Thursday, January 27, 2011

indexing hashmap-based cache for real time query (UBS

There might be other posts in this blog, but take this as a refresher...

UBS (Stamford, not JC team) equity system has large data set in memory. Perhaps a hell lot of market data. I was told the system was so well-tuned that it needs just one full GC run each day (See 2 other posts on "1 GC/day"). It's presumably based on hashmaps or a key/value noSQL DB

What if I want all the IBM trades over the past 5 days, but hashmap key is something like confirm-ID or trade-ID but not stock symbol? This requires a full scan of the entire universe of trades.

Gemfire suggests that an index is much faster than a full scan. (Probably same in SecDB and Sandra) an index is a separate map of (stockSymbol -} confirm-ID) or a simpler map of (sotckSymbol -} tradeObject) [1]. If you want a range select like "stock symbols starting with IB", then you need a RB tree, or a skip list tree.

[1] I feel confirm-ID is more flexible. You can easily make the cache distributed.

A radical approach keeps everything in DB, and front it with a DB-cache. Full scan scenario? You hit the DB index. However, b+tree index is optimized for disk, sub-optimal for in-memory. A more serious penalty is network/IPC latency, even if you run the entire DB in the same Unix box. Admire the _single_ JVM solution !

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