OLAP performance tests

About parallel query

ApsaraDB PolarDB MySQL 8.0 launches a parallel query framework. By default, parallel query is disabled. After parallel query is enabled, the parallel query framework is automatically enabled when the amount of queried data reaches the specified threshold. This helps to reduce the time required to run the query.

ApsaraDB PolarDB MySQL 8.0 distributes data to different threads at the storage layer. Multiple threads perform parallel computing and return the results to the leader thread. Then, the leader thread merges the results and returns the final result to the user. This helps to improve the query speed and accuracy.

Parallel query is implemented based on the parallel processing capability of multi-core CPUs. The following figure shows how parallel query works on a cluster that has an 8-core CPU and 32-GB memory.

The following section describes how to test the performance of an ApsaraDB PolarDB MySQL cluster under different conditions where the loose_max_parallel_degree parameter is set to 16 and 0, respectively. The test results are also provided.

Test environment

• An Elastic Compute Service (ECS) instance and an ApsaraDB PolarDB MySQL cluster are used for testing, and they must be deployed in the same region and zone. In this test, they are both deployed in Zone I of the China (Hangzhou) region.
• The VPC network type is selected for both the ECS instance and the ApsaraDB PolarDB MySQL cluster.
  Note Make sure that the ECS instance and the ApsaraDB PolarDB MySQL cluster are connected to the same VPC network.
• The ApsaraDB PolarDB MySQL cluster for testing is as follows:
  • The node specification is polar.mysql.x8.4xlarge (32-core 256 GB).
  • The database engine is MySQL 8.0.
  • The cluster contains two nodes, one primary node and one read-only node.
  • Use the primary endpoint to connect to the cluster. For information about how to query the primary endpoint, see View or apply for an endpoint.
• The ECS instance for testing is as follows:
  • The instance type is ecs.c5.4xlarge.
  • An ultra disk of 1,000 GiB is attached to the instance.
  • The image used by the instance is 64-bit CentOS 7.0.

Test tool

TPC-H is a standard benchmark. It is developed and released by the Transaction Processing Performance (TPC) Council to evaluate query capabilities of databases. The TPC-H benchmark contains 8 tables and defines 22 complex SQL queries. Most of the queries contain Join operations on several tables, subqueries, and Group by clauses.

Install TPC-H

1. Install TPC-H on the ECS instance.
   Note

   • The TPC-H version used in this topic is v2.18.0. Download TPC-H v2.18.0.
   • Before you download TPC-H, make sure that you have performed real-name registration.

   
2. Open the dbgen directory.

   cd dbgen

3. Copy the makefile file.

   cp makefile.suite makefile

4. Modify parameters in the makefile file, including the CC, DATABASE, MACHINE, and WORKLOAD parameters.
   1. Open the makefile file.

      vim makefile

   2. Modify the definitions of the CC, DATABASE, MACHINE, and WORKLOAD parameters.

        ################
        ## CHANGE NAME OF ANSI COMPILER HERE
        ################
        CC      = gcc
        # Current values for DATABASE are: INFORMIX, DB2, ORACLE,
        #                                  SQLSERVER, SYBASE, TDAT (Teradata)
        # Current values for MACHINE are:  ATT, DOS, HP, IBM, ICL, MVS,
        #                                  SGI, SUN, U2200, VMS, LINUX, WIN32
        # Current values for WORKLOAD are:  TPCH
        DATABASE= MYSQL
        MACHINE = LINUX
        WORKLOAD = TPCH

   3. Press Esc and then enter :wq to save the file and exit.
5. Modify the tpcd.h file and add new macro definitions.
   1. Open the tpcd.h file.

      vim tpcd.h

   2. Add the following macro definitions.

      #ifdef MYSQL
      #define GEN_QUERY_PLAN ""
      #define START_TRAN "START TRANSACTION"
      #define END_TRAN "COMMIT"
      #define SET_OUTPUT ""
      #define SET_ROWCOUNT "limit %d;\n"
      #define SET_DBASE "use %s;\n"
      #endif

   3. Press Esc and then enter :wq to save the file and exit.
6. Compile the makefile file.

   make

   After the file is compiled, two executable files are generated in this directory:

   • dbgen: the tool to generate data. When you use the InfiniDB test script, you must use this tool to generate TPC-H data.
   • qgen: the tool to generate SQL queries. The queries generated by different seeds are different. To ensure repeatability, use the 22 queries provided in the attachment.
7. Use TPC-H to generate test data.

   ./dbgen -s 100

   The -s parameter is used to specify the amount of data to be generated.

8. Use TPC-H to generate a query.
   Note To ensure the repeatability of test results, you may skip this step and use the 22 queries in the Attachment.
   1. Copy qgen and dists.dss into the queries directory.

      cp qgen queries
      cp dists.dss queries

   2. Use the following script to generate a query.

      #! /usr/bin/bash
      for i in {1..22}
      do  
        ./qgen -d $i -s 100 > db"$i".sql
      done

Test procedure

1. Verify that parallel query is enabled on the ApsaraDB PolarDB MySQL cluster.
   1. Log on to the ApsaraDB for PolarDB console.
   2. In the upper-left corner of the console, select the region where the cluster is deployed.
   3. Click the ID of the cluster.
   4. In the left-side navigation pane, choose Settings and Management > Parameters.
   5. Enter loose_max_parallel_degree in the search box and click the search icon.
      
