Sure, I can do that.
My main concern is write latency and the write timeouts we are experiencing.
Read latency is secondary, as long as we do not introduce timeouts on read and
do not exceed our sampling intervals (see below).
We are running Cassandra 1.2.1 on Ubuntu 12.04 with JDK 1.7.0_17 (64bit).
The hardware is virtual but so far we are the only tenant on the physical host.
Hardware:
- 1x6 cores with 2.3GHz
- 30GB RAM
- 1 physical disk for both the tx log and the data files
- 2 x 1GB Ethernet combined into one virtual interface
Cassandra Config:
Cassandra runs with
- 7.5GB of heap and
- 600MB of new gen space
as calculated by the cassandra-env script.
I have adjusted all cassandra.yaml settings where clear guidance is given, e.g.
<factor> x <num_cores>.
I have tried to increase and decrease heap (between 6 and 8GB) and new gen size
(between 300 and 1.1GB).
I have tried compaction_throughput_mb_per_sec values between 16 and 48.
I have disabled key caches.
Unfortunately Cassandra has to share the host with other Java processes, the
most resource demanding being ActiveMQ 5.8.
Log Output:
Over the course of a day (08:00 to 22:00) I see in the logs
- 280 and 760 "GC for ParNew" per hour (most around 300/h)
- 60 and 180 "Completed flushing" per hour (most around 100/h)
- 17 and 46 "Compacted N sstables to" per hour (most around 35/h)
Data Model:
The data model is made up of 6 column families. 3 are dynamic to capture the
time-line of 3 event types; each event creates a new column and the value is
the row key of the event. 3 have a static schema and store the event itself.
The largest event messages has 16 attributes. All are short text identifiers,
floating point numbers and timestamps. For storage in Cassandra every attribute
is converted to a string and stored with the utf8 validator.
Timeouts and Memory pressure:
The write-timeouts correlate with the hours of high (ca. >450/h) "GC for
ParNew". I never saw any read-timeouts. I set all timeouts to 20 seconds in
cassandra.yaml.
Cassandra comes under memory pressure ("Flushing CFS X to relieve memory
pressure") between 3 and 5 times a day. The tendency is for it to happen in the
afternoon and evening. But also sometimes right after 08:00 in the morning. In
about 75% of the cases it flushes one of the event column families, in 25% a
time-line column family.
Write Load:
We collect events for a theoretical universe of 2.2 million items -> there are
a max of 2.2 million rows in each of the time-line column families, but I
never saw an estimated row count in the cfstats of more than 1 million.
Roughly 1/3 of the entities receive a maximum of 3 events, one of each event
type, in a 15 minutes interval from 08:00 to 22:00. The other 2/3 receive 3
events 3 times a day. About 16'000 entities receive only one event type, but
about once in 3 minutes.
On a typical day the load adds up to about 70 to 80 million messages.
Not all messages are original though. The sources will re-send an event in
every interval if there are no new events. The noise ratio I do not know. I
guestimate it to be at least 50%. In case of a repeat the existing time-line
column and event row are updated with their previous values.
Read Load:
In one hour intervals we sample a time coherent snapshot of the events. To do
so we iterate over all rows in the three time-line column families and load the
value of the column that is most recent given a cut-off timestamp. The value is
the row key of the actual event, which we then load as well. We do that in
batches of 100 rows at a time.
Deletes:
Every night we delete all events that are older than 2 days. Again in batches
of 100 rows.
Thanks for helping!
Ralf
________________________________
From: Alain RODRIGUEZ [[email protected]]
Sent: Thursday, May 02, 2013 09:12
To: [email protected]
Subject: Re: How does a healthy node look like?
Well, maybe should you describe us your hardware and the C* release toi are
using. Also give us some metrics.
Le 30 avr. 2013 18:48, "Steppacher Ralf"
<[email protected]<mailto:[email protected]>>
a écrit :
Hi,
I have troubles finding some quantitative information as to how a healthy
Cassandra node should look like (CPU usage, number of flushes,SSTables,
compactions, GC), given a certain hardware spec and read/write load. I have
troubles gauging our first and only Cassandra node, whether it needs tuning or
is simply overloaded.
If anyone could point me to some data that would be very helpful.
(So far I have run the node with the default settings in cassandra.yaml and
cassandra-env. The log claims that the server is occasionally under memory
pressure and I get frequent timeouts for writes. I see what I think are many
flushes, compactions and GCs in the log. Some toying with heap and new gen
sizes, key cache, and the compaction throughput settings did not improve the
overall situation much.)
Thanks!
Ralf
