SlideShare ist ein Scribd-Unternehmen logo
1 von 50
Downloaden Sie, um offline zu lesen
© 2018 Bloomberg Finance L.P. All rights reserved.
Serving Billions of
Queries in Millisecond
Latency
HBaseConAsia 2018
August 17, 2018
Biju Nair
bnair10@bloomberg.net
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Agenda
• Need for low latency
• HBase principles
• Modeling
• Implementation
• Monitoring and Tuning
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Bloomberg by the numbers
• Founded in 1981
• 325,000 subscribers in 170 countries
• Over 19,000 employees in 192 locations
• More News reporters than The New York Times + Washington Post +
Chicago Tribune
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Bloomberg Tech
• More than 5,000 software engineers (and growing)
• 100+ engineers and data scientists devoted to machine learning
• One of the largest private networks in the world
• 100B+ tick messages per day, with a peak of more than 10 million
messages/second
• 2M news stories ingested / published each day (that's >500 news stories
ingested/second)
• News content from 125K+ sources
• More than a billion messages (emails and IB chats) processed each day
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Bloomberg in a nutshell
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Data Storage and Retrieval
• Files
• VSAM
• Network
• Hierarchical
• Relational
• MPP
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Using RDBMS
• Use Case
• Entities and Relations
• Logical data model
• Physical data model
• Implementation and tuning
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
HBase Principles
• Ordered Key Value Store
• Distributed
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Key Value
Key-9999 Value-a
Key-9998 Value-b
Key-9997 Value-c
Key-9996 Value-d
…
…
Key-9995 Value-e
Key-9994 Value-f
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Ordered Key Value
Key-9999 Value-a
Key-9998 Value-b
Key-9997 Value-c
Key-9996 Value-d
…
…
Key-9995 Value-e
Key-9994 Value-a
Lexicographicorder
Key-9993 Value-g
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Distributed Order Key Value
Key-199 Value
Key-198 Value
Key-197 Value
Key-499 Value
…
Key-498 Value
Key-497 Value
ordered
…
Key-299 Value
…
Key-298 Value
Key-297 Value
ordered
…
…
…
Key-599 Value
…
Key-598 Value
Key-597 Value
…
Key-399 Value
…
Key-398 Value
Key-397 Value
…
Key-999 Value
…
Key-998 Value
Key-997 Value
…
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Abstraction
• Table row view
• Versioning
• ACIDity
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Table Row View
Key Value
Column Id ValueRow Id Timestamp
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Table Row View
Key11|col1|1234567 Value-A
Key11|col2|1234567 Value-B
Key11|col3|1234567 Value-C
Key11|col4|1234567 Value-D
Key11
Value-A Value-B Value-C
Col1 Col2 Col3
Value-D
Col4
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Versioning
Key11|col1|1234567 Value-A1
Key11|col1|1234566 Value-A
Key11|col2|1234567 Value-B
Key11|col3|1234567 Value-CC
Key11|col3|1234563 Value-C
Key11|col4|1234567 Value-DD
Key11|col4|1234560 Value-D1
Key11|col4|1234557 Value-D
Descendingorder
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
ACIDity
• Atomic at row level
• Consistent to a point in time before the request
• Isolation through MVCC (reads) and row locks (mutations)
• Durability is guaranteed for all successful mutations
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Data Modeling
• Fitness for key value store
— Can’t build relations
— No secondary indexes
— De-normalization
• Understand queries to design key
— Data Skew
— Query Skew
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Data Skew
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-a Value
Key-a Value
Key-a Value
Key-b Value
Key-b Value
Key-b Value
Key-a Value
Key-h Value
Key-h Value
Key-h Value
Key-d Value
Key-d Value
Key-d Value
Key-f Value
Key-f Value
Key-x Value
Key-x Value
Key-z Value
Key-z Value
Key-y Value
Key-y Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Data Skew
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-a Value
Key-a Value
Key-a Value
Key-b Value
Key-b Value
Key-b Value
Key-a Value
Key-h Value
Key-h Value
Key-h Value
Key-d Value
Key-d Value
Key-d Value
Key-f Value
Key-f Value
Key-x Value
Key-x Value
Key-z Value
Key-z Value
Key-y Value
Key-y Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Key-e Value
Hotspot
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Query Skew
Key-199 Value
Key-198 Value
Key-197 Value
Key-499 Value
…
Key-498 Value
Key-497 Value
…
Key-299 Value
…
Key-298 Value
Key-297 Value
…
…
…
Key-599 Value
…
Key-598 Value
Key-597 Value
…
Key-399 Value
…
Key-398 Value
Key-397 Value
…
Key-999 Value
…
Key-998 Value
Key-997 Value
…
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Query Skew
Key-199 Value
Key-198 Value
Key-197 Value
Key-499 Value
…
Key-498 Value
Key-497 Value
…
Key-299 Value
…
Key-298 Value
Key-297 Value
…
…
…
Key-599 Value
…
Key-598 Value
Key-597 Value
…
Key-399 Value
…
Key-398 Value
Key-397 Value
…
Key-999 Value
…
Key-998 Value
Key-997 Value
…
Queries
Queries
Queries
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Query Skew
Key-199 Value
Key-198 Value
Key-197 Value
Key-499 Value
…
Key-498 Value
Key-497 Value
…
Key-299 Value
…
Key-298 Value
Key-297 Value
…
…
…
Key-599 Value
…
Key-598 Value
Key-597 Value
…
Key-399 Value
…
Key-398 Value
Key-397 Value
…
Key-999 Value
…
Key-998 Value
Key-997 Value
…
Queries
Queries
Queries
Hotspot
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
HBase
Data Write
Memory
File System
WAL t1 t1 t1
Store files
Write
1
2
3
Block Block Block
Data Idx Blm
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
HBase
Data Read
Memstore
File System
WAL
Read
1
Block Cache
2
Block
t1 t1 t1
Store files
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Cache
• Pack more blocks into cache
— Block size
— Column Family
• Large cache
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Block Size and Cache Use
BlockCache
unuseduse
64 K Blocks
unuseduse
unuseduse unuseduse
unuseduse unuseduse
unuseduse unuseduse
unuseduse unuseduse
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Block Size and Cache Use
BlockCache
unuseduse
64 K Blocks
unuseduse
unuseduse unuseduse
unuseduse unuseduse
unuseduse unuseduse
unuseduse unuseduse
BlockCache
use
16 K Blocks
use
use use
use use
use use
use use
use use
use use use
