1.
CASSANDRA
AT INSTAGRAM
Rick Branson, Infrastructure Engineer
@rbranson
SF Cassandra Meetup
August 29, 2013
Disqus HQ

2.
September 2012
Redis fillin' up.

3.
What sucks?

4.
THE OBVIOUS
Memory is expensive.

5.
LESS OBVIOUS:
In-memory "degrades" poorly

6.
•Flat namespace. What's in there?
•Heap fragmentation
•Single threaded

7.
BGSAVE

8.
•Boils down to centralized logging
•VERY high skew of writes to reads
(1,000:1)
•Ever growing data set
•Durability highly valued
•Dumb to store it in RAM, basically...
The Data

9.
• Cassandra 1.1
• 3 EC2 m1.xlarge (2-core, 15GB RAM)
• RAIDed ephemerals (1.6TB of SATA)
• RF=3
• 6GB Heap, 200MB NewSize
• HSHA
The Setup

10.
It worked. Mostly.

11.
The horriblecool
thing about Chef...

12.
commit a1489a34d2aa69316b010146ab5254895f7b9141
Author: Rick Branson
Date: Thu Oct 18 20:05:16 2012 -0700
Follow the rules for Cassandra listen_address so I don't
burn a whole day fixing my retarded mistake

13.
commit 41c96f3243a902dd6af4ea29ef6097351a16494a
Author: Rick Branson
Date: Tue Oct 30 17:12:00 2012 -0700
Use 256k JVM stack size for C* -- fixes a bug that got
integrated with 1.1.6 packaging + Java 1.6.0_u34+

14.
November 2013
Doubled to 6 nodes.
18,000 connections. Spread those more evenly.

15.
commit 3f2e4f2e5da6fe99d7f3fc13c0da09b464b3a9e0
Author: Rick Branson
Date: Wed Nov 21 09:50:21 2012 -0800
Drop key cache size on C*UA cluster: was causing heap
issues, and apparently 1GB is _WAY_ outside of the normal
range of operation for nodes of this size.

16.
commit 5926aa5ce69d48e5f2bb7c0d0e86b411645bc786
Author: Rick Branson
Date: Mon Dec 24 12:41:13 2012 -0800
Lower memtable sizes on C* UA cluster to make more room
for compression metadata / bloom filters on heap

17.
1.2.1.
It went well.
well... until...

18.
commit 84982635d5c807840d625c22a8bd4407c1879eba
Author: Rick Branson
Date: Thu Jan 31 09:43:56 2013 -0800
Switch Cassandra from tokens to vnodes
commit e990acc5dc69468c8a96a848695fca56e79f8b83
Author: Rick Branson
Date: Sun Feb 10 20:26:32 2013 -0800
We aren't ready for vnodes yet guys

19.
TAKEAWAY
Let stupidenterprising, experienced operators that
will submit patches take the first few bullets on
brand-new major versions.

20.
commit acb02daea57dca889c2aa45963754a271fa51566
Author: Rick Branson
Date: Sun Feb 10 20:36:34 2013 -0800
Doubled C* cluster

21.
commit cc13a4c15ee0051bb7c4e3b13bd6ae56301ac670
Author: Rick Branson
Date: Thu Mar 14 16:23:18 2013 -0700
Subtract token from C*ua7 to replace the node

22.
pycassa exceptions (last 6 months)

23.
•3.4TB
•vnode migration still pending

24.
TAKEAWAY
Adopt a technology by understanding what it's
best at and letting it do that first, then expand...

25.
•Sharded master/slave Redis
•32x68GB (m2.4xlarge)
•Space (memory) bound
•Resharding sucks
•Failover is manual, wakes us up at night

26.
user_id: [
activity,
activity,
...
]

27.
user_id: [
activity,
activity,
...
]
Thrift Serialized Activity

28.
Bound the Size
user_id: [
activity1,
activity2,
...
activity100,
activity101,
...
]
LTRIM <user_id> 0 99

29.
Undo
user_id: [
activity1,
activity2,
activity3,
...
]
LREM <user_id> 0 <activity2>

30.
C* data model
user_id
TimeUUID1 TimeUUID2
...
TimeUUID101
user_id
<activity> <activity>
...
<activity>

31.
Bound the Size
user_id
TimeUUID1 TimeUUID2
...
TimeUUID101
user_id
<activity> <activity>
...
<activity>
get(<user_id>)
delete(<user_id>,
columns=[<TimeUUID101>,
<TimeUUID102>,
<TimeUUID103>,
...])

32.
The great destroyer of
systems shows up.
Tombstones abound.

33.
user_id
TimeUUID1 TimeUUID2
...
TimeUUID2
user_id <activity> <activity> ... [tombstone]user_id
timestamp1 timestamp2
...
timestamp2
Cassandra internally stores deletes as
tombstones, which mark data for a given
column as deleted at-or-before a timestamp.
Column Delete
tombstone timestamp is >= live
column timestamp, so it will be
hidden from queries and
compacted away.

34.
user_id
TimeUUID1 TimeUUID2
...
TimeUUID101
user_id <activity> <activity> ... <activity>user_id
timestamp1 timestamp2
...
timestamp101
TimeUUID = timestamp
To avoid tombstones, exploit that the
timestamp embedded in our TimeUUID
(ordering) is the same as the column
timestamp.

