VDiff v1

Compare the source and target in a workflow to ensure integrity

This is the legacy v1 VDiff. VDiff v2, which runs on tablets, is now production-ready. We recommend that you begin using v2 instead.

Command #

VDiff -- --v1 [--source_cell=<cell>] [--target_cell=<cell>] [--tablet_types=primary,replica,rdonly]
       [--limit=<max rows to diff>] [--tables=<table list>] [--format=json] [--max_extra_rows_to_compare=1000]
       [--filtered_replication_wait_time=30s] [--debug_query] [--only_pks] <keyspace.workflow>

Description #

VDiff does a row by row comparison of all tables associated with the workflow, diffing the source keyspace and the target keyspace and reporting counts of missing/extra/unmatched rows.

It is highly recommended that you do this before you finalize a workflow with SwitchTraffic.

Parameters #

--source_cell #

optional
default all

VDiff will choose a tablet from this cell to diff the source tables with the target tables

--target_cell #

optional
default all

VDiff will choose a tablet from this cell to diff the target tables with the source tables

--tablet_types #

optional
default in_order:RDONLY,REPLICA,PRIMARY

A comma separated list of tablet types that are used while picking a tablet for sourcing data. One or more from PRIMARY, REPLICA, RDONLY.

--filtered_replication_wait_time #

optional
default 30s

VDiff finds the current position of the source primary and then waits for the target replication to reach that position for --filtered_replication_wait_time. If the target is much behind the source or if there is a high write qps on the source then this time will need to be increased.

--limit #

optional
default 9223372036854775807

Maximum number of rows to run vdiff on (across all tables specified). This limit is usually set while diffing a large table as a quick consistency check.

--tables #

optional
default all tables in the workflow

A comma separated list of tables to run vdiff on.

--format #

optional
default unstructured text output

Only other format supported is json
Example: #
[{
  "ProcessedRows": 5,
  "MatchingRows": 5,
  "MismatchedRows": 0,
  "ExtraRowsSource": 0,
  "ExtraRowsTarget": 0
},{
  "ProcessedRows": 3,
  "MatchingRows": 3,
  "MismatchedRows": 0,
  "ExtraRowsSource": 0,
  "ExtraRowsTarget": 0
}]

--max_extra_rows_to_compare #

optional
default 1000

Limits the number of extra rows on both the source and target that we will perform a second compare pass on to confirm that the rows are in fact different in content and not simply returned in a different order on the source and target (which can happen when there are collation differences, e.g. different MySQL versions).

--debug_query #

optional

Adds a MySQL query to the report that can be used for further debugging.

--only_pks #

optional

When reporting missing rows, only show primary keys in the report.

keyspace.workflow #

mandatory

Name of target keyspace and the associated workflow to run VDiff on.

Example #

$ vtctlclient VDiff customer.commerce2customer

Summary for corder: {ProcessedRows:10 MatchingRows:10 MismatchedRows:0 ExtraRowsSource:0 ExtraRowsTarget:0}
Summary for customer: {ProcessedRows:11 MatchingRows:11 MismatchedRows:0 ExtraRowsSource:0 ExtraRowsTarget:0}

Using VDiff With Huge Tables #

Currently VDiff runs within vtctld. Each VDiff will stream rows from all sources and targets and then compare them row by row after assembling the rows in order. Since there are no database transactions, VDiff will run much faster than the actual workflow. However, for huge tables (billions of rows or terabytes in size) this can take several hours or even days depending on the number of rows, row composition, server configurations and the topology of the cluster. If your sources and/or targets are across multiple cells, for example, this can slow down the VDiff considerably.

Actual VDiff speeds are of course dependent on several factors in your cluster. But as a reference, we have seen VDiffs run as fast as 400mrph (million rows per hour) (~9B rows/day) for tables with short rows, or as slow as 60mrph (~1.5B rows/day), for tables with larger width and complex columns.

You may need to use one or more of the following recommendations while running long VDiffs:

  • If VDiff takes more than an hour vtctlclient will hit grpc/http timeouts of 1 hour. In that case you can use vtctl (the bundled vctlclient + vtctld) instead.
  • VDiff also synchronizes sources and targets to get consistent snapshots. If you have a high write QPS then you may encounter timeouts during the sync. Use higher values of --filtered_replication_wait_time to prevent that, for example --filtered_replication_wait_time=4h.
  • If VDiff takes more than a day set the --wait-time parameter, which is the maximum time a vtctl command can run for, to a value comfortably higher than the expected run time, for example --wait-time=168h.
  • You can follow the progress of the command by tailing the vtctld logs. VDiff logs progress every 10 million rows. This can also give you an early indication of how long it will run for, allowing you to increase your settings if needed.

Note #

  • There is no throttling, so you might see an increased lag in the replica used as the source.
  • VDiff is currently not resumable, so any timeouts or errors mean that you will need to rerun the entire VDiff again.
  • VDiff runs one table at a time.
VDiff v2, which addresses these issues, is now production-ready and we recommend you use that instead.
VDiff v1