It is not a good idea to do this unless the fraction of rows that differ is very small. Background and requirements I see this as the next step in my recent series of posts on MySQL tools and techniques to keep replication running reliably and smoothly.
These happen potentially many times.
It builds the entire tree, then does the search. I want you correct for me. In particular, it will allow a smart DBA to specify how the grouping and recursion should happen. Also, creating these tables is not replication-friendly; the queries that run on the master will run on the slave too.
Likewise, if my table contains client data and only one client is bad, the same situation will happen.
We have a similar tool called SQLyog Job Agent which incorporates most of what you have discussed in this article. These and other spatial and temporal locality scenarios are realistic, because lots of real data is unevenly distributed.
Even analyzing the index structures on the table, and then trying to decide which are good choices, is too risky to do automatically.
The first summary table contains as many rows as the table to analyze. Fixing the rows on the master, and letting the fixes propagate to the slave via the normal means, might actually be a good idea. Summary In this article I proposed some ideas for a top-down, in-client, replication-centric way to compare a table known to differ on a master and slave, find the rows that differ, and resolve them.
Basically each summary table is build once and then it is scanned just once, so having an index built on some attribute would not be amortized. If the factor iseach level in an intermediate summary table will contain the groupwise checksum of about rows in the next most granular level summary table.
The choice of grouping is actually the most complicated part. The first checksum table has million rows; the second has 1 million, and so on. If you do develop a working implementation of your own, do let me know! James 6 Mar 07 at 7: Issues I need to research are whether the different number of rows affected on the slave will cause trouble, and if this can be solved with a temporary slave-skip-errors setting.
The algorithm needs to be: Efficient in terms of network load and server load, both when finding and when resolving differences. If the primary key is a character string, I might group on the first few letters of the string.
It can recurse all the databases and tables to repair an entire database, or just operate on a single table. We have a lot of data in InnoDB tables with day-first or week-first primary keys, which as you know creates a day-first or week-first clustered index.
Some things I assume: The issue with the indexing is not scans, but lookups from a child table to its parent tables, including the group-by queries.
It defeats any optimizations I might be able to make based on knowledge of where in the table the rows differ. Xaprb 15 May 07 at 7: This is a major issue, especially in some large tables I work with where we do things a client or account at a time. This might not be a problem for everyone, but it would not be acceptable for my purposes.
Groups are defined by taking checksums from the previous level modulo the folding factor. Too much of the table is different.Simple life, Complicated mind Wednesday, December 16, An algorithm to find and resolve data differences between MySQL tables.
specifically so I can ‘patch’ a replication slave that has gotten slightly out of sync without completely re-initializing it. I intend to create a tool that can identify which rows are different and bring.
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