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Showing entries 1 to 10 of 58 10 Older Entries

Displaying posts with tag: indexing (reset)

Why Unique Indexes are Bad
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Before creating a unique index in TokuMX or TokuDB, ask yourself, “does my application really depend on the database enforcing uniqueness of this key?” If the answer is ANYTHING other than yes, do not declare the index to be unique. Why? Because unique indexes may kill your write performance. In this post, I’ll explain why.

Unique indexes are a strange beast: they have no impact on standard …

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Purging old rows with QueryScript: three use cases
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Problem: you need to purge old rows from a table. This may be your weekly/monthly cleanup task. The table is large, the amount of rows to be deleted is large, and doing so in one big DELETE is too heavy.

You can use oak-chunk-update or pt-archiver to accomplish the task. You can also use server side scripting with …

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532x Multikey Index Insertion Performance Increase for MongoDB with Fractal Tree Indexes
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In my three previous MongoDB blogs I wrote about our implementation of Fractal Tree(R) indexes on MongoDB, showing a 10x insertion performance increase, a 268x query performance increase, and a comparison of covered …

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My Talk Next Week at HighLoad++
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Next week I’ll be visiting Moscow to talk at Highload++. The conference will take place during Monday 22nd and Tuesday 23rd at the Radisson hotel. I will be giving my personal version of an indexing talk that my colleagues have given in meetups and conferences in the US.

Highload++ conference is targeted to address the issues of complex high traffic web properties. Most of these sites depend on databases to deliver their content, record the traffic and report the application activities in real time. As I learned early …

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Looking for MongoDB users to test Fractal Tree Indexing
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In my three previous blogs I wrote about our implementation of Fractal Tree Indexes on MongoDB, showing a 10x insertion performance increase, a 268x query performance increase, and a comparison of covered indexes and clustered indexes. The …

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MongoDB Index Shootout: Covered Indexes vs. Clustered Fractal Tree Indexes
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In my two previous blogs I wrote about our implementation of Fractal Tree Indexes on MongoDB, showing a 10x insertion performance increase and a 268x query performance increase. MongoDB’s covered indexes can provide some …

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How common_schema split()s tables - internals
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This post exposes some of the internals, and the SQL behind QueryScript's split. common_schema/QueryScript 1.1 introduces the split statement, which auto-breaks a "large" query (one which operates on large tables as a whole or without keys) into smaller queries, and executes them in sequence.

This makes for easier transactions, less locks held, potentially …

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Table split(...) for the masses
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(pun intended)

common_schema's new split statement (see release announcement) auto-splits complex queries over large tables into smaller ones: instead of issuing one huge query, split breaks one's query into smaller queries, each working on a different set of rows (a chunk).

Thus, it is possible to avoid holding locks for long times, allowing for smaller transactions. It …

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Webinar: Understanding Indexing
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Three rules on making indexes around queries to provide good performance

Application performance often depends on how fast a query can respond and query performance almost always depends on good indexing. So one of the quickest and least expensive ways to increase application performance is to optimize the indexes. This talk presents three simple and effective rules on how to construct indexes around queries that result in good performance.


Time: 2PM EDT / 11AM PDT

This …


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Fractal Tree Indexing and Filesystems – HotStorage 2012
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Modern file systems are well equipped to deal with large writes. One area that remains challenging however is to efficiently write out “microdata”, such as metadata and small portions of large files, while showing good I/O utilization when the data is read back. This challenge is evident with mount options like “noatime” which disables updating file access time on reads. This kind of solution avoids the problem altogether. Another approach, delayed allocation, is meant to coalesce small writes in memory as long as possible before writing it out to disk. Filesystems like ext4 and Btrfs use delayed allocation to make a best-effort at …

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Showing entries 1 to 10 of 58 10 Older Entries

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