use use
use use
use use use
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Block Size vs. Read Latency
BAvg 16.731 16.728 16.761 16.763 16.418 16.371 16.37 16.431 16.152 16.14 16.169 16.158 16.308 16.29 16.325 16.307 16.34 16.381 16.391 16.352
BMedian 14 14 14 14 13 13 13 13 15 15 15 15 13 13 13 13 13 13 13 13
B95% 41 41 41 41 41 41 41 41 43 43 43 43 40 40 40 40 41 41 41 41
B99% 55 55 55 55 54 54 54 54 55 55 55 55 54 54 54 54 54 54 55 54
B99.9% 71 71 71 71 70 70 70 70 67 67 67 67 71 70 70 71 71 71 71 70
BMax 545 1062 559 567 1075 1027 561 567 564 541 558 1062 1062 561 1075 1072 1067 563 1035 1032
Avg 3.002 5.362 5.361 5.357 6.419 6.369 6.405 6.383 6.188 6.196 6.182 6.174 6.246 6.264 6.268 6.253 5.194 5.207 5.219 3.031
Median 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
95% 10 15 15 15 18 18 18 18 18 18 17 17 18 18 18 18 15 15 15 10
99% 15 26 26 26 30 30 30 30 28 28 28 28 29 29 29 29 25 24 25 15
99.90% 26 41 41 41 45 45 45 45 43 43 43 43 44 44 44 44 41 41 41 26
Max 2261 127 185 102 90 106 92 102 93 106 119 114 89 140 132 82 81 150 93 1910
Get Performance (ms) – 64 K Block
Get Performance (ms) – 16 K Block
Note: Smaller block size increases index block size
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Block Size vs. Index Size
Idx Sz K Bloom K
266346 2368
247895 2240
225561 2096
253633 2368
224862 2016
225685 2096
16 K Blocks
Idx Sz K Bloom K
472058 2432
574239 2944
331899 1792
471362 2304
517272 2560
469543 2432
8 K Blocks
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Column Family
Key11|col1|1234567 Value-A1
Key11|col1|1234566 Value-A
Key11|col2|1234567 Value-B
Key11|col3|1234567 Value-CC
Key11|col3|1234563 Value-C
Key11|col4|1234567 Value-DD
Key11|col4|1234560 Value-D1
Key11|col4|1234557 Value-D
BlockCache
use use
use use
use use
use use
use use
use use
use use use
use use
use use
use use use
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Column Family
File System
t1:cf2 t1:cf2
Store files
t1:cf1 t1:cf1
cf1:col1 Timestamp cf2:col1 TimestampRow Id ValueValueRow Id
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Column Family
BlockCache
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1 cf1
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Column Family
BlockCache
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf1 cf1
BlockCache
cf1 cf1
cf1 cf1
cf1 cf1
cf1 cf2
cf1 cf2
cf1 cf1
cf1 cf1 cf1
cf1 cf1
cf2 cf1
cf1 cf2 cf1
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Compaction
File System
K-x K-x D-1
Store files
K-xK-xK-x
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Compaction
File System
K-x K-x D-1
Store files
K-xK-xK-x
File System
Store files
K-x
Compaction
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Compaction
• Part of regular HBase operations
• Minor Compaction
• Major Compaction
• Utilizes server and HBase resources
• Major compaction can be scheduled
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Short Circuit Read
HBase/DFS
Client
HDFS
File System
Data
TCP
HBase/DFS
Client
HDFS
File System
Data
TCP
Open
File
Pass
FD
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Garbage Collection
HBase Memstore
File System
WAL t1 t1 t1
Store filesRead
1
Block Cache
2
Block
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Garbage Collection
HBase Memstore
File System
WAL t1 t1 t1
Store filesRead
1
Block Cache
3
Block
Off-heap Cache Block
2
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Large Cache
Avg 2.693 2.814 2.836 2.842 2.812
Median 1 1 1 1 1
95% 8 8 8 8 8
99% 14 14 14 14 15
99.90% 20 20 20 20 20
99.99% 32 31 32 32 33
100.00% 313 319 315 376 341
Max latency 1049 1046 1048 1044 1235
61 GB of Cache
Avg 3.872 3.995 3.936 4.007 4.052
Median 1 1 1 1 1
95% 14 14 14 15 15
99% 20 20 20 20 20
99.90% 27 27 27 28 28
99.99% 36 36 36 37 37
100.00% 208 310 332 207 232
Max latency 1360 1906 1736 1359 1363
93 GB of Cache
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Garbage Collection
• Fine tune Garbage Collector
• For example, some CMS GC options to look at
— ExplicitGCInvokesConcurrent
— CMSInitiatingOccupancyFraction
— UseCMSInitiatingOccupancyOnly
— ParallelGCThreads
— UseParNewGC
• Log GC info which will help with tuning
— PrintGCDetails
— Loggc
— PrintTenuringDistribution
— …
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Region Replication
HMaster
RS1 RS2 RS3 RS4 RS5 RS6
system
ZK
T1 r1
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Region Replication
HMaster
RS1 RS2 RS3 RS4 RS5 RS6
system
ZK
T1 r1
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Region Replication
HMaster
RS1 RS2 RS3 RS4 RS5 RS6
system
ZK
T1 r1T1 r1
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Region Replication
• Requires changes to cluster configuration
— hbase.region.replica.replication.enabled
— hbase.regionserver.storefile.refresh.period (not the complete list)
• Need to specify region replication in table definition
— create 't1', 'f1', {REGION_REPLICATION => 2}
• Client needs to specify when to read secondary
— get1.setConsistency(Consistency.TIMELINE);
— hbase.client.primaryCallTimeout.get
— hbase.client.primaryCallTimeout.multiget
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Region Replication
Time (ms) readers totalQuery totalStale %age
3,000 512 1,520,207 0 0.00%
3,000 512 1,520,207 0 0.00%
3,000 512 1,520,207 0 0.00%
1,000 512 1,520,207 0 0.00%
1,000 512 1,520,207 0 0.00%
1,000 512 1,520,207 0 0.00%
100 512 1,520,207 5,101 0.34%
100 512 1,520,207 1,476 0.10%
100 512 1,520,207 74 0.00%
50 512 1,520,207 6,173 0.41%
50 512 1,520,207 4,785 0.31%
50 512 1,520,207 5,263 0.35%
10 512 1,520,207 22,518 1.48%
10 512 1,520,207 16,818 1.11%
10 512 1,520,207 19,050 1.25%
PrimaryCall Timeout Vs Stale Calls
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Application
• Table pre-split
• Connection reuse
• No read cache/scan cache/batch requests
• Bulk load instead of Put/Batch Mutate
• Column Identifiers
• Code on server
— Co-processor
— Filters
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Monitoring
• Cache hit ratio
• Data locality
• GC pause
• Compactions
• Call queue
• Read latencies
• Server metrics
© 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved.
Summary
• Familiarize system principles
• Use DB development lifecycle
• Ascertain natural fitness for HBase
© 2018 Bloomberg Finance L.P. All rights reserved.
Thank You!
Reference: http://hbase.apache.org
Connect with Bloomberg’s Hadoop Team:
hadoop@bloomberg.net

