ficstar software: cassandra installation to optimization
TRANSCRIPT
![Page 1: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/1.jpg)
Cassandra Installation to Optimization40-minutes of best practice and resources
@VictorFAnjos
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2© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
Welcome to
Who Wants to perform 1M ops/s
50:50
@VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
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5© 2015. All Rights Reserved.
A: NAS / SAN
C: DAS SATA
B: SSD
D: DAS SCSI
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
This storage medium allows for best performance.
@VictorFAnjos
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6© 2015. All Rights Reserved. @VictorFAnjos
A: NAS / SAN
C: DAS SATA
B: SSD
D: DAS SCSI
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
This storage medium allows for best performance.
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Installation and considerations
how to store the datastore
Storage Area Network Solid State Drive
7© 2015. All Rights Reserved. @VictorFAnjos
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Installation and considerations
how to store the datastore
Local (DAS), iSCSI, Fiber Channel
8© 2015. All Rights Reserved. @VictorFAnjos
● AVOID network storage like the plague
● Direct Attached Storage FTW
● Disk latency is a HUGE deal for performance
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Installation and considerations
how to store the datastore
9© 2015. All Rights Reserved. 9@VictorFAnjos
SATA/SAS DAS
PCIe/NVMe DAS
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Installation and considerations
how to store the datastore
10© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
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12© 2015. All Rights Reserved. @VictorFAnjos
A: ZFS
C: Ext4
B: Btrfs
D: F2FS
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
When using SSDs, this filesystem type
is best.
@VictorFAnjos
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13© 2015. All Rights Reserved. @VictorFAnjos
A: ZFS
C: Ext4
B: Btrfs
D: F2FS
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
When using SSDs, this filesystem type
is best.
@VictorFAnjos
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Congratulations!
You’ve Reachedthe 1,000 ops/s
Milestone!
Congratulations!Congratulations!@VictorFAnjos
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Installation and considerations
i can’t believe it’s not btrfs
15© 2015. All Rights Reserved. @VictorFAnjos
● easiest to use ext4 (it’s on most linux distros), but F2FS get 5-10% gains in write performance
● if NOT using F2FS, make sure to TRIM
● multiple disks → use RAID0
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
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17© 2015. All Rights Reserved. @VictorFAnjos
A: 0
C: Equal to HEAP
B: ½ of HEAP
D: EQUAL TO RAM
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
This is the sweetspot for SWAP
when using C*
@VictorFAnjos
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18© 2015. All Rights Reserved. @VictorFAnjos
A: 0
C: Equal to HEAP
B: ½ of HEAP
D: EQUAL TO RAM
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
This is the sweetspot for SWAP
when using C*
@VictorFAnjos
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Installation and considerations
to swap or not to swap
19© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 21: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/21.jpg)
21© 2015. All Rights Reserved. @VictorFAnjos
A: 64G
C: 16G
B: 32G
D: 8G
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
Having 64G of RAM means you should optimize to have ___G of HEAP.
@VictorFAnjos
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22© 2015. All Rights Reserved. @VictorFAnjos
A: 64G
C: 16G
B: 32G
D: 8G
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
Having 64G of RAM means you should optimize to have ___G of HEAP.
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Installation and considerations
how much heap?
23© 2015. All Rights Reserved. @VictorFAnjos
http://docs.datastax.com/en/cassandra/1.2/cassandra/operations/ops_tune_jvm_c.html
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 25: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/25.jpg)
25© 2015. All Rights Reserved. @VictorFAnjos
A: EC2Snitch
C: Simple Snitch
B: Dynamic Snitch
D: Property File Snitch
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
Definitely DO NOT use this snitch in
Multi-DC environments.
@VictorFAnjos
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26© 2015. All Rights Reserved. @VictorFAnjos
A: EC2Snitch
C: Simple Snitch
B: Dynamic Snitch
D: Property File Snitch
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
Definitely DO NOT use this snitch in
Multi-DC environments.
