- We have at least one device for each playback pipeline architecture we support (The app uses several approaches for video playback on Android such as hardware decoder, software decoder, OMX-AL, iOMX).
- We choose devices with high and low end processors as well as devices with different memory capabilities.
- We have representatives that support each major operating system by make in addition to supporting custom ROMs (most notably CM7, CM9).
- We choose devices that are most heavily used by Netflix Subscribers.
Wednesday, March 14, 2012
Tuesday, March 13, 2012
A number of previous blogs have discussed our adoption of Cassandra as a NoSQL solution in the cloud. We now have over 55 Cassandra clusters in the cloud and are moving our source of truth from our Datacenter to these Cassandra clusters. As part of this move we have not only contributed to Cassandra itself but developed software to ease its deployment and use. It is our plan to open source as much of this software as possible.
We recently announced the open sourcing of Priam, which is a co-process that runs alongside Cassandra on every node to provide backup and recovery, bootstrapping, token assignment, configuration management and a RESTful interface to monitoring and metrics. In January we also announced our Cassandra Java client Astyanax which is built on top of Thrift and provides lower latency, reduced latency variance, and better error handling.
At Netflix we have recently started to standardize our load testing across the fleet using Apache JMeter. As Cassandra is a key part of our infrastructure that needs to be tested we developed a JMeter plugin for Cassandra. In this blog we discuss the plugin and present performance data for Astyanax vs Thrift collected using this plugin.
Cassandra JMeter Plugin
JMeter allows us to customize our test cases based on our application logic/datamodel. The Cassandra JMeter plugin we are releasing today is described on the github wiki here. It consists of a jar file that is placed in JMeter's lib/ext directory. The instructions to build and install the jar file are here.
An example screenshot is shown below.
We set up a simple 6-node Cassandra cluster using EC2 m2.4xlarge instances, and the following schema
Six million rows were then inserted into the cluster with a replication factor 3. Each row has 19 columns of simple ascii data. Total data set is 2.9GB per node so easily cacheable in our instances which have 68GB of memory. We wanted to test the latency of the client implementation using a single Get Range Slice operation ie 100% Read only. Each test was run twice to ensure the data was indeed cached, confirmed with iostat. One hundred JMeter threads were used to apply the load with 100 connections from JMeter to each node of Cassandra. Each JMeter thread therefore has at least 6 connections to choose from when sending it's request to Cassandra.
Every Cassandra JMeter Thread Group has a Config Element called CassandraProperties which contains clientType amongst other properties. For Astyanax clientType is set t0 com.netflix.jmeter.connections.a6x.AstyanaxConnection, for Thrift com.netflix.jmeter.connections.thrift.ThriftConnection.
Token Aware is the default JMeter setting. If you wish to experiment with other settings create a properties file, cassandra.properties, in the JMeter home directory with properties from the list below.
This graph shows the throughput at 5 second intervals for the Token Aware client vs the Thrift client. Token aware is consistently higher than Thrift and its average is 3% better throughput
JMeter reports response times to millisecond granularity. The Token Aware implementation responds in 2ms the majority of the time with occasional 3ms periods, the average is 2.29ms. The Thrift implementation is consistently at 3ms. So Astyanax has about a 30% better response time than raw Thrift implementation without token aware connection pool.
The plugin provides a wide range of samplers for Put, Composite Put, Batch Put, Get, Composite Get, Range Get and Delete. The github wiki has examples for all these scenarios including jmx files to try. Usually we develop the test scenario using the GUI on our laptops and then deploy to the cloud for load testing using the non-GUI version. We often deploy on a number of drivers in order to apply the required level of load.
The data for the above benchmark was also collected using a tool called casstat which we are also making available in the repository. Casstat is a bash script that calls other tools at regular intervals, compares the data with its previous sample, normalizes it on a per second basis and displays the pertinent data on a single line. Under the covers casstat uses
- Cassandra nodetool cfstats to get Column Family performance data
- nodetool tpstats to get internal state changes
- nodetool cfhistograms to get 95th and 99th percentile response times
- nodetool compactionstats to get details on number and type of compactions
- iostat to get disk and cpu performance data
- ifconfig to calculate network bandwidth
An example output is below (note some fields have been removed and abbreviated to reduce the width)
We merge the casstat data from each Cassandra node and then use gnuplot to plot throughput etc.
The Cassandra JMeter plugin has become a key part of our load testing environment. We hope the wider community also finds it useful.