35.
user_id
TimeUUID1 TimeUUID2
...
TimeUUID101
user_id <activity> <activity> ... <activity>user_id
timestamp1 timestamp2
...
timestamp101
delete(<user_id>,
timestamp=<timestamp101>)
Row Delete
Cassandra can also store row tombstones,
which delete all data from a row at-or-before
the timestamp provided.

36.
Optimizes Reads
SSTable
max_ts=100
SSTable
max_ts=200
SSTable
max_ts=300
SSTable
max_ts=400
SSTable
max_ts=500
SSTable
max_ts=600
SSTable
max_ts=700
SSTable
max_ts=800
Contains row tombstone
with timestamp 350
Safely ignored
using in-memory
metadata

37.
~10% of actions are undos.

38.
Undo Support
user_id
TimeUUID1 TimeUUID2
...
TimeUUID101
user_id
<activity> <activity>
...
<activity>
get(<user_id>)
delete(<user_id>,
columns=[<TimeUUID2>])

39.
get(<user_id>)
delete(<user_id>,
columns=[<TimeUUID2>])
Simple Race Condition
The state of the row may have changed
between these two operations.
💩

40.
Replica
[A, B]
Replica
[A]
Writer
insert B OK
Replica
[A, B]
FAIL
Like
Diverging Replicas

41.
Replica
[A, B]
Replica
[A]
Writer
read [A]
Replica
[A, B]
Undo Like
Diverging Replicas
Replica is missing B, so if a read
is required to find B before
deleting it, it's going to fail.

42.
SuperColumn = Old/Busted
AntiColumn = New/Hotness
user_id
(0, <TimeUUID>) (1, <TimeUUID>) (1, <TimeUUID>)
user_id
anti-column activity activity
"Anti-Column"
Borrowing from the idea of Cassandra's by-
name tombstones, Contains an MD5 hash of
the activity data "value" it is marking as
deleted.

43.
user_id
(0, <TimeUUID>) (1, <TimeUUID>) (1, <TimeUUID>)
user_id
anti-column activity activity
Composite Column
First component is zero for anti-columns,
splitting the row into two independent lists,
and ensuring the anti-columns always appear
at the head.

44.
Replica
[A, B]
Replica
[A]
Writer
insert B OK
Replica
[A, B]
FAIL
Like
Diverging Replicas: Solved

45.
Replica
[A, B, C]
Replica
[A, C]
Writer
insert C
Replica
[A, B, C]
Undo Like
Diverging Replicas: Solved
OK
Instead of read-before-write, an
anti-column is inserted to mark
the activity as deleted.

46.
TAKEAWAY
Read-before-write is a smell. Try to model data as
a log of user "intent" rather than manhandling the
data into place.

47.
•Keep 30% "buffer" for trims.
•Undo without read. (thumbsup)
•Large lists suck for this. (thumbsdown)
•CASSANDRA-5527

48.
Built in two days.
Experience paid off.

49.
Reusability is key to rapid rollout.
Great documentation eases concerns.

50.
•C* 1.2.3
•vnodes, LeveledCompactionStrategy
•12 hi1.4xlarge (8-core, 60GB, 2T SSD)
•3 AZs, RF=3, CL W=TWO R=ONE
•8G heap, 800M NewSize
Initial Setup

51.
1. Dial up Double Writes
2. Test with "Shadow" Reads
3. Dial up "Real" Reads
Rollout

52.
commit 1c3d99a9e337f9383b093009dba074b8ade20768
Author: Rick Branson
Date: Mon May 6 14:58:54 2013 -0700
Bump C* inbox heap size 8G -> 10G, seeing heap pressure

53.
Bootstrapping sucked because compacting
10,000 SSTables takes forever.
sstable_size_in_mb: 5 => 25

54.
Monitor Consistency
$ nodetool netstats
Mode: NORMAL
Not sending any streams.
Not receiving any streams.
Read Repair Statistics:
Attempted: 3192520
Mismatch (Blocking): 0
Mismatch (Background): 11584
Pool Name Active Pending Completed
Commands n/a 0 1837765727
Responses n/a 1 1750784545
UPDATE COLUMN FAMILY
InboxActivitiesByUserID
WITH read_repair_chance = 0.01;
99.63% consistent

55.
SSTable Size (again)
Saw lots of GC pressure related to buffer
garbage. Eventually they landed on a new
default in 1.2.9+ (160MB).
sstable_size_in_mb: 25 => 128

56.
Fetch & Deserialize Time (measured from app)
Mean vs P90 (ms), trough-to-peak

57.
Space used (live): 180114509324
Space used (total): 180444164726
Memtable Columns Count: 2315159
Memtable Data Size: 112197632
Memtable Switch Count: 1312
Read Count: 316192445
Read Latency: 1.982 ms.
Write Count: 1581610760
Write Latency: 0.031 ms.
Pending Tasks: 0
Bloom Filter False Positives: 481617
Bloom Filter False Ratio: 0.08558
Bloom Filter Space Used: 54723960
Compacted row minimum size: 25
Compacted row maximum size: 545791
Compacted row mean size: 3020

58.
20K 200-column slice reads/sec
30K 1-column mutations/sec
30% CPU utilization
48K clients
Peak Stats

59.
Exciting Future Things
•Python Native Protocol Driver
•Read CPU Consumption Work
•Mass CQL Adoption
•Triggers
•CAS (for limited use cases)

60.
Next 6 Months...
•Node repair visibility & monitoring
•Objects & Associations Storage API on
C* + memcache
•Migrate more from Redis
•New major use case
•Cassandra 2.0?

61.
We're hiring!