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SSDs EXCEL
IN BIG DATA
ARCHITECTURE
SSDs EXCEL
IN BIG DATA
ARCHITECTURE
Boosting cost/performance with SSDs is all about
LOCATION, LOCATION, LOCATION
Here are 8 critical spots in big
data architecture....
SCALE UP
One larger multicore,
all-SSD node in a
Hadoop cluster can
take on bigger jobs or
chaining, freeing up
smaller nodes for
easier jobs1
VIRTUALIZATION
SSDs mitigate ill effects
of smaller I/O blocks
and larger number of
requests in Xen 2
MAP REDUCE
Targeting intermediate
shuffle results produced
by MapReduce
algorithms at an SSD
reduces severe loads on
overwhelmed HDDs 3
SPILLING
RDDS
Spark running on
Amazon EC2
nodes backed by
Amazon S3
all-SSD storage
sets records 7
HYBRID
DATABASE
Keeping smaller files
and indices in RAM,
with larger files
stored on SSDs,
speeds up NoSQL 8
1
2
5
4
3
1
2
5
TIERED
STORAGE
Aiming more HDFS
requests at PCIe SSDs in
a hybrid cluster increases
average I/O rate 4
SMALL
“HOT” FILES
Caching Facebook messages
on an SSD triples HBase
performance through
reduced latency 5
TIGHTLY
COUPLED
MIT tests FPGA fabric and
local ARM cores on SSDs
to pre-process data and
speed searches 6
6 7 86 7 8
4
3
OPENOPEN
TOLLSTOLLSTOLLSTOLLS
1 <Scale Up>
“Scale-up vs Scale-out for Hadoop: Time to rethink?”, Appuswamy et al, Microsoft
Research, presented at SoCC ‘13, October 2013,
http://www.msr-waypoint.com/pubs/204499/a20-appuswamy.pdf
2 <Virtualization>
“Performance Implications of SSDs in Virtualized Hadoop Clusters”, Ahn et al, Samsung
Electronics, presented at IEEE BigData Congress, June 2014,
http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6906832
3 <MapReduce>
“The Truth About MapReduce Performance on SSDs”, Karthik Kambatla and Yanpei
Chen, Cloudera Inc. and Purdue University, presented at LISA 14 sponsored by USENIX,
November 2014,
https://www.usenix.org/conference/lisa14/conference-program/presentation/kambatla
4 <Tiered Storage>
“hatS: A Heterogeneity-Aware Tiered Storage for Hadoop”. Krish et al,
Virginia Tech, presented at IEEE/ACM CCGrid2014, May 2014,
http://people.cs.vt.edu/butta/docs/ccgrid2014-hats.pdf
5 <Small, "Hot" Files>
“Analysis of HDFS under HBase: A Facebook Messages Case Study”,
Harter et al, Facebook Inc. and University of Wisconsin, Madison,
presented at FAST ’14 sponsored by USENIX, February 2014,
http://research.cs.wisc.edu/adsl/Publications/fbmessages-fast14.pdf
6 <Tightly Coupled>
“Cutting cost and power consumption for big data”, Larry Hardesty,
Massachusetts Institute of Technology, July 10, 2015,
http://news.mit.edu/2015/cutting-cost-power-big-data-0710
7 <Spilling RDDs>
“Spark the fastest open source engine for sorting a petabyte”,
Databricks, November 2014,
https://databricks.com/blog/2014/10/10/spark-petabyte-sort.html
8 <Hybrid Database>
Aerospike web site, http://www.aerospike.com/flash-optimized/
BIG DATA CLUSTERS WITH SSDS IN
CRITICAL LOCATIONS COMPLETE
MORE REQUESTS,
BIG DATA CLUSTERS WITH SSDS IN
CRITICAL LOCATIONS COMPLETE
MORE REQUESTS,
SSDs with V-NAND unlock
big data performance with:
For more details on findings from these research
studies samsung.com/enterprisessd
1 2
HIGHER
IOPS
LOWER
LATENCY
MORE
DWPD
READ THE WHITE PAPER TO LEARN MORE

