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Why does my choice of storage matter with cassandra?
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Johnny Miller
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Talk given at Netherlands Cassandra Users meetup, November 2014
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Why does my choice of storage matter with cassandra?
1.
Why does my
choice of storage matter with Cassandra? Johnny Miller, Solutions Architect @CyanMiller www.linkedin.com/in/johnnymiller
2.
Quote “The single biggest
predictor of success or failure with a Cassandra deployment is in storage choice” Patrick McFadin, Chief Evangelist for Cassandra, @PatrickMcFadin ©2014 DataStax Confidential. Do not distribute without consent. 2
3.
Cassandra Storage Engine ©2014
DataStax Confidential. Do not distribute without consent. 3
4.
Inserts/Updates ©2014 DataStax Confidential.
Do not distribute without consent. 4 Memtables are organized in sorted order by row key and flushed to SSTables sequentially (Read/Write) Ordered Map of KVP, (Immutable, Read Only) Append only file structure, providing interim durability for writes before they get flushed to SSTables (Write Only)
5.
Reads ©2014 DataStax Confidential.
Do not distribute without consent. 5
6.
Deletes • Unlike most
DBs, deleted data is not immediately removed from disk. • A marker called a tombstone is written to indicate the the column is deleted • A tombstones exist for a configurable period of time, and are only deleted from disk via compaction after that time has expired. • Deletes are just as fast as inserts J ©2014 DataStax Confidential. Do not distribute without consent. 6
7.
Compaction • Regular compaction
of data in Cassandra is essential for a healthy and performant cluster. • SSTables are immutable • Get rid or duplicate/overwritten data • Drop deleted data and tomnstones • Data in SSTables is sorted by partition key, the effect of which is that while the SSTables are being consolidated, the disk I/O is not random. ©2014 DataStax Confidential. Do not distribute without consent. 7
8.
Compaction Strategies • There
is a choice of three strategies Cassandra can use for compaction and all have different disk I/O profiles and capacity requirements. • SizeTieredCompactionStrategy (default) • Using this strategy causes bursts in I/O activity while a compaction is in process • These I/O bursts can negatively affect read-heavy workloads, but typically do not impact write performance. • Data highly likely to be spread across multiple SSTables i.e. multiple disk seeks • LeveledCompactionStrategy • ~90% of the time, data will be in only a single SSTable i.e. minimal disk seeks • However, there is significantly higher Disk I/O than size tiered compaction in order to guarantee how many SSTables data may be spread across • Due to high disk I/O rarely appropriate for on traditional HDD • DateTieredCompactionStrategy (C* 2.0.11+ and 2.1.1+) • Stores data written within a certain period of time in the same SSTable. • Can store data that has been set to expire using TTL in an SSTable with other data scheduled to expire at approximately – can just drop the SSTable without any compaction! ©2014 DataStax Confidential. Do not distribute without consent. 8
9.
Choice of storage
matters • Most databases rewrite modified data in place and writes are buffered and then flushed to disk as random writes. • With Cassandra: • Disk writes are typically sequential append only operations • On-disk tables are written in a sorted order so compaction running time increases linearly with the amount of data • So choice of storage is pretty important!! ©2014 DataStax Confidential. Do not distribute without consent. 9
10.
Disks and Configuration
Options ©2014 DataStax Confidential. Do not distribute without consent. 10
11.
Quote “For many applications,
we are no longer constrained by hard drive capacity, but by seek speeds. Essentially, a 7200 RPM hard drive is capable of delivering approximately 100 seeks per second, and this has not changed in more than 10 years, even as disk capacity has been doubling every 18–24 months. In fact, if you have a big data application which required a half a petabyte of storage, what had previously required 1024 disk drives when we were using 500 GB drives, now that 3 TB disks are available, only 171 disk drives are needed. So a storage array capable of storing half a petabyte is now capable of 80% fewer seeks.” - Ted Ts’o Maintainer of the ext4 file system in the Linux kernel ©2014 DataStax Confidential. Do not distribute without consent. 11
12.
Hard Drive/Spinning Disk ©2014
DataStax Confidential. Do not distribute without consent. 12 This part actually has to move!This bit spins around very fast
13.
So what can
we do? • Memory? • Caching can help, but the hit rate has to be extremely high to mitigate the mechanical latency of spinning disks • Get rid of the moving parts! • Mechanical media will never be able to keep up under load • Today’s databases service multiple users with difference access patterns • A relatively small number of concurrent disk reads can result in seconds of latency • SSDs don’t have moving parts • SSDs can eliminate entire classes of problems • With Cassandra in particular, you will save a lot of money on staff resources by investing in SSDs up front • Compactions can be tough on flash, but it’s not as bad as you think ©2014 DataStax Confidential. Do not distribute without consent. 13
14.