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Installation and considerations
son of a snitch
27© 2015. All Rights Reserved. @VictorFAnjos
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Installation and considerations
son of a snitch
28© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 30: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/30.jpg)
30© 2015. All Rights Reserved. @VictorFAnjos
A: Synchronous AND Full Queries
C: Synchronous AND Prepared Statements
B: Asynchronous AND Prepared Statements
D: Asynchronous AND Full Queries
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
To reduce latency and wire time to my
app, I should opt for.
@VictorFAnjos
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31© 2015. All Rights Reserved. @VictorFAnjos
A: Synchronous AND Full Queries
C: Synchronous AND Prepared Statements
B: Asynchronous AND Prepared Statements
D: Asynchronous AND Full Queries
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
To reduce latency and wire time to my
app, I should opt for.
@VictorFAnjos
![Page 32: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/32.jpg)
Achieving performance through code/drivers
should I stay or should I go
32© 2015. All Rights Reserved. @VictorFAnjos
● Client writes to any Cassandra node
● Coordinator node replicates to other nodes (in local and remote Data Center)
● Local write acks returned to coordinator
● Client gets ack when enough total nodes are committed
● Data written to internal commit log disks
● When data arrives, remote node replicates data
MULTI DC
● Ack direct to source region coordinator
● Remote copies written to commit log disks
lf a node or region goes offline, hinted handoff completes the write when the node comes back up (as long as there are enough nodes to satisfy consistency level).
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Achieving performance through code/drivers
should I stay or should I go
33© 2015. All Rights Reserved. @VictorFAnjos
Prepare ONCE...
Bind and Execute multiple times.
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Achieving performance through code/drivers
should I stay or should I go
34© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 36: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/36.jpg)
36© 2015. All Rights Reserved. @VictorFAnjos
A: 1 / 1 = 1
C: 2 * 1 = 2
B: 2 / 1 = 2
D: 2 / 2 + 1 = 2
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
With RF=2 and CL=Quorum, operations failed when 1 node went down because of this.
@VictorFAnjos
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37© 2015. All Rights Reserved. @VictorFAnjos
A: 1 / 1 = 1
C: 2 * 1 = 2
B: 2 / 1 = 2
D: 2 / 2 + 1 = 2
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
With RF=2 and CL=Quorum, operations failed when 1 node went down because of this.
@VictorFAnjos
![Page 38: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/38.jpg)
Congratulations!
You’ve Reachedthe 32,000 ops/s
Milestone!
Congratulations!Congratulations!@VictorFAnjos
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Achieving performance through code/drivers
when friends aren’t enough
39© 2015. All Rights Reserved. @VictorFAnjos
Replication Factor = 3
Insert into a cluster of size 6 with consistency Quorum
Two nodes in token range must be present for write to succeed
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Achieving performance through code/drivers
when friends aren’t enough
40© 2015. All Rights Reserved. @VictorFAnjos
What happens now?
Cannot achieve consistency level QUORUM
Cannot achieve consistency level QUORUM
Cannot achieve consistency level QUORUM
Cannot achieve consistency level QUORUM
Nodes in partition key DOWN
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 42: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/42.jpg)
42© 2015. All Rights Reserved. @VictorFAnjos
A: Truth table
C: CAP Theorem
B: Brewer’s Theorem
D: Entropy
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
This mathematical and CS concept helps when data modeling for query
optimization.
@VictorFAnjos
![Page 43: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/43.jpg)
43© 2015. All Rights Reserved. @VictorFAnjos
A: Truth table
C: CAP Theorem
B: Brewer’s Theorem
D: Entropy
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
This mathematical and CS concept helps when data modeling for query
optimization.
![Page 44: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/44.jpg)
Data modelling, CQLSH and more
the truth shall set you free
44© 2015. All Rights Reserved. @VictorFAnjos
Motivated by CS, Math, Engineering
Allows for creating building blocks that yield a single output
More complex truth tables can arise
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Data modelling, CQLSH and more
the truth shall set you free
45© 2015. All Rights Reserved. @VictorFAnjos
How about searching for username?
And what about full_name?
user_stream
← ← ← Partition Key → → → user_id username full_name
1 0 00 1 00 0 1
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 47: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/47.jpg)
47© 2015. All Rights Reserved. @VictorFAnjos
A: Reads / Batches
C: Writes / Deletes
B: Writes / Batches
D: Reads / Deletes
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
A shift in paradigms, what should you
maximize and reduce for good performance.
