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Time Series Data With A 
Apache Cassandra 
ApacheCon Europe 
November 18, 2014 
Eric Evans 
eevans@opennms.org 
@jericevans
Open
Open
Open
Open
Network 
Management 
System
OpenNMS: What It Is 
● Network Management System 
○ Discovery and Provisioning 
○ Service monitoring 
○ Data collection 
○ Event management, notifications 
● Java, open source, GPLv3 
● Since 1999
Time series: RRDTool 
● Round Robin Database 
● First released 1999 
● Time series storage 
● File-based, constant-size, self-maintaining 
● Automatic, incremental aggregation
… and oh yeah, graphing
Consider 
● 5+ IOPs per update (read-modify-write)! 
● 100,000s of metrics, 1,000s IOPS 
● 1,000,000s of metrics, 10,000s IOPS 
● 15,000 RPM SAS drive, ~175-200 IOPS
Hmmm 
We collect and write a great deal; We read 
(graph) relatively little. 
So why are we aggregating everything?
Also 
● Not everything is a graph 
● Inflexible 
● Incremental backups impractical 
● Availability subject to filesystem access
TIL 
Metrics typically appear in groups that are 
accessed together. 
Optimizing storage for grouped access is a 
great idea!
What OpenNMS needs: 
● High throughput 
● High availability 
● Late aggregation 
● Grouped storage/retrieval
Cassandra 
● Distributed database 
● Highly available 
● High throughput 
● Tunable consistency
SSTables 
Writes 
Memtable 
Commitlog 
SSTable 
Memory 
Disk
Write Properties 
● Optimized for write throughput 
● Sorted on disk 
● Perfect for time series!
Partitioning Z A 
A 
B 
C 
Key: Apple 
...
Placement 
A 
B 
C 
Key: Apple 
...
Replication 
A 
B 
C 
Key: Apple 
...
CAP Theorem 
Consistency 
Availability 
Partition tolerance
Consistency 
A 
B 
? 
W=2
Consistency 
R=2 
R+W > N 
? 
B 
C
Distribution Properties 
● Symmetrical 
● Linearly scalable 
● Redundant 
● Highly available
D ata M odel
Data Model 
resource
Data Model 
resource 
T1 T2 T3
Data Model 
resource 
T1 
M1 M2 
V1 V2 
M3 
V3 
T2 
M1 M2 
V1 V2 
M3 
V3 
T3 
M1 M2 
V1 V2 
M3 
V3
Data Model 
CREATE TABLE samples ( 
T timestamp, 
M text, 
V double, 
resource text, 
PRIMARY KEY(resource, T, M) 
);
Data model 
resource T1 M1 V1 T1 M2 V2 T1 M3 V3
Data model 
resource T1 M1 V1 T1 M2 V2 T1 M3 V3 
SELECT * FROM samples 
WHERE resource = ‘resource’ 
AND T = ‘T1’;
Data model 
resource T1 M1 V1 T1 M2 V2 T1 M3 V3 
resource T1 M1 V1
Data model 
resource T1 M1 V1 T1 M2 V2 T1 M3 V3 
T1 M1 V1 
T1 M2 V2 
resource 
resource
Data model 
resource T1 M1 V1 T1 M2 V2 T1 M3 V3 
T1 M1 V1 
T1 M2 V2 
T1 M3 V3 
resource 
resource 
resource
Data model 
resource T1 M1 V1 T2 M1 V1 T3 M1 V1 
SELECT * FROM samples 
WHERE resource = ‘resource’ 
AND T >= ‘T1’ AND T <= ‘T3’;
Newts 
● Standalone time series data-store 
○ REST server 
○ Java API 
● Raw sample storage and retrieval 
● Flexible aggregations (computed at read) 
○ Rate (counter types) 
○ Pluggable aggregation functions 
○ Arbitrary calculations
Newts 
● Search-enabled 
● Fast; Runs at Cassandra-speed 
● Apache licensed 
● Github (http://github.com/OpenNMS/newts) 
● http://newts.io
Fin

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