Weitere ähnliche Inhalte

Ähnlich wie HBaseConAsia2018 Track3-1: Serving billions of queries in millisecond latencies

InfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxData
InfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxDataInfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxData
InfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxDataInfluxData
 
Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...
Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...
Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...confluent
 
Moneyball: Using Advanced Account Insights for Effective ABM Activation
Moneyball: Using Advanced Account Insights for Effective ABM ActivationMoneyball: Using Advanced Account Insights for Effective ABM Activation
Moneyball: Using Advanced Account Insights for Effective ABM ActivationEngagio
 
Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...
Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...
Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...confluent
 
Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...
Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...
Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...Lucidworks
 
How Financial Services can Save On File Storage
How Financial Services can Save On File Storage How Financial Services can Save On File Storage
How Financial Services can Save On File Storage Charly Mostert
 
From Startup to Recognized IoT Leader
From Startup to Recognized IoT Leader From Startup to Recognized IoT Leader
From Startup to Recognized IoT Leader Amazon Web Services
 
HBase Internals And Operations
HBase Internals And OperationsHBase Internals And Operations
HBase Internals And OperationsBiju Nair
 
Augmented OLAP for Big Data
Augmented OLAP for Big DataAugmented OLAP for Big Data
Augmented OLAP for Big DataLuke Han
 
Augmented OLAP Analytics for Big Data
Augmented OLAP Analytics for Big DataAugmented OLAP Analytics for Big Data
Augmented OLAP Analytics for Big DataTyler Wishnoff
 
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...M&E Leadership Session: The State of the Industry, What's New from AWS for M&...
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...Amazon Web Services
 
From Data To Insights
From Data To Insights From Data To Insights
From Data To Insights Orit Alul
 
Building csm while going from on premise to saa s
Building csm while going from on premise to saa sBuilding csm while going from on premise to saa s
Building csm while going from on premise to saa sJessica Osborn
 
AWS 金融服務概覽與區塊鍊案例分享
AWS 金融服務概覽與區塊鍊案例分享AWS 金融服務概覽與區塊鍊案例分享
AWS 金融服務概覽與區塊鍊案例分享Amazon Web Services
 
Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...
Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...
Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...Amazon Web Services
 
Gimel at Dataworks Summit San Jose 2018
Gimel at Dataworks Summit San Jose 2018Gimel at Dataworks Summit San Jose 2018
Gimel at Dataworks Summit San Jose 2018Romit Mehta
 
Dataworks | 2018-06-20 | Gimel data platform
Dataworks | 2018-06-20 | Gimel data platformDataworks | 2018-06-20 | Gimel data platform
Dataworks | 2018-06-20 | Gimel data platformDeepak Chandramouli
 
Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...Hannah Flynn
 
Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...Aggregage
 
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...Amazon Web Services
 

Ähnlich wie HBaseConAsia2018 Track3-1: Serving billions of queries in millisecond latencies (20)

InfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxData
InfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxDataInfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxData
InfluxDB Enterprise Architectural Patterns | Craig Hobbs | InfluxData
 
Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...
Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...
Building a Data Subscription Service with Kafka Connect (Danica Fine & Ajay V...
 
Moneyball: Using Advanced Account Insights for Effective ABM Activation
Moneyball: Using Advanced Account Insights for Effective ABM ActivationMoneyball: Using Advanced Account Insights for Effective ABM Activation
Moneyball: Using Advanced Account Insights for Effective ABM Activation
 
Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...
Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...
Replaying KStreams Apps Using State Snapshots (Nishchay Sinha & Yan Wang, Blo...
 
Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...
Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...
Learning to Rank: From Theory to Production - Malvina Josephidou & Diego Cecc...
 
How Financial Services can Save On File Storage
How Financial Services can Save On File Storage How Financial Services can Save On File Storage
How Financial Services can Save On File Storage
 
From Startup to Recognized IoT Leader
From Startup to Recognized IoT Leader From Startup to Recognized IoT Leader
From Startup to Recognized IoT Leader
 
HBase Internals And Operations
HBase Internals And OperationsHBase Internals And Operations
HBase Internals And Operations
 
Augmented OLAP for Big Data
Augmented OLAP for Big DataAugmented OLAP for Big Data
Augmented OLAP for Big Data
 
Augmented OLAP Analytics for Big Data
Augmented OLAP Analytics for Big DataAugmented OLAP Analytics for Big Data
Augmented OLAP Analytics for Big Data
 
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...M&E Leadership Session: The State of the Industry, What's New from AWS for M&...
M&E Leadership Session: The State of the Industry, What's New from AWS for M&...
 
From Data To Insights
From Data To Insights From Data To Insights
From Data To Insights
 
Building csm while going from on premise to saa s
Building csm while going from on premise to saa sBuilding csm while going from on premise to saa s
Building csm while going from on premise to saa s
 
AWS 金融服務概覽與區塊鍊案例分享
AWS 金融服務概覽與區塊鍊案例分享AWS 金融服務概覽與區塊鍊案例分享
AWS 金融服務概覽與區塊鍊案例分享
 
Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...
Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...
Building SRE from Scratch at Coinbase during Hypergrowth (DEV315-S) - AWS re:...
 
Gimel at Dataworks Summit San Jose 2018
Gimel at Dataworks Summit San Jose 2018Gimel at Dataworks Summit San Jose 2018
Gimel at Dataworks Summit San Jose 2018
 
Dataworks | 2018-06-20 | Gimel data platform
Dataworks | 2018-06-20 | Gimel data platformDataworks | 2018-06-20 | Gimel data platform
Dataworks | 2018-06-20 | Gimel data platform
 
Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...
 
Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...Modern Product Data Workflows: How King Crushes New Product Development using...
Modern Product Data Workflows: How King Crushes New Product Development using...
 
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...
Hollywood's Cloud-Based Content Lakes: Modernized Media Archives (MAE203) - A...
 

Mehr von Michael Stack

hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud
hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloudhbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud
hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on CloudMichael Stack
 
hbaseconasia2019 Recent work on HBase at Pinterest
hbaseconasia2019 Recent work on HBase at Pinteresthbaseconasia2019 Recent work on HBase at Pinterest
hbaseconasia2019 Recent work on HBase at PinterestMichael Stack
 
hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd
hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltdhbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd
hbaseconasia2019 Phoenix Practice in China Life Insurance Co., LtdMichael Stack
 
hbaseconasia2019 HBase at Didi
hbaseconasia2019 HBase at Didihbaseconasia2019 HBase at Didi
hbaseconasia2019 HBase at DidiMichael Stack
 
hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...
hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...
hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...Michael Stack
 
hbaseconasia2019 HBase at Tencent
hbaseconasia2019 HBase at Tencenthbaseconasia2019 HBase at Tencent
hbaseconasia2019 HBase at TencentMichael Stack
 
hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...
hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...
hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...Michael Stack
 
hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...
hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...
hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...Michael Stack
 
hbaseconasia2019 Pharos as a Pluggable Secondary Index Component
hbaseconasia2019 Pharos as a Pluggable Secondary Index Componenthbaseconasia2019 Pharos as a Pluggable Secondary Index Component
hbaseconasia2019 Pharos as a Pluggable Secondary Index ComponentMichael Stack
 
hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba
hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibabahbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba
hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at AlibabaMichael Stack
 
hbaseconasia2019 OpenTSDB at Xiaomi
hbaseconasia2019 OpenTSDB at Xiaomihbaseconasia2019 OpenTSDB at Xiaomi
hbaseconasia2019 OpenTSDB at XiaomiMichael Stack
 
hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark
hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Sparkhbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark
hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and SparkMichael Stack
 
hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBasehbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBaseMichael Stack
 
hbaseconasia2019 Distributed Bitmap Index Solution
hbaseconasia2019 Distributed Bitmap Index Solutionhbaseconasia2019 Distributed Bitmap Index Solution
hbaseconasia2019 Distributed Bitmap Index SolutionMichael Stack
 
hbaseconasia2019 HBase Bucket Cache on Persistent Memory
hbaseconasia2019 HBase Bucket Cache on Persistent Memoryhbaseconasia2019 HBase Bucket Cache on Persistent Memory
hbaseconasia2019 HBase Bucket Cache on Persistent MemoryMichael Stack
 
hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL
hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACLhbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL
hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACLMichael Stack
 
hbaseconasia2019 BDS: A data synchronization platform for HBase
hbaseconasia2019 BDS: A data synchronization platform for HBasehbaseconasia2019 BDS: A data synchronization platform for HBase
hbaseconasia2019 BDS: A data synchronization platform for HBaseMichael Stack
 
hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...
hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...
hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...Michael Stack
 
hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...
hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...
hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...Michael Stack
 
HBaseConAsia2019 Keynote
HBaseConAsia2019 KeynoteHBaseConAsia2019 Keynote
HBaseConAsia2019 KeynoteMichael Stack
 