@VictorFAnjos
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48© 2015. All Rights Reserved. @VictorFAnjos
A: Reads / Batches
C: Writes / Deletes
B: Writes / Batches
D: Reads / Deletes
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
A shift in paradigms, what should you
maximize and reduce for good performance.
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Data modelling, CQLSH and more
do the write thing
49© 2015. All Rights Reserved. @VictorFAnjos
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Data modelling, CQLSH and more
do the write thing
50© 2015. All Rights Reserved. @VictorFAnjos
memtable --- < 100ns
commit log --- ~ 1 ms
DELETES / TTL cause compactions
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Data modelling, CQLSH and more
do the write thing
51© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 53: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/53.jpg)
53© 2015. All Rights Reserved. @VictorFAnjos
A: ACID
C: Rollback
B: Vector
D: Sharding
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
To not hit a 2B record limit (per row), this
RDBMS borrowed term can still makes sense.
@VictorFAnjos
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54© 2015. All Rights Reserved. @VictorFAnjos
A: ACID
C: Rollback
B: Vector
D: Sharding
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
To not hit a 2B record limit (per row), this
RDBMS borrowed term can still makes sense.
@VictorFAnjos
![Page 55: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/55.jpg)
Data modelling, CQLSH and more
sit on this and rotate
55© 2015. All Rights Reserved. @VictorFAnjos
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 57: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/57.jpg)
57© 2015. All Rights Reserved. @VictorFAnjos
A: Batches
C: Secondary Indexes
B: Synchronous
D: MySQL
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
Many say to use sparingly, I would say, avoid like the plague.
@VictorFAnjos
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58© 2015. All Rights Reserved. @VictorFAnjos
A: Batches
C: Secondary Indexes
B: Synchronous
D: MySQL
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
Many say to use sparingly, I would say, avoid like the plague.
![Page 59: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/59.jpg)
Performance must-haves
never be second best
59© 2015. All Rights Reserved. @VictorFAnjos
writes are distributed among the cluster
each partition key refers to one exact position in which to get a row
but what do we do when we don’t have exactly the right type of index to specify a queryCREATE TABLE users ( user varchar, email varchar, state varchar, PRIMARY KEY (user));-- OPTION 1 : create an indexCREATE INDEX idxUBS on users (state);
-- OPTION 2 : create another table (store data twice)CREATE TABLE usersByState ( state varchar, user varchar, PRIMARY KEY (state, user));
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151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
@VictorFAnjos
![Page 61: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/61.jpg)
61© 2015. All Rights Reserved. @VictorFAnjos
A: UDT
C: JSON
B: Lightweight Transactions
D: Hinted handoff
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
This recent addition to C* now helps with ACID like transactions, at a bit
of a performance hit.
@VictorFAnjos
![Page 62: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/62.jpg)
62© 2015. All Rights Reserved. @VictorFAnjos
A: UDT
C: JSON
B: Lightweight Transactions
D: Hinted handoff
50:50
151413121110987654321
1 Million500,000250,000125,00064,00032,00016,0008,0004,0002,0001,000500300200100
This recent addition to C* now helps with ACID like transactions, at a bit
of a performance hit.
@VictorFAnjos
![Page 63: Ficstar Software: Cassandra Installation to Optimization](https://reader033.vdocuments.net/reader033/viewer/2022052117/588583f01a28ab84668b486b/html5/thumbnails/63.jpg)
Performance must-haves
slimfast agreement
63© 2015. All Rights Reserved. @VictorFAnjos
Prepares a proposal that is sent to a number of Acceptors.Waits on a an acknowledgement (in form of promise) from Acceptors.Sends accept message to Quorum of Acceptors with new value to commit.Returns success? completion to client.
Determines if proposal is newer than what it has seen.Acknowledges/agree with its own highest proposal value seen AND the current value (of what is to be set).Receive message to commit new value.Accept and return on successful commit of value.
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64© 2015. All Rights Reserved. @VictorFAnjos
Performance must-haves
slimfast agreement
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Thank you