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SSDs Excel in Big Data Architecture

  • 1. SSDs EXCEL IN BIG DATA ARCHITECTURE SSDs EXCEL IN BIG DATA ARCHITECTURE Boosting cost/performance with SSDs is all about LOCATION, LOCATION, LOCATION Here are 8 critical spots in big data architecture.... SCALE UP One larger multicore, all-SSD node in a Hadoop cluster can take on bigger jobs or chaining, freeing up smaller nodes for easier jobs1 VIRTUALIZATION SSDs mitigate ill effects of smaller I/O blocks and larger number of requests in Xen 2 MAP REDUCE Targeting intermediate shuffle results produced by MapReduce algorithms at an SSD reduces severe loads on overwhelmed HDDs 3 SPILLING RDDS Spark running on Amazon EC2 nodes backed by Amazon S3 all-SSD storage sets records 7 HYBRID DATABASE Keeping smaller files and indices in RAM, with larger files stored on SSDs, speeds up NoSQL 8 1 2 5 4 3 1 2 5 TIERED STORAGE Aiming more HDFS requests at PCIe SSDs in a hybrid cluster increases average I/O rate 4 SMALL “HOT” FILES Caching Facebook messages on an SSD triples HBase performance through reduced latency 5 TIGHTLY COUPLED MIT tests FPGA fabric and local ARM cores on SSDs to pre-process data and speed searches 6 6 7 86 7 8 4 3 OPENOPEN TOLLSTOLLSTOLLSTOLLS 1 <Scale Up> “Scale-up vs Scale-out for Hadoop: Time to rethink?”, Appuswamy et al, Microsoft Research, presented at SoCC ‘13, October 2013, http://www.msr-waypoint.com/pubs/204499/a20-appuswamy.pdf 2 <Virtualization> “Performance Implications of SSDs in Virtualized Hadoop Clusters”, Ahn et al, Samsung Electronics, presented at IEEE BigData Congress, June 2014, http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6906832 3 <MapReduce> “The Truth About MapReduce Performance on SSDs”, Karthik Kambatla and Yanpei Chen, Cloudera Inc. and Purdue University, presented at LISA 14 sponsored by USENIX, November 2014, https://www.usenix.org/conference/lisa14/conference-program/presentation/kambatla 4 <Tiered Storage> “hatS: A Heterogeneity-Aware Tiered Storage for Hadoop”. Krish et al, Virginia Tech, presented at IEEE/ACM CCGrid2014, May 2014, http://people.cs.vt.edu/butta/docs/ccgrid2014-hats.pdf 5 <Small, "Hot" Files> “Analysis of HDFS under HBase: A Facebook Messages Case Study”, Harter et al, Facebook Inc. and University of Wisconsin, Madison, presented at FAST ’14 sponsored by USENIX, February 2014, http://research.cs.wisc.edu/adsl/Publications/fbmessages-fast14.pdf 6 <Tightly Coupled> “Cutting cost and power consumption for big data”, Larry Hardesty, Massachusetts Institute of Technology, July 10, 2015, http://news.mit.edu/2015/cutting-cost-power-big-data-0710 7 <Spilling RDDs> “Spark the fastest open source engine for sorting a petabyte”, Databricks, November 2014, https://databricks.com/blog/2014/10/10/spark-petabyte-sort.html 8 <Hybrid Database> Aerospike web site, http://www.aerospike.com/flash-optimized/ BIG DATA CLUSTERS WITH SSDS IN CRITICAL LOCATIONS COMPLETE MORE REQUESTS, BIG DATA CLUSTERS WITH SSDS IN CRITICAL LOCATIONS COMPLETE MORE REQUESTS, SSDs with V-NAND unlock big data performance with: For more details on findings from these research studies samsung.com/enterprisessd 1 2 HIGHER IOPS LOWER LATENCY MORE DWPD READ THE WHITE PAPER TO LEARN MORE