Hologres:Test plan

About TPC-H

The following description is quoted from the TPC Benchmark™ H (TPC-H) specification:

TPC-H is a decision support benchmark that consists of a suite of business-oriented ad hoc queries and concurrent data modifications. The queries and the data populating the database have been chosen to have broad industry-wide relevance. This benchmark illustrates decision support systems that examine large volumes of data, execute queries with a high degree of complexity, and give answers to critical business questions.

For more information, see TPC Benchmark™ H Standard Specification.

Datasets

TPC-H is a test set developed by the Transaction Processing Performance Council (TPC) to simulate decision support systems. TPC-H is used in academia and industries to evaluate the performance of decision support systems.

TPC-H models data in production environments to simulate the data warehouse of a sales system. The data warehouse consists of eight tables. The size of each table ranges from 1 GB to 3 TB. The TPC-H benchmark test involves 22 query statements. The test focuses on the response time of each query, which is the amount of time required from submitting a query to receiving the returned result. The test results can comprehensively reflect the capability of the system to process queries. For more information, see TPC BENCHMARK H Standard Specification.

Scenarios

Precautions

To reduce the variables that may have impacts on test results, we recommend that you use new instances each time you perform the tests described in this topic, instead of upgrading or downgrading the specifications of existing instances, to meet the test requirements.

Performance test on OLAP queries

Performance test on point queries of key-value pairs

You can use the database hologres_tpch and the table ORDERS that are created for the performance test on OLAP queries to perform the performance test on point queries of key-value pairs. Procedure:

1. Create a table.

   The performance test on point queries of key-value pairs requires a row-oriented table. Therefore, the table created for the performance test on OLAP queries cannot be directly used. You must create a row-oriented table. You can use the PostgreSQL client to connect to the Hologres instance and run the following command to create a table named public.orders_row.

   Note

   For more information about how to use the PostgreSQL client to connect to the Hologres instance, see the "Connect to a Hologres instance for data development" section in Use the PostgreSQL client to connect to Hologres.

   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. Import data.

   You can execute the INSERT INTO statement to import data from the ORDERS table in the TPC-H dataset to the public.orders_row table.

   Note

   Hologres V2.1.17 and later support the Serverless Computing feature. The Serverless Computing feature is suitable for scenarios in which you want to import a large amount of data offline, run large-scale extract, transform, and load (ETL) jobs, or query a large amount of data from foreign tables. You can use the Serverless Computing feature to perform the preceding operations based on additional serverless computing resources. This can eliminate the need to reserve additional computing resources for the instances. This improves instance stability and reduces the occurrences of out of memory (OOM) errors. You are charged only for the additional serverless computing resources used by tasks. For more information about the Serverless Computing feature, see Overview of Serverless Computing. For more information about how to use the Serverless Computing feature, see User guide on Serverless Computing.

   -- Optional. We recommend that you use the Serverless Computing feature to import a large amount of data offline and run extract, transform, and load (ETL) jobs.
   SET hg_computing_resource = 'serverless';
   
   INSERT INTO public.orders_row SELECT * FROM public.orders;
   
   -- Reset the configurations. This ensures that serverless computing resources are not used for subsequent SQL statements. 
   RESET hg_computing_resource;

3. Perform queries.

   1. Generate a query statement.

      The following table describes the two types of queries involved in the performance test on point queries of key-value pairs.

      Query type	Query statement	Description
      Single-value filtering	SELECT column_a ,column_b ,... ,column_x FROM table_x WHERE pk = value_x ;	This query statement applies to single-value filtering where only one primary key value is specified in the WHERE clause.
      Multi-value filtering	SELECT column_a ,column_b ,... ,column_x FROM table_x WHERE pk IN ( value_a, value_b,..., value_x ) ;	This query statement applies to multi-value filtering where multiple primary key values are specified in the WHERE clause.

      You can execute the following script to generate the required SQL statement.

      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

      Two SQL files are generated:

      • kv_query_single.sql: The SQL statement that applies to single-value filtering is saved in this file.

      • kv_query_in.sql: The SQL statement that applies to multi-value filtering is saved in this file, where 10 random primary key values are specified in the WHERE clause.