Mehr von Michael Stack (20)

hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud
hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloudhbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud
hbaseconasia2019 HBase Table Monitoring and Troubleshooting System on Cloud
 
hbaseconasia2019 Recent work on HBase at Pinterest
hbaseconasia2019 Recent work on HBase at Pinteresthbaseconasia2019 Recent work on HBase at Pinterest
hbaseconasia2019 Recent work on HBase at Pinterest
 
hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd
hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltdhbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd
hbaseconasia2019 Phoenix Practice in China Life Insurance Co., Ltd
 
hbaseconasia2019 HBase at Didi
hbaseconasia2019 HBase at Didihbaseconasia2019 HBase at Didi
hbaseconasia2019 HBase at Didi
 
hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...
hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...
hbaseconasia2019 The Practice in trillion-level Video Storage and billion-lev...
 
hbaseconasia2019 HBase at Tencent
hbaseconasia2019 HBase at Tencenthbaseconasia2019 HBase at Tencent
hbaseconasia2019 HBase at Tencent
 
hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...
hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...
hbaseconasia2019 Spatio temporal Data Management based on Ali-HBase Ganos and...
 
hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...
hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...
hbaseconasia2019 Bridging the Gap between Big Data System Software Stack and ...
 
hbaseconasia2019 Pharos as a Pluggable Secondary Index Component
hbaseconasia2019 Pharos as a Pluggable Secondary Index Componenthbaseconasia2019 Pharos as a Pluggable Secondary Index Component
hbaseconasia2019 Pharos as a Pluggable Secondary Index Component
 
hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba
hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibabahbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba
hbaseconasia2019 Phoenix Improvements and Practices on Cloud HBase at Alibaba
 
hbaseconasia2019 OpenTSDB at Xiaomi
hbaseconasia2019 OpenTSDB at Xiaomihbaseconasia2019 OpenTSDB at Xiaomi
hbaseconasia2019 OpenTSDB at Xiaomi
 
hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark
hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Sparkhbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark
hbaseconasia2019 BigData NoSQL System: ApsaraDB, HBase and Spark
 
hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBasehbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
hbaseconasia2019 Test-suite for Automating Data-consistency checks on HBase
 
hbaseconasia2019 Distributed Bitmap Index Solution
hbaseconasia2019 Distributed Bitmap Index Solutionhbaseconasia2019 Distributed Bitmap Index Solution
hbaseconasia2019 Distributed Bitmap Index Solution
 
hbaseconasia2019 HBase Bucket Cache on Persistent Memory
hbaseconasia2019 HBase Bucket Cache on Persistent Memoryhbaseconasia2019 HBase Bucket Cache on Persistent Memory
hbaseconasia2019 HBase Bucket Cache on Persistent Memory
 
hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL
hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACLhbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL
hbaseconasia2019 The Procedure v2 Implementation of WAL Splitting and ACL
 
hbaseconasia2019 BDS: A data synchronization platform for HBase
hbaseconasia2019 BDS: A data synchronization platform for HBasehbaseconasia2019 BDS: A data synchronization platform for HBase
hbaseconasia2019 BDS: A data synchronization platform for HBase
 
hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...
hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...
hbaseconasia2019 Further GC optimization for HBase 2.x: Reading HFileBlock in...
 
hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...
hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...
hbaseconasia2019 HBCK2: Concepts, trends, and recipes for fixing issues in HB...
 
HBaseConAsia2019 Keynote
HBaseConAsia2019 KeynoteHBaseConAsia2019 Keynote
HBaseConAsia2019 Keynote
 

Kürzlich hochgeladen

Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girlsRussian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girlsMonica Sydney
 
Mira Road Housewife Call Girls 07506202331, Nalasopara Call Girls
Mira Road Housewife Call Girls 07506202331, Nalasopara Call GirlsMira Road Housewife Call Girls 07506202331, Nalasopara Call Girls
Mira Road Housewife Call Girls 07506202331, Nalasopara Call GirlsPriya Reddy
 
在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查ydyuyu
 
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac RoomVip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Roommeghakumariji156
 
pdfcoffee.com_business-ethics-q3m7-pdf-free.pdf
pdfcoffee.com_business-ethics-q3m7-pdf-free.pdfpdfcoffee.com_business-ethics-q3m7-pdf-free.pdf
pdfcoffee.com_business-ethics-q3m7-pdf-free.pdfJOHNBEBONYAP1
 
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...gajnagarg
 
20240507 QFM013 Machine Intelligence Reading List April 2024.pdf
20240507 QFM013 Machine Intelligence Reading List April 2024.pdf20240507 QFM013 Machine Intelligence Reading List April 2024.pdf
20240507 QFM013 Machine Intelligence Reading List April 2024.pdfMatthew Sinclair
 
Indian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi EscortsIndian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi EscortsMonica Sydney
 
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdfMatthew Sinclair
 
Call girls Service in Ajman 0505086370 Ajman call girls
Call girls Service in Ajman 0505086370 Ajman call girlsCall girls Service in Ajman 0505086370 Ajman call girls
Call girls Service in Ajman 0505086370 Ajman call girlsMonica Sydney
 
一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样
一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样
一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样ayvbos
 
Russian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi EscortsRussian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi EscortsMonica Sydney
 
Best SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency DallasBest SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency DallasDigicorns Technologies
 
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...kajalverma014
 
Local Call Girls in Seoni 9332606886 HOT & SEXY Models beautiful and charmin...
Local Call Girls in Seoni  9332606886 HOT & SEXY Models beautiful and charmin...Local Call Girls in Seoni  9332606886 HOT & SEXY Models beautiful and charmin...
Local Call Girls in Seoni 9332606886 HOT & SEXY Models beautiful and charmin...kumargunjan9515
 
一比一原版奥兹学院毕业证如何办理
一比一原版奥兹学院毕业证如何办理一比一原版奥兹学院毕业证如何办理
一比一原版奥兹学院毕业证如何办理F
 
哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查
哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查
哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查ydyuyu
 
