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hbaseconasia2017: Large scale data near-line loading method and architecture

HBaseCon
HBaseCon

Shuaifeng Zhou When we do real-time data loading to HBase, we use put/putlist interface. After receiving put request, regionserver will write WAL, write data into memory store, flush memory store to disk-store, then compact files again and again. That precedure occupies too much resource and causing read/write performance decrease. To solve the problem, we provide a kind of near-line loading method and architecture, greatly increase the loading bandwidth, and decrease the influence to read operations. hbaseconasia2017 hbasecon hbase https://www.eventbrite.com/e/hbasecon-asia-2017-tickets-34935546159#

hbaseconasia2017: Large scale data near-line loading method and architecture

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Large scale data near-line loading
method and architecture
FiberHome Telecommunication
2017-7-19
/usr/bin/whoami
Shuaifeng Zhou(周帅锋):
• Big data research and development director ( Fiberhome 2013-)
• Software engineer (Huawei 2007-2013)
• Use and contribute to HBase since 2009
• sfzhou1791@fiberhome.com
Motivation1
Contents
Solution2
Optimization3
Tests4
Summarize5
HBase Realtime Data Loading
 WAL/Flush/Compact
Triple IO pressure
 Read/Write operations
share resource:
 Cpu
 Network
 Disk IO
 Handler
 Read performance
decrease too much when
write load is heavy
Why near-line data loading?
DelayScale
ReliableResource
Large scale data loading reliably with acceptable time delay and resource occupation
Billions write ops per
region server one day
Usually, several minutes
delay is acceptable for
customers
Resource occupied can
be limited under an
acceptable level
Write op can be
repeated
Optimistic failure
handling
HBase
Motivation1
Contents
Solution2
Optimization3
Tests4
Summarize5
Ad

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