Igniters, I had several private talks with Igniters about data compression and would like to share the summary with ... Igniters :-)
Currently all Ignite's data is uncompressed. It leads to excessive network traffic, GC pressure and disk IO (in case of persistence). Most modern databases are able to compress data, what gives them 2-4x size reduction on typical workloads. We need compression in Ignite. There are several options I'd like to discuss. The main difference between them - on what "level" to compress: per-entry, per-data-page or per-cache. *1) Per-entry compression* Apache Geode uses this approach. Every cache entry is compressed using Snappy. This is very easy to implement, but every entry access (e.g. reading single field) require full decompression or even re-compression, what could lead to higher CPU consumption and worse performance. *2) Per-data-page compression* Oracle and DB2 use this approach. Pages are compressed with dictionary-based approach (e.g. LZV). It is important, that they do not compress the whole page. Instead, only actual data is compressed, while page structure remains intact. Dictionary is placed within the page. This way it is possible to work with individual entries and even individual fields without full page decompression. Another important thing - it is not necessary to re-compress the page on each write. Instead, data is stored in uncompressed form first, and compressed even after certain threshold is reached. So negative CPU impact is minimal. Typical compression rate would be higher than in per-entry case, because the more data you have, the better it can be compressed. *3) Per-cache compression* Suggested by Alex Goncharuk. We could have a dictionary for the whole cache. This way we could achieve the highest compression rate possible. The downside is complex implementation - we would have to develop an algorithm of sharing the dictionary within the cluster. At some point the dictionary could become too huge to fit in-memory, so we should either control it's size or spill it to disk. I propose to use per-data-page approach as both gives nice compression rate and relatively easy to implement. Please share your thoughts. Vladimir.