   2. Install pgbench, which facilitates statistics collection on queries. You can run the following command to install pgbench:

      yum install postgresql-contrib -y

      To prevent incompatibility issues, we recommend that you install pgbench V13 or later. If you have locally installed pgbench, make sure that its version is later than V9.6. To view the version of pgbench, run the following command:

      pgbench --version

   3. Execute the query statement.

      Note

      You must run the following commands in the directory where the SQL files reside.

      • Use pgbench to execute the query statement that applies to single-value filtering.

        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

      • Use pgbench to execute the query statement that applies to multi-value filtering.

        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

      The following table describes the parameters in the preceding commands.

      Parameter	Description
      AccessKey_ID	The AccessKey ID of your Alibaba Cloud account. You can obtain the AccessKey ID from the AccessKey Pair page.
      AccessKey_Secret	The AccessKey secret of your Alibaba Cloud account. You can obtain the AccessKey secret from the AccessKey Pair page.
      Database	The name of the Hologres database. After you purchase a Hologres instance, a database named postgres is created by default. You can connect the postgres database to the Hologres instance. However, limited resources are allocated to this database. We recommend that you create a database to ensure sufficient resources for your business. For more information, see Create a database.
      Endpoint	The endpoint of the Hologres instance. You can obtain the endpoint of the Hologres instance from the Network Information section of the Instance Details page in the Hologres console.
      Port	The port number of the Hologres instance. You can obtain the port number of the Hologres instance on the Instance Details page in the Hologres console.
      Client_Num	The number of clients to be tested. In this example, you need to test only query performance, but not the concurrency. Therefore, this parameter is set to 1.
      Query_Seconds	The stress testing duration of each query to be executed by each client. Unit: seconds. In this example, this parameter is set to 300.

Data update test

You can test the performance of data updates based on the primary key for the OLAP engine. In this example, a row of data is inserted, or a row of data is updated if a primary key conflict occurs.

• Generate a query statement.

  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

• Insert data or update data. For more information about the parameters, see Parameters in this topic.

  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

• Sample result:

  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)

Performance test on using Realtime Compute for Apache Flink to write data to Hologres in real time

You can perform this test to evaluate the performance of using Realtime Compute for Apache Flink to write data to Hologres in real time.

• Hologres DDL statements

  In this example, a Hologres table that contains 10 columns is used. The key column is configured as the primary key column. To create this Hologres table, you can execute the following DDL statements:

  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;

• Scripts for a Realtime Compute for Apache Flink deployment

  You can use the random number generator provided by fully managed Flink to write data to Hologres. If a primary key conflict occurs, the entire row of data is updated. Each row contains data of more than 512 bytes. You can execute the following scripts to run a Realtime Compute for Apache Flink job:

  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'
    );
  
  -- Create a Hologres result table.
  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>', -- The name of the Hologres database. 
      'tablename'='<yourTablename>', -- The name of the Hologres table to which you want to write data. 
      'username'='<yourUsername>', --The AccessKey ID of your Alibaba Cloud account. 
      'password'='<yourPassword>', -- The AccessKey secret of your Alibaba Cloud account. 
      'endpoint'='<yourEndpoint>', -- The VPC endpoint of the Hologres instance to which you want to connect. 
      'connectionSize' = '10', -- The default value is 3.
      'jdbcWriteBatchSize' = '1024', -- The default value is 256.
      'jdbcWriteBatchByteSize' = '2147483647',  -- The default value is 20971520.
      'mutatetype'='insertorreplace'  -- Insert a row of data, or replace data in an entire row.
    );
  
  -- Extract, transform, and load data and write data to Hologres.
  insert into flink_case_1_sink
  select key,
    value1,
    value2,
    value3,
    value4,
    value5,
    value6,
    value7,
    value8,
    value9
  from
    flink_case_1_source
  ;

  For more information about the parameters, see Hologres result table.

• Sample result:

  On the Monitoring Information page of the Hologres instance in the Hologres console, you can view the records per second (RPS).

22 TPC-H query statements

• 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;