一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制
一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制
一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制pxcywzqs
 
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样ayvbos
 

Kürzlich hochgeladen (20)

Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girlsRussian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
Russian Call girls in Abu Dhabi 0508644382 Abu Dhabi Call girls
 
Mira Road Housewife Call Girls 07506202331, Nalasopara Call Girls
Mira Road Housewife Call Girls 07506202331, Nalasopara Call GirlsMira Road Housewife Call Girls 07506202331, Nalasopara Call Girls
Mira Road Housewife Call Girls 07506202331, Nalasopara Call Girls
 
在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查在线制作约克大学毕业证(yu毕业证)在读证明认证可查
在线制作约克大学毕业证(yu毕业证)在读证明认证可查
 
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac RoomVip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
Vip Firozabad Phone 8250092165 Escorts Service At 6k To 30k Along With Ac Room
 
pdfcoffee.com_business-ethics-q3m7-pdf-free.pdf
pdfcoffee.com_business-ethics-q3m7-pdf-free.pdfpdfcoffee.com_business-ethics-q3m7-pdf-free.pdf
pdfcoffee.com_business-ethics-q3m7-pdf-free.pdf
 
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
Top profile Call Girls In Dindigul [ 7014168258 ] Call Me For Genuine Models ...
 
20240507 QFM013 Machine Intelligence Reading List April 2024.pdf
20240507 QFM013 Machine Intelligence Reading List April 2024.pdf20240507 QFM013 Machine Intelligence Reading List April 2024.pdf
20240507 QFM013 Machine Intelligence Reading List April 2024.pdf
 
Indian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi EscortsIndian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
Indian Escort in Abu DHabi 0508644382 Abu Dhabi Escorts
 
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
20240509 QFM015 Engineering Leadership Reading List April 2024.pdf
 
Call girls Service in Ajman 0505086370 Ajman call girls
Call girls Service in Ajman 0505086370 Ajman call girlsCall girls Service in Ajman 0505086370 Ajman call girls
Call girls Service in Ajman 0505086370 Ajman call girls
 
一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样
一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样
一比一原版(Flinders毕业证书)弗林德斯大学毕业证原件一模一样
 
Russian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi EscortsRussian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
Russian Escort Abu Dhabi 0503464457 Abu DHabi Escorts
 
Best SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency DallasBest SEO Services Company in Dallas | Best SEO Agency Dallas
Best SEO Services Company in Dallas | Best SEO Agency Dallas
 
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
best call girls in Hyderabad Finest Escorts Service 📞 9352988975 📞 Available ...
 
Local Call Girls in Seoni 9332606886 HOT & SEXY Models beautiful and charmin...
Local Call Girls in Seoni  9332606886 HOT & SEXY Models beautiful and charmin...Local Call Girls in Seoni  9332606886 HOT & SEXY Models beautiful and charmin...
Local Call Girls in Seoni 9332606886 HOT & SEXY Models beautiful and charmin...
 
call girls in Anand Vihar (delhi) call me [🔝9953056974🔝] escort service 24X7
call girls in Anand Vihar (delhi) call me [🔝9953056974🔝] escort service 24X7call girls in Anand Vihar (delhi) call me [🔝9953056974🔝] escort service 24X7
call girls in Anand Vihar (delhi) call me [🔝9953056974🔝] escort service 24X7
 
一比一原版奥兹学院毕业证如何办理
一比一原版奥兹学院毕业证如何办理一比一原版奥兹学院毕业证如何办理
一比一原版奥兹学院毕业证如何办理
 
哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查
哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查
哪里办理美国迈阿密大学毕业证(本硕)umiami在读证明存档可查
 
一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制
一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制
一比一原版(Offer)康考迪亚大学毕业证学位证靠谱定制
 
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
一比一原版(Curtin毕业证书)科廷大学毕业证原件一模一样
 