The best way
to do it – SSDs! • What is an SSD? • Solid State Drive • Bits stored in NAND Flash Memory • No moving parts • “Seeks” 2-3 orders of magnitude faster than spinning disk • What’s the catch? • Smaller capacity • More expensive • Flash wears out In practice, this is not a problem – if it makes you nervous, keep spares ©2014 DataStax Confidential. Do not distribute without consent. 14
15.
The IO Scheduler •
NOOP - use this scheduler if you know another IO device (like a RAID card) will be doing its own IO scheduling. The NOOP scheduler is just a pass-through. • Deadline - otherwise, use the deadline scheduler • Tell the OS the drive is non-rotational • Tune read-ahead way down – start at 0 and work your way up Don’t forget to tune the OS for SSDs ©2014 DataStax Confidential. Do not distribute without consent. 15 echo deadline > /sys/block/<drive>/queue/scheduler echo 0 > /sys/block/sda/queue/rotational blockdev –setra 0 /dev/<drive>
16.
Use SSDs • More
flexibility and substantial performance benefit • Typically 10x the performance for less than 2x the cost (potentially lower) when compared with HDDs. • You can use LeveledCompactionStrategy • SSD drives can scale up to cope with larger compaction overheads while simultaneously serving many random reads. • Netflix found that they could half the total system cost to achieve the same level of throughput. • Additionally the mean read request latency was reduced from 10ms to 2.2ms and 99th percentile request latency was reduced from 65ms to 10ms. • http://techblog.netflix.com/2012/07/benchmarking-high-performance-io-with.html. ©2014 DataStax Confidential. Do not distribute without consent. 16
17.
The worst way
to do it • Shared Storage • Cassandra is a shared-nothing architecture with no single point of failure • Adding shared storage adds a single point of failure • Irrespective of the terrible performance – this alone is enough reason not to do it. ©2014 DataStax Confidential. Do not distribute without consent. 17 Shared Storage
18.
Local storage configuration •
RAID or JBOD? • RAID – Redundant Array of (Independepent/Inexpensive) Devices • JBOD – Just a Bunch Of Disks • RAID • Common Cassandra RAID levels are 0, 1, 10 • RAID-0 is most common, but means all data on node must be rebuilt from other nodes when a drive fails • JBOD • Drives are listed individually in cassandra.yaml • Failed drives can be replaces individually ©2014 DataStax Confidential. Do not distribute without consent. 18
19.
How to choose
between RAID or JBOD? • Performance • For SSDs, not so much… • Compactions are usually throttled significantly below bus speed • So a single SSD usually has sufficient throughput • Throughput is really the only advantage RAID buys • Manageability • Pick the option that best fits the deployment scenario • If using SSD, and drives can be replaced, choose JBOD • Otherwise, RAID is probably the right choice. ©2014 DataStax Confidential. Do not distribute without consent. 19
20.
How to choose
between RAID or JBOD? • Cloud provider • EC2 ephemeral SSD can’t be replaced, use RAID (and dont use EBS) • GCE persistent SSD volumes can be replaced, JBOD is useful • Not all drives are hot swapable • PCIe devices can’t conveniently be replaced • SSD Spares for JBOD mode • Keep spare SSDs online, but not in use • Allows the node to be easily brought back online with a quick config change ©2014 DataStax Confidential. Do not distribute without consent. 20
21.
Comparison Data ©2014 DataStax
Confidential. Do not distribute without consent. 21
22.
FusionIO ioDrive II ©2014
DataStax Confidential. Do not distribute without consent. 22 Reads Writes Latency (microseconds)
23.
PNY XLR8 SSD
(consumer grade MLC) ©2014 DataStax Confidential. Do not distribute without consent. 23
24.
Samsung 840 Pro
SSD (consumer grade MLC) ©2014 DataStax Confidential. Do not distribute without consent. 24
25.
7200RPM SATA ©2014 DataStax
Confidential. Do not distribute without consent. 25
26.
7200RPM SAS ©2014 DataStax
Confidential. Do not distribute without consent. 26
27.
10K SATA ©2014 DataStax
Confidential. Do not distribute without consent. 27
28.
15K SAS ©2014 DataStax
Confidential. Do not distribute without consent. 28
29.
All Drives ©2014 DataStax
Confidential. Do not distribute without consent. 29
30.
All SSDs ©2014 DataStax
Confidential. Do not distribute without consent. 30
31.
Conclusion • Using SSDs
is a good idea • Better response times • Less variance in performance • Significantly higher throughput so fewer servers needed ©2014 DataStax Confidential. Do not distribute without consent. 31 VS
32.
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