   6. Set the current value to 16.
      Note To clearly understand how parallel query improves the performance of the cluster, perform a comparative test, in which this parameter is set to 16 and then 0.
   7. After the parameter is modified, click Apply Changes in the upper-left corner of the page.
   8. In the Save Changes dialog box that appears, click OK.
2. Connect to an ApsaraDB PolarDB MySQL database on the ECS instance. For more information, see Connect to a database cluster.
3. Create a database.

   create database tpch100g

4. Creates a table.

   source ./dss.ddl

   Note dss.ddl is under the dbgen directory in TPC-H.
5. Load data.
   1. Use the following script to create load.ddl.

      load data local INFILE 'customer.tbl' INTO TABLE customer FIELDS TERMINATED BY '|';
      load data local INFILE 'region.tbl' INTO TABLE region FIELDS TERMINATED BY '|';
      load data local INFILE 'nation.tbl' INTO TABLE nation FIELDS TERMINATED BY '|';
      load data local INFILE 'supplier.tbl' INTO TABLE supplier FIELDS TERMINATED BY '|';
      load data local INFILE 'part.tbl' INTO TABLE part FIELDS TERMINATED BY '|';
      load data local INFILE 'partsupp.tbl' INTO TABLE partsupp FIELDS TERMINATED BY '|';
      load data local INFILE 'orders.tbl' INTO TABLE orders FIELDS TERMINATED BY '|';
      load data local INFILE 'lineitem.tbl' INTO TABLE lineitem FIELDS TERMINATED BY '|';

   2. Load data.

      source ./load.ddl

6. Create a primary key and a foreign key.

   source ./dss.ri

   This example uses the tpch100g database that was previously created. Replace the content in the dss.ri file in TPC-H with the following content.

   use TPCH100G;
   -- ALTER TABLE REGION DROP PRIMARY KEY;
   -- ALTER TABLE NATION DROP PRIMARY KEY;
   -- ALTER TABLE PART DROP PRIMARY KEY;
   -- ALTER TABLE SUPPLIER DROP PRIMARY KEY;
   -- ALTER TABLE PARTSUPP DROP PRIMARY KEY;
   -- ALTER TABLE ORDERS DROP PRIMARY KEY;
   -- ALTER TABLE LINEITEM DROP PRIMARY KEY;
   -- ALTER TABLE CUSTOMER DROP PRIMARY KEY;
   -- For table REGION
   ALTER TABLE REGION
   ADD PRIMARY KEY (R_REGIONKEY);
   -- For table NATION
   ALTER TABLE NATION
   ADD PRIMARY KEY (N_NATIONKEY);
   ALTER TABLE NATION
   ADD FOREIGN KEY NATION_FK1 (N_REGIONKEY) references REGION(R_REGIONKEY);
   COMMIT WORK;
   -- For table PART
   ALTER TABLE PART
   ADD PRIMARY KEY (P_PARTKEY);
   COMMIT WORK;
   -- For table SUPPLIER
   ALTER TABLE SUPPLIER
   ADD PRIMARY KEY (S_SUPPKEY);
   ALTER TABLE SUPPLIER
   ADD FOREIGN KEY SUPPLIER_FK1 (S_NATIONKEY) references NATION(N_NATIONKEY);
   COMMIT WORK;
   -- For table PARTSUPP
   ALTER TABLE PARTSUPP
   ADD PRIMARY KEY (PS_PARTKEY,PS_SUPPKEY);
   COMMIT WORK;
   -- For table CUSTOMER
   ALTER TABLE CUSTOMER
   ADD PRIMARY KEY (C_CUSTKEY);
   ALTER TABLE CUSTOMER
   ADD FOREIGN KEY CUSTOMER_FK1 (C_NATIONKEY) references NATION(N_NATIONKEY);
   COMMIT WORK;
   -- For table LINEITEM
   ALTER TABLE LINEITEM
   ADD PRIMARY KEY (L_ORDERKEY,L_LINENUMBER);
   COMMIT WORK;
   -- For table ORDERS
   ALTER TABLE ORDERS
   ADD PRIMARY KEY (O_ORDERKEY);
   COMMIT WORK;
   -- For table PARTSUPP
   ALTER TABLE PARTSUPP
   ADD FOREIGN KEY PARTSUPP_FK1 (PS_SUPPKEY) references SUPPLIER(S_SUPPKEY);
   COMMIT WORK;
   ALTER TABLE PARTSUPP
   ADD FOREIGN KEY PARTSUPP_FK2 (PS_PARTKEY) references PART(P_PARTKEY);
   COMMIT WORK;
   -- For table ORDERS
   ALTER TABLE ORDERS
   ADD FOREIGN KEY ORDERS_FK1 (O_CUSTKEY) references CUSTOMER(C_CUSTKEY);
   COMMIT WORK;
   -- For table LINEITEM
   ALTER TABLE LINEITEM
   ADD FOREIGN KEY LINEITEM_FK1 (L_ORDERKEY)  references ORDERS(O_ORDERKEY);
   COMMIT WORK;
   ALTER TABLE LINEITEM
   ADD FOREIGN KEY LINEITEM_FK2 (L_PARTKEY,L_SUPPKEY) references 
           PARTSUPP(PS_PARTKEY,PS_SUPPKEY);
   COMMIT WORK;

