Hello,

I'm trying to troubleshoot a performance a replication issue between two version of MariaDB.  I know that we are using two EOL versions, but I want to rule out all issues before prioritizing migrating to a new version.

I have built a new dedicated replication server (B) to replace the current dedicated replica (A).  A and B are both running identical OSes and versions and near identical hardware in a RAID 10 configuration.  The main difference is that B has newer disks that slightly outperform A.  I benchmarked both A and B to validate this.  Both A and B are configured identically (other then server-id).

Replica A (and primary)  is running MariaDB 10.3.31.  Replica B is running  10.3.39.

A few other things to note:

I have external monitoring to alert when either hits 500+ Seconds_Behind_Master.  Since standing B up, I am seeing it fall behind a few times a day.   The interesting thing is that A is not falling behind from the primary.

Upon further examination, a scheduled job that executes hundreds of similar delete operations off the same table (that has approx. 3 million records) is where B is largely getting hung up.  Something like this:

DELETE FROM table WHERE x = 800000 AND y = 40000

The table has an index on just x.

Running ANALYZE FORMAT=JSON SELECT * FROM table WHERE x = 800000 AND y = 40000  from B show a striking difference in total time spent: 

REPLICA B:
{
  "query_block": {
    "select_id": 1,
    "r_loops": 1,
    "r_total_time_ms": 490.13,
    "table": {
      "table_name": "table",
      "access_type": "ref",
      "possible_keys": ["table_index"],
      "key": "table_index",
      "key_length": "4",
      "used_key_parts": ["x"],
      "ref": ["const"],
      "r_loops": 1,
      "rows": 795555,
      "r_rows": 31,
      "r_total_time_ms": 490.08,
      "filtered": 100,
      "r_filtered": 100,
      "index_condition": "table.y = '40000'"
    }
  }
}
vs:
REPLICA A:
{
  "query_block": {
    "select_id": 1,
    "r_loops": 1,
    "r_total_time_ms": 106.37,
    "table": {
      "table_name": "table",
      "access_type": "ref",
      "possible_keys": ["table_index"],
      "key": "table_index",
      "key_length": "4",
      "used_key_parts": ["x"],
      "ref": ["const"],
      "r_loops": 1,
      "rows": 1146482,
      "r_rows": 31,
      "r_total_time_ms": 106.34,
      "filtered": 100,
      "r_filtered": 100,
      "index_condition": "table.y = '40000'"
    }
  }
}

That is a significant difference performance wise.  From a hardware point of view, B should have a slight edge over A.  But the contrary is true by a large margin.


As a short term "fix", I added a secondary index: create index table_index2 on table(x, y);   This significantly speeds up this operation, and, for now, seems to deal with much of the experienced replication lab in B:

SERVER B:
{
  "query_block": {
    "select_id": 1,
    "r_loops": 1,
    "r_total_time_ms": 0.253,
    "table": {
      "table_name": "table",
      "access_type": "ref",
      "possible_keys": [
        "table_index",
        "table_index2"
      ],
      "key": "table_index2,
      "key_length": "8",
      "used_key_parts": ["x", "y"],
      "ref": ["const", "const"],
      "r_loops": 1,
      "rows": 31,
      "r_rows": 31,
      "r_total_time_ms": 0.2037,
      "filtered": 100,
      "r_filtered": 100
    }
  }
}

This seems reasonable as a general optimization, but provides little comfort in understanding the root cause of my performance issue with B.  I'm hesitant to retire A in favor of B until I can get to the bottom of this.

The question I have for the community is: what would you recommend that I do to get further perspective on the issue to determine a course of action?

Thanks everyone,

Mike


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