Add index and table metrics to vttablet

[rafer]

Description

This adds the following metrics to vttablet's schema engine.

• TableRows (by table) - The estimated number of rows in the table
• TableClusteredIndexSize (by table) - The size of the clustered index (i.e. the size of the "row data")
• IndexCardinality (by index) - The estimated number of unique values in the index
• IndexBytes (by index) - The size of the index

metrics sample

curl -sS http://localhost:15100/debug/vars | jq -S '{TableRows, TableClusteredIndexSize, IndexCardinality, IndexBytes}'
{
  "IndexBytes": {
    "corder.PRIMARY": 16384,
    "customer.PRIMARY": 16384,
    "product.PRIMARY": 16384
  },
  "IndexCardinality": {
    "corder.PRIMARY": 0,
    "customer.PRIMARY": 0,
    "product.PRIMARY": 0
  },
  "TableClusteredIndexSize": {
    "corder": 16384,
    "customer": 16384,
    "product": 16384
  },
  "TableRows": {
    "corder": 0,
    "customer": 0,
    "product": 0
  }
}

These values are read from mysql system tables when Engine#Reload is called, and made available via Env#Exporter

Partition names

Since mysql implements partitions internally as one table per partition, the "table name" referenced in the stats tables mostly look like TABLE_NAME#p#PARTITION_NAME. We want to report statistics per logical table (not per partition) so we need a way to extract the underlying table name. Unfortunately, it's not as simple as splitting the composite name by #p#, because it's possible to create a table or partition with #p# as a part of the name.

The approach I took here is to load the information_schema.partitions table, which includes separate columns for the table and partition name. Then, as we read through the stats tables that contain the composite name, if we encounter a #p#, we attempt to find a matching table/partition in the loaded list, and, if it is present, we can find the base table name.

An alternative method would be to make use of information_schema.innodb_tables.name column (like we do here), which provides the table name with special characters encoded. This makes it possible to confidently split on #p#, because the # characters would be encoded if they were part of the real table or partition name. I opted for the "loading all partitions" approach instead because the joins required to get an encoded table name made the queries too slow when there are many tables, indexes or partitions.

Performance

Since performance of the queries run on #Reload has been an issue in the past, I tested the queries added in this PR with the following test setup.

• 5,000 tables with 6 indexes each (5 secondary indexes)
• 5 tables with 5,000 partitions each, 4 indexes each (3 secondary indexes)

Results:

• Entire updateTableIndexMetrics method: 716ms
  • Partitions query: 37ms
  • Table stats query (table row count and clustered index size): 15ms
  • Index bytes query (byte size of each index): 205ms
  • Cardinality query: 427ms

For comparison the InnoDBTableSizes query takes 2.0s for the same test setup.

Related Issue(s)

#17569

Checklist

• "Backport to:" labels have been added if this change should be back-ported to release branches
• If this change is to be back-ported to previous releases, a justification is included in the PR description
• Tests were added or are not required
• Did the new or modified tests pass consistently locally and on CI?
• Documentation was added or is not required

Deployment Notes

None

[vitess-bot]

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