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pg-htap-pgpool-setup.md

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This a tutorial to build an HTAP service based on PostgreSQL, MyDuck Server, and PGPool-II.

Prerequisites

Launch the HTAP cluster

Go the root path of this project and run the following commands:

cd devtools/htap-setup-pg/pgpool2
docker compose up -d --wait

Then you'll get a HTAP cluster. Have fun!

Connecting

The HTAP service can be accessed by

docker exec -ti htap-pgpool bash -c "PGPASSWORD=postgres psql -h localhost -U postgres -d postgres"

And a table test with one row data is replicated from the primary PostreSQL to MyDuck server.

psql (17.1)
Type "help" for help.

postgres=# \d
        List of relations
 Schema | Name | Type  |  Owner
--------+------+-------+----------
 public | test | table | postgres
(1 row)

postgres=# select * from test;
 id | name
----+------
  1 | test
(1 row)

Monitor status

  • The status of proxy PGPool-II can be retrieved by the built-in statement SHOW POOL_NODES. e.g. You can get the status of the servers by executing the statement SHOW POOL_NODES; on the connection to PGPool server.
postgres=# show pool_nodes;
 node_id | hostname | port | status | pg_status | lb_weight |  role   | pg_role | select_cnt | load_balance_node | replication_delay | replication_state | replication_sync_state | last_status_change  
---------+----------+------+--------+-----------+-----------+---------+---------+------------+-------------------+-------------------+-------------------+------------------------+---------------------
 0       | pgsql    | 5432 | up     | up        | 0.000000  | primary | primary | 1          | false             | 0                 |                   |                        | 2024-11-20 14:24:25
 1       | myduck   | 5432 | up     | up        | 1.000000  | standby | standby | 0          | true              | 288784            | streaming         | async                  | 2024-11-20 14:24:25
(2 rows)
  • After you connect to the HTAP service, any read statements will be sent to MyDuck Server. MyDuck Server will leverage the power of DuckDB to boost the analytical performance! The counting of the statement routing is also shown in the column select_cnt in the result of SHOW POOL_NODES.

For instance, before executing a READ statement on HTAP service:

postgres=# show pool_nodes;
 node_id | hostname | port | status | pg_status | lb_weight |  role   | pg_role | select_cnt | load_balance_node | replication_delay | replication_state | replication_sync_state | last_status_change  
---------+----------+------+--------+-----------+-----------+---------+---------+------------+-------------------+-------------------+-------------------+------------------------+---------------------
 0       | pgsql    | 5432 | up     | up        | 0.000000  | primary | primary | 1          | false             | 0                 |                   |                        | 2024-11-20 14:24:25
 1       | myduck   | 5432 | up     | up        | 1.000000  | standby | standby | 0          | true              | 288784            | streaming         | async                  | 2024-11-20 14:24:25
(2 rows)

after executing the READ statement. As you can see, the select_cnt has been increased by 1, indicating that the read statement has been routed to MyDuck server.

postgres=# select * from test;
 id | name 
----+------
  1 | test
(1 row)

postgres=# show pool_nodes;
 node_id | hostname | port | status | pg_status | lb_weight |  role   | pg_role | select_cnt | load_balance_node | replication_delay | replication_state | replication_sync_state | last_status_change  
---------+----------+------+--------+-----------+-----------+---------+---------+------------+-------------------+-------------------+-------------------+------------------------+---------------------
 0       | pgsql    | 5432 | up     | up        | 0.000000  | primary | primary | 1          | false             | 0                 |                   |                        | 2024-11-20 14:24:25
 1       | myduck   | 5432 | up     | up        | 1.000000  | standby | standby | 1          | true              | 288784            | streaming         | async                  | 2024-11-20 14:24:25
(2 rows)

Let's insert a new row and then query the table. Without surprise, the data has been replicated to our MyDuck server.

postgres=# 
postgres=# insert into test values (2, 'test again');
INSERT 0 1
postgres=# select * from test;
 id |    name    
----+------------
  1 | test
  2 | test again
(2 rows)

postgres=# show pool_nodes;
 node_id | hostname | port | status | pg_status | lb_weight |  role   | pg_role | select_cnt | load_balance_node | replication_delay | replication_state | replication_sync_state | last_status_change  
---------+----------+------+--------+-----------+-----------+---------+---------+------------+-------------------+-------------------+-------------------+------------------------+---------------------
 0       | pgsql    | 5432 | up     | up        | 0.000000  | primary | primary | 1          | false             | 0                 |                   |                        | 2024-11-20 14:24:25
 1       | myduck   | 5432 | up     | up        | 1.000000  | standby | standby | 2          | true              | 48                | streaming         | async                  | 2024-11-20 14:24:25
(2 rows)

Cleanup

You can run docker compose down to clean up all resources after the trial.