7. Create an index.

   #! /usr/bin/bash
   host=$1
   port=$2
   user=$3
   password=$4
   db=$5
   sqls=("create index i_s_nationkey on supplier (s_nationkey);"
   "create index i_ps_partkey on partsupp (ps_partkey);"
   "create index i_ps_suppkey on partsupp (ps_suppkey);"
   "create index i_c_nationkey on customer (c_nationkey);"
   "create index i_o_custkey on orders (o_custkey);"
   "create index i_o_orderdate on orders (o_orderdate);"
   "create index i_l_orderkey on lineitem (l_orderkey);"
   "create index i_l_partkey on lineitem (l_partkey);"
   "create index i_l_suppkey on lineitem (l_suppkey);"
   "create index i_l_partkey_suppkey on lineitem (l_partkey, l_suppkey);"
   "create index i_l_shipdate on lineitem (l_shipdate);"
   "create index i_l_commitdate on lineitem (l_commitdate);"
   "create index i_l_receiptdate on lineitem (l_receiptdate);"
   "create index i_n_regionkey on nation (n_regionkey);"
   "analyze table supplier"
   "analyze table part"
   "analyze table partsupp"
   "analyze table customer"
   "analyze table orders"
   "analyze table lineitem"
   "analyze table nation"
   "analyze table region")
   for sql in "${sqls[@]}"
   do
       mysql -h$host -P$port -u$user -p$password -D$db  -e "$sql"
   done

   Note To more effectively measure the performance improvement brought by parallel query, you can use the following query to preload the used index data to the memory pool.

   #! /bin/bash
   host=$1
   port=$2
   user=$3
   password=$4
   dbname=$5
   MYSQL="mysql -h$host -P$port -u$user -p$password -D$dbname"
   if [ -z ${dbname} ]; then
       echo "dbname not defined."
       exit 1
   fi
   table_indexes=(
           "supplier PRIMARY"
           "supplier i_s_nationkey"
           "part PRIMARY"
           "partsupp PRIMARY"
           "partsupp i_ps_partkey"
           "partsupp i_ps_suppkey"
           "customer PRIMARY"
           "customer i_c_nationkey"
           "orders PRIMARY"
           "orders i_o_custkey"
           "orders i_o_orderdate"
           "lineitem PRIMARY"
           "lineitem i_l_orderkey"
           "lineitem i_l_partkey"
           "lineitem i_l_suppkey"
           "lineitem i_l_partkey_suppkey"
           "lineitem i_l_shipdate"
           "lineitem i_l_commitdate"
           "lineitem i_l_receiptdate"
           "nation i_n_regionkey"
           "nation PRIMARY"
           "region PRIMARY"
   )
   for table_index in "${table_indexes[@]}"
   do
       ti=($table_index)
       table=${ti[0]}
       index=${ti[1]}
       SQL="select count(*) from ${table} force index(${index})"
       echo "$MYSQL -e '$SQL'"
       $MYSQL -e "$SQL"
   done

8. Run the query.

   #! /usr/bin/env bash
   host=$1
   port=$2
   user=$3
   password=$4
   database=$5
   resfile=$6
   echo "start test run at"`date "+%Y-%m-%d %H:%M:%S"`|tee -a ${resfile}.out
   for (( i=1; i<=22;i=i+1 ))
   do
   queryfile="Q"${i}".sql"
   start_time=`date "+%s. %N"`
   echo "run query ${i}"|tee -a ${resfile}.out
   mysql -h ${host}  -P${port} -u${user} -p${password} $database -e" source $queryfile;" |tee -a ${resfile}.out
   end_time=`date "+%s. %N"`
   start_s=${start_time%.*}
   start_nanos=${start_time#*.}
   end_s=${end_time%.*}
   end_nanos=${end_time#*.}
   if [ "$end_nanos" -lt "$start_nanos" ];then
           end_s=$(( 10#$end_s -1 ))
           end_nanos=$(( 10#$end_nanos + 10 ** 9))
   fi
   time=$(( 10#$end_s - 10#$start_s )).`printf "%03d\n" $(( (10#$end_nanos - 10#$start_nanos)/10**6 ))`
   echo ${queryfile} "the "${j}" run cost "${time}" second start at"`date -d @$start_time "+%Y-%m-%d %H:%M:%S"`" stop at"`date -d @$end_time "+%Y-%m-%d %H:%M:%S"` >> ${resfile}.time
   done