HBaseConAsia2018 Track3-1: Serving billions of queries in millisecond latencies

  • 1. © 2018 Bloomberg Finance L.P. All rights reserved. Serving Billions of Queries in Millisecond Latency HBaseConAsia 2018 August 17, 2018 Biju Nair bnair10@bloomberg.net
  • 2. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Agenda • Need for low latency • HBase principles • Modeling • Implementation • Monitoring and Tuning
  • 3. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Bloomberg by the numbers • Founded in 1981 • 325,000 subscribers in 170 countries • Over 19,000 employees in 192 locations • More News reporters than The New York Times + Washington Post + Chicago Tribune
  • 4. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Bloomberg Tech • More than 5,000 software engineers (and growing) • 100+ engineers and data scientists devoted to machine learning • One of the largest private networks in the world • 100B+ tick messages per day, with a peak of more than 10 million messages/second • 2M news stories ingested / published each day (that's >500 news stories ingested/second) • News content from 125K+ sources • More than a billion messages (emails and IB chats) processed each day
  • 5. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Bloomberg in a nutshell
  • 6. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Data Storage and Retrieval • Files • VSAM • Network • Hierarchical • Relational • MPP
  • 7. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Using RDBMS • Use Case • Entities and Relations • Logical data model • Physical data model • Implementation and tuning
  • 8. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. HBase Principles • Ordered Key Value Store • Distributed
  • 9. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Key Value Key-9999 Value-a Key-9998 Value-b Key-9997 Value-c Key-9996 Value-d … … Key-9995 Value-e Key-9994 Value-f
  • 10. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Ordered Key Value Key-9999 Value-a Key-9998 Value-b Key-9997 Value-c Key-9996 Value-d … … Key-9995 Value-e Key-9994 Value-a Lexicographicorder Key-9993 Value-g
  • 11. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Distributed Order Key Value Key-199 Value Key-198 Value Key-197 Value Key-499 Value … Key-498 Value Key-497 Value ordered … Key-299 Value … Key-298 Value Key-297 Value ordered … … … Key-599 Value … Key-598 Value Key-597 Value … Key-399 Value … Key-398 Value Key-397 Value … Key-999 Value … Key-998 Value Key-997 Value …
  • 12. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Abstraction • Table row view • Versioning • ACIDity
  • 13. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Table Row View Key Value Column Id ValueRow Id Timestamp
  • 14. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Table Row View Key11|col1|1234567 Value-A Key11|col2|1234567 Value-B Key11|col3|1234567 Value-C Key11|col4|1234567 Value-D Key11 Value-A Value-B Value-C Col1 Col2 Col3 Value-D Col4
  • 15. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Versioning Key11|col1|1234567 Value-A1 Key11|col1|1234566 Value-A Key11|col2|1234567 Value-B Key11|col3|1234567 Value-CC Key11|col3|1234563 Value-C Key11|col4|1234567 Value-DD Key11|col4|1234560 Value-D1 Key11|col4|1234557 Value-D Descendingorder
  • 16. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. ACIDity • Atomic at row level • Consistent to a point in time before the request • Isolation through MVCC (reads) and row locks (mutations) • Durability is guaranteed for all successful mutations
  • 17. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Data Modeling • Fitness for key value store — Can’t build relations — No secondary indexes — De-normalization • Understand queries to design key — Data Skew — Query Skew
  • 18. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Data Skew Key-e Value Key-e Value Key-e Value Key-e Value Key-a Value Key-a Value Key-a Value Key-b Value Key-b Value Key-b Value Key-a Value Key-h Value Key-h Value Key-h Value Key-d Value Key-d Value Key-d Value Key-f Value Key-f Value Key-x Value Key-x Value Key-z Value Key-z Value Key-y Value Key-y Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value
  • 19. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Data Skew Key-e Value Key-e Value Key-e Value Key-e Value Key-a Value Key-a Value Key-a Value Key-b Value Key-b Value Key-b Value Key-a Value Key-h Value Key-h Value Key-h Value Key-d Value Key-d Value Key-d Value Key-f Value Key-f Value Key-x Value Key-x Value Key-z Value Key-z Value Key-y Value Key-y Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Key-e Value Hotspot
  • 20. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Query Skew Key-199 Value Key-198 Value Key-197 Value Key-499 Value … Key-498 Value Key-497 Value … Key-299 Value … Key-298 Value Key-297 Value … … … Key-599 Value … Key-598 Value Key-597 Value … Key-399 Value … Key-398 Value Key-397 Value … Key-999 Value … Key-998 Value Key-997 Value …
  • 21. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Query Skew Key-199 Value Key-198 Value Key-197 Value Key-499 Value … Key-498 Value Key-497 Value … Key-299 Value … Key-298 Value Key-297 Value … … … Key-599 Value … Key-598 Value Key-597 Value … Key-399 Value … Key-398 Value Key-397 Value … Key-999 Value … Key-998 Value Key-997 Value … Queries Queries Queries
  • 22. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Query Skew Key-199 Value Key-198 Value Key-197 Value Key-499 Value … Key-498 Value Key-497 Value … Key-299 Value … Key-298 Value Key-297 Value … … … Key-599 Value … Key-598 Value Key-597 Value … Key-399 Value … Key-398 Value Key-397 Value … Key-999 Value … Key-998 Value Key-997 Value … Queries Queries Queries Hotspot
  • 23. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. HBase Data Write Memory File System WAL t1 t1 t1 Store files Write 1 2 3 Block Block Block Data Idx Blm
  • 24. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. HBase Data Read Memstore File System WAL Read 1 Block Cache 2 Block t1 t1 t1 Store files
  • 25. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Cache • Pack more blocks into cache — Block size — Column Family • Large cache
  • 26. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Block Size and Cache Use BlockCache unuseduse 64 K Blocks unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse
  • 27. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Block Size and Cache Use BlockCache unuseduse 64 K Blocks unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse unuseduse BlockCache use 16 K Blocks use use use use use use use use use use use use use use use use use use use use use
