tree 19790e61fcd2b070621c4780bf5c8c0b0c44c026
parent 50610cbe8742f4a1e3da60b406cb36b4c962bd72
author Joel Fernandes <joelaf@google.com> 1494842551 -0700
committer KP Singh <kpsingh@google.com> 1498769462 +0200

trappy: Speed up trappy by caching trace parsing

Pandas is extremely fast at parsing csv to data frames. Astonishingly it takes
< 1s to serialize/deserialize a 100MB work of traces with 430000 events to/from
csv. We leverage this and write out a data frames into a csv file when they are
created for the first time. Next time we read it out if it exists. To make
sure, the cache isn't stale, we take the md5sum of the trace file and also
ensure all CSVs exist before reading from the cache. I get a speed up of 16s to
1s when parsing a 100MB trace.

Co-developed-by: Brendan Jackman <brendan.jackman@arm.com>
Signed-off-by: Joel Fernandes <joelaf@google.com>
Reviewed-by: KP Singh <kpsingh@google.com>