Allowoverride fileinfo re write as a logarithmic equation

Each row in the first table contains key column sa checksum of the key column sand a checksum of the whole row. Each row in an intermediate-level summary table contains checksums for a group of rows in the next more granular level of summary data.

Finally, and this could be either a strength or weakness, this approach lets every level of the recursion have a different branching factor, which might be appropriate or not — the DBA needs to decide.

If you do develop a working implementation of your own, do let me know. It builds the entire tree, then does the search. 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.

Too much of the table is different. Here are my requirements. Groups are defined by taking checksums from the previous level modulo the folding factor. Efficient on the client-side where the tool is executed.

Efficient in terms of network load and server load, both when finding and when resolving differences. If a single-column key, look for another key whose cardinality is less, and recurse from that to the primary key instead.

Too much of the table is different. 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. Also, creating these tables is not replication-friendly; the queries that run on the master will run on the slave too.

If the primary key is a character string, I might group on the first few letters of the string. In the best case, all other things being equal, it will require the server to read about as many rows as the bottom-up approach, but it will exploit locality — a client at a time, a day at a time, and so on.

Also, creating these tables is not replication-friendly; the queries that run on the master will run on the slave too.

Generate groupwise checksums for the whole table in a top-level grouping more on that later. I want you correct for me. The flip side of this is actually a strength: Designed for statement-based replication, which means no temp tables, no expensive queries that will propagate to the slave, and so forth.

We have a similar tool called SQLyog Job Agent which incorporates most of what you have discussed in this article. Moreover, if the candidate tuples are somehow an identifiable fraction of the table, it might be simpler to just download them directly for comparison, that would be a third algorithm: The flip side of this is actually a strength: Take for example one of our tables that is primary-keyed on IDs, which are auto-incremented numbers, and client account numbers.

Likewise, if my table contains client data and only one client is bad, the same situation will happen. The documentation for this tool is an excellent read, as it goes into great detail on the algorithm used.

The algorithm needs to be: Tables must have primary keys. The issue with the indexing is not scans, but lookups from a child table to its parent tables, including the group-by queries.

Moreover, if the candidate tuples are somehow an identifiable fraction of the table, it might be simpler to just download them directly for comparison, that would be a third algorithm: 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.

I need a tool that, given a table known to differ on master and slave swill efficiently compare the tables and resolve the differences. Each row in the first table contains key column sa checksum of the key column sand a checksum of the whole row.

I intend to create a tool that can identify which rows are different and bring them into sync. 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.

It defeats any optimizations I might be able to make based on knowledge of where in the table the rows differ. 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. FreeBSD, Linux, PHP, JavaScript, MySQL, Programming. I’ve been designing an algorithm to 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.

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