  • 28. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Block Size vs. Read Latency BAvg 16.731 16.728 16.761 16.763 16.418 16.371 16.37 16.431 16.152 16.14 16.169 16.158 16.308 16.29 16.325 16.307 16.34 16.381 16.391 16.352 BMedian 14 14 14 14 13 13 13 13 15 15 15 15 13 13 13 13 13 13 13 13 B95% 41 41 41 41 41 41 41 41 43 43 43 43 40 40 40 40 41 41 41 41 B99% 55 55 55 55 54 54 54 54 55 55 55 55 54 54 54 54 54 54 55 54 B99.9% 71 71 71 71 70 70 70 70 67 67 67 67 71 70 70 71 71 71 71 70 BMax 545 1062 559 567 1075 1027 561 567 564 541 558 1062 1062 561 1075 1072 1067 563 1035 1032 Avg 3.002 5.362 5.361 5.357 6.419 6.369 6.405 6.383 6.188 6.196 6.182 6.174 6.246 6.264 6.268 6.253 5.194 5.207 5.219 3.031 Median 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 95% 10 15 15 15 18 18 18 18 18 18 17 17 18 18 18 18 15 15 15 10 99% 15 26 26 26 30 30 30 30 28 28 28 28 29 29 29 29 25 24 25 15 99.90% 26 41 41 41 45 45 45 45 43 43 43 43 44 44 44 44 41 41 41 26 Max 2261 127 185 102 90 106 92 102 93 106 119 114 89 140 132 82 81 150 93 1910 Get Performance (ms) – 64 K Block Get Performance (ms) – 16 K Block Note: Smaller block size increases index block size
  • 29. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Block Size vs. Index Size Idx Sz K Bloom K 266346 2368 247895 2240 225561 2096 253633 2368 224862 2016 225685 2096 16 K Blocks Idx Sz K Bloom K 472058 2432 574239 2944 331899 1792 471362 2304 517272 2560 469543 2432 8 K Blocks
  • 30. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Column Family Key11|col1|1234567 Value-A1 Key11|col1|1234566 Value-A Key11|col2|1234567 Value-B Key11|col3|1234567 Value-CC Key11|col3|1234563 Value-C Key11|col4|1234567 Value-DD Key11|col4|1234560 Value-D1 Key11|col4|1234557 Value-D BlockCache use use use use use use use use use use use use use use use use use use use use use use
  • 31. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Column Family File System t1:cf2 t1:cf2 Store files t1:cf1 t1:cf1 cf1:col1 Timestamp cf2:col1 TimestampRow Id ValueValueRow Id
  • 32. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Column Family BlockCache cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1
  • 33. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Column Family BlockCache cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf1 BlockCache cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf2 cf1 cf2 cf1 cf1 cf1 cf1 cf1 cf1 cf1 cf2 cf1 cf1 cf2 cf1
  • 34. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Compaction File System K-x K-x D-1 Store files K-xK-xK-x
  • 35. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Compaction File System K-x K-x D-1 Store files K-xK-xK-x File System Store files K-x Compaction
  • 36. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Compaction • Part of regular HBase operations • Minor Compaction • Major Compaction • Utilizes server and HBase resources • Major compaction can be scheduled
  • 37. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Short Circuit Read HBase/DFS Client HDFS File System Data TCP HBase/DFS Client HDFS File System Data TCP Open File Pass FD
  • 38. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Garbage Collection HBase Memstore File System WAL t1 t1 t1 Store filesRead 1 Block Cache 2 Block
  • 39. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Garbage Collection HBase Memstore File System WAL t1 t1 t1 Store filesRead 1 Block Cache 3 Block Off-heap Cache Block 2
  • 40. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Large Cache Avg 2.693 2.814 2.836 2.842 2.812 Median 1 1 1 1 1 95% 8 8 8 8 8 99% 14 14 14 14 15 99.90% 20 20 20 20 20 99.99% 32 31 32 32 33 100.00% 313 319 315 376 341 Max latency 1049 1046 1048 1044 1235 61 GB of Cache Avg 3.872 3.995 3.936 4.007 4.052 Median 1 1 1 1 1 95% 14 14 14 15 15 99% 20 20 20 20 20 99.90% 27 27 27 28 28 99.99% 36 36 36 37 37 100.00% 208 310 332 207 232 Max latency 1360 1906 1736 1359 1363 93 GB of Cache
  • 41. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Garbage Collection • Fine tune Garbage Collector • For example, some CMS GC options to look at — ExplicitGCInvokesConcurrent — CMSInitiatingOccupancyFraction — UseCMSInitiatingOccupancyOnly — ParallelGCThreads — UseParNewGC • Log GC info which will help with tuning — PrintGCDetails — Loggc — PrintTenuringDistribution — …
  • 42. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Region Replication HMaster RS1 RS2 RS3 RS4 RS5 RS6 system ZK T1 r1
  • 43. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Region Replication HMaster RS1 RS2 RS3 RS4 RS5 RS6 system ZK T1 r1
  • 44. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Region Replication HMaster RS1 RS2 RS3 RS4 RS5 RS6 system ZK T1 r1T1 r1
  • 45. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Region Replication • Requires changes to cluster configuration — hbase.region.replica.replication.enabled — hbase.regionserver.storefile.refresh.period (not the complete list) • Need to specify region replication in table definition — create 't1', 'f1', {REGION_REPLICATION => 2} • Client needs to specify when to read secondary — get1.setConsistency(Consistency.TIMELINE); — hbase.client.primaryCallTimeout.get — hbase.client.primaryCallTimeout.multiget
  • 46. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Region Replication Time (ms) readers totalQuery totalStale %age 3,000 512 1,520,207 0 0.00% 3,000 512 1,520,207 0 0.00% 3,000 512 1,520,207 0 0.00% 1,000 512 1,520,207 0 0.00% 1,000 512 1,520,207 0 0.00% 1,000 512 1,520,207 0 0.00% 100 512 1,520,207 5,101 0.34% 100 512 1,520,207 1,476 0.10% 100 512 1,520,207 74 0.00% 50 512 1,520,207 6,173 0.41% 50 512 1,520,207 4,785 0.31% 50 512 1,520,207 5,263 0.35% 10 512 1,520,207 22,518 1.48% 10 512 1,520,207 16,818 1.11% 10 512 1,520,207 19,050 1.25% PrimaryCall Timeout Vs Stale Calls
  • 47. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Application • Table pre-split • Connection reuse • No read cache/scan cache/batch requests • Bulk load instead of Put/Batch Mutate • Column Identifiers • Code on server — Co-processor — Filters
  • 48. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Monitoring • Cache hit ratio • Data locality • GC pause • Compactions • Call queue • Read latencies • Server metrics
  • 49. © 2018 Bloomberg Finance L.P. All rights reserved.© 2018 Bloomberg Finance L.P. All rights reserved. Summary • Familiarize system principles • Use DB development lifecycle • Ascertain natural fitness for HBase
  • 50. © 2018 Bloomberg Finance L.P. All rights reserved. Thank You! Reference: http://hbase.apache.org Connect with Bloomberg’s Hadoop Team: hadoop@bloomberg.net