见Hologres结果表。

• 示例结果

  在Hologres的管理控制台的监控信息页面，即可看到RPS的数值。

TPC-H 22条查询语句

• Q1

  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 '120' day
  group by
          l_returnflag,
          l_linestatus
  order by
          l_returnflag,
          l_linestatus;

• Q2

  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 = 'EUROPE'
          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 = 'EUROPE'
          )
  order by
          s_acctbal desc,
          n_name,
          s_name,
          p_partkey
  limit 100;

• Q3

  select
          l_orderkey,
          sum(l_extendedprice * (1 - l_discount)) as revenue,
          o_orderdate,
          o_shippriority
  from
          customer,
          orders,
          lineitem
  where
          c_mktsegment = 'MACHINERY'
          and c_custkey = o_custkey
          and l_orderkey = o_orderkey
          and o_orderdate < date '1995-03-23'
          and l_shipdate > date '1995-03-23'
  group by
          l_orderkey,
          o_orderdate,
          o_shippriority
  order by
          revenue desc,
          o_orderdate
  limit 10;

• Q4

  select
          o_orderpriority,
          count(*) as order_count
  from
          orders
  where
          o_orderdate >= date '1996-07-01'
          and o_orderdate < date '1996-07-01' + 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;

• Q5

  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 = 'EUROPE'
          and o_orderdate >= date '1996-01-01'
          and o_orderdate < date '1996-01-01' + interval '1' year
  group by
          n_name
  order by
          revenue desc;

• Q6

  select
          sum(l_extendedprice * l_discount) as revenue
  from
          lineitem
  where
          l_shipdate >= date '1996-01-01'
          and l_shipdate < date '1996-01-01' + interval '1' year
          and l_discount between 0.02 - 0.01 and 0.02 + 0.01
          and l_quantity < 24;

• Q7

  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 = 'CANADA' and n2.n_name = 'BRAZIL')
                                  or (n1.n_name = 'BRAZIL' and n2.n_name = 'CANADA')
                          )
                          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;

• Q8

  select
          o_year,
          sum(case
                  when nation = 'BRAZIL' 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 = 'AMERICA'
                          and s_nationkey = n2.n_nationkey
                          and o_orderdate between date '1995-01-01' and date '1996-12-31'
                          and p_type = 'LARGE ANODIZED COPPER'
          ) as all_nations
  group by
          o_year
  order by
          o_year;

• Q9

  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 '%maroon%'
          ) as profit
  group by
          nation,
          o_year
  order by
          nation,
          o_year desc;

• 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 '1993-02-01'
          and o_orderdate < date '1993-02-01' + 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

  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 = 'EGYPT'
  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 = 'EGYPT'
                  )
  order by
          value desc;

• 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 ('FOB', 'AIR')
          and l_commitdate < l_receiptdate
          and l_shipdate < l_commitdate
          and l_receiptdate >= date '1997-01-01'
          and l_receiptdate < date '1997-01-01' + interval '1' year
  group by
          l_shipmode
  order by
          l_shipmode;

• Q13

  select
          c_count,
          count(*) as custdist
  from
          (
                  select
                          c_custkey,
                          count(o_orderkey) as c_count
                  from
                          customer left outer join orders on
                                  c_custkey = o_custkey
                                  and o_comment not like '%special%deposits%'
                  group by
                          c_custkey
          ) c_orders
  group by
          c_count
  order by
          custdist desc,
          c_count desc;

• Q14

  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 '1997-06-01'
          and l_shipdate < date '1997-06-01' + interval '1' month;

• Q15

  with revenue0(SUPPLIER_NO, TOTAL_REVENUE)  as
      (
      select
          l_suppkey,
          sum(l_extendedprice * (1 - l_discount))
      from
          lineitem
      where
          l_shipdate >= date '1995-02-01'
          and l_shipdate < date '1995-02-01' + 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;

• Q16

  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#45'
          and p_type not like 'SMALL ANODIZED%'
          and p_size in (47, 15, 37, 30, 46, 16, 18, 6)
          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;

• Q17

  select
          sum(l_extendedprice) / 7.0 as avg_yearly
  from
          lineitem,
          part
  where
          p_partkey = l_partkey
          and p_brand = 'Brand#51'
          and p_container = 'WRAP PACK'
          and l_quantity < (
                  select
                          0.2 * avg(l_quantity)
                  from
                          lineitem
                  where
                          l_partkey = p_partkey
          );

• Q18

  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;

• Q19

  select
          sum(l_extendedprice* (1 - l_discount)) as revenue
  from
          lineitem,
          part
  where
          (
                  p_partkey = l_partkey
                  and p_brand = 'Brand#52'
                  and p_container in ('SM CASE', 'SM BOX', 'SM PACK', 'SM PKG')
                  and l_quantity >= 3 and l_quantity <= 3 + 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#43'
                  and p_container in ('MED BAG', 'MED BOX', 'MED PKG', 'MED PACK')
                  and l_quantity >= 12 and l_quantity <= 12 + 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#52'
                  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'
          );

• Q20

  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 'drab%'
                          )
                          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 '1996-01-01'
                                          and l_shipdate < date '1996-01-01' + interval '1' year
                          )
          )
          and s_nationkey = n_nationkey
          and n_name = 'KENYA'
  order by
          s_name;

• Q21

  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 = 'PERU'
  group by
          s_name
  order by
          numwait desc,
          s_name
  limit 100;

• Q22

  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
                                  ('24', '32', '17', '18', '12', '14', '22')
                          and c_acctbal > (
                                  select
                                          avg(c_acctbal)
                                  from
                                          customer
                                  where
                                          c_acctbal > 0.00
                                          and substring(c_phone from 1 for 2) in
                                                  ('24', '32', '17', '18', '12', '14', '22')
                          )
                          and not exists (
                                  select
                                          *
                                  from
                                          orders
                                  where
                                          o_custkey = c_custkey
                          )
          ) as custsale
  group by
          cntrycode
  order by
          cntrycode;