The ADvanced Systems Laboratory (ADSL)
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Analysis of HDFS Under HBase: A Facebook Messages Case Study
Tyler Harter,
Dhruba Borthakur*,
Siying Dong*,
Amitanand Aiyer*,
Liyin Tang*,
Andrea C. Arpaci-Dusseau,
Remzi H. Arpaci-Dusseau
Department of Computer Sciences, University of Wisconsin-Madison
* Facebook Inc.
Abstract:
We present a multilayer study of the Facebook Messages stack,
which is based on HBase and HDFS. We collect and analyze HDFS
traces to identify potential improvements, which we then evaluate
via simulation. Messages represents a new HDFS workload: whereas
HDFS was built to store very large files and receive
mostly-sequential I/O, 90% of files are smaller than 15MB and I/O
is highly random. We find hot data is too large to easily fit in
RAM and cold data is too large to easily fit in flash; however, cost
simulations show that adding a small flash tier improves performance
more than equivalent spending on RAM or disks. HBase's layered
design offers simplicity, but at the cost of performance; our
simulations show that network I/O can be halved if compaction
bypasses the replication layer. Finally, although Messages is
read-dominated, several features of the stack (i.e., logging,
compaction, replication, and caching) amplify write I/O, causing
writes to dominate disk I/O.
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