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From "ZAIDI, ASAD A" <>
Subject RE: Partition range incremental repairs
Date Mon, 19 Jun 2017 19:07:48 GMT
Few options that you can consider to improve repair time are:

§  Un-throttle streamthroughput & interdcstreamthroughput , at least for the duration
of repair.

§  Increase number of job threads i.e. to use –j option

§  Use subrange repair options

§  implement jumbo frames on your internode- communication network cards on your C* host

§  If possible, reduce # of vnodes!

From: Chris Stokesmore []
Sent: Monday, June 19, 2017 4:50 AM
Subject: Re: Partition range incremental repairs

Anyone have anymore thoughts on this at all? Struggling to understand it..

On 9 Jun 2017, at 11:32, Chris Stokesmore <<>>

Hi Anuj,

Thanks for the reply.

1). We are using Cassandra 2.2.8, and our repair commands we are comparing are
"nodetool repair --in-local-dc --partitioner-range” and
"nodetool repair --in-local-dc”
Since 2.2 I believe inc repairs are the default - that seems to be confirmed in the logs that
list the repair details when a repair starts.

2) From looks at a few runsr, on average:
with -pr repairs, each node is approx 6.5 - 8 hours, so a total over the 7 nodes of 53 hours
With just inc repairs, each node ~26 - 29 hours, so a total of 193

3) we currently have two DCs in total, the ‘production’ ring with 7 nodes and RF=3, and
a testing ring with one single node and RF=1 for our single keyspace we currently use.

4) Yeah that number came from the Cassandra repair logs from an inc repair, I can share the
number reports when using a pr repair later this evening when the currently running repair
has completed.

Many thanks for the reply again,


On 6 Jun 2017, at 17:50, Anuj Wadehra <<>>

Hi Chris,

Can your share following info:

1. Exact repair commands you use for inc repair and pr repair

2. Repair time should be measured at cluster level for inc repair. So, whats the total time
it takes to run repair on all nodes for incremental vs pr repairs?

3. You are repairing one dc DC3. How many DCs are there in total and whats the RF for keyspaces?
Running pr on a specific dc would not repair entire data.

4. 885 ranges? From where did you get this number? Logs? Can you share the number ranges printed
in logs for both inc and pr case?


Sent from Yahoo Mail on Android<>

On Tue, Jun 6, 2017 at 9:33 PM, Chris Stokesmore
<<>> wrote:
Thank you for the excellent and clear description of the different versions of repair Anuj,
that has cleared up what I expect to be happening.

The problem now is in our cluster, we are running repairs with options (parallelism: parallel,
primary range: false, incremental: true, job threads: 1, ColumnFamilies: [], dataCenters:
[DC3], hosts: [], # of ranges: 885) and when we do our repairs are taking over a day to complete
when previously when running with the partition range option they were taking more like 8-9

As I understand it, using incremental should have sped this process up as all three sets of
data on each repair job should be marked as repaired however this does not seem to be the
case. Any ideas?


On 6 Jun 2017, at 16:08, Anuj Wadehra <<>>

Hi Chris,

Using pr with incremental repairs does not make sense. Primary range repair is an optimization
over full repair. If you run full repair on a n node cluster with RF=3, you would be repairing
each data thrice.
E.g. in a 5 node cluster with RF=3, a range may exist on node A,B and C . When full repair
is run on node A, the entire data in that range gets synced with replicas on node B and C.
Now, when you run full repair on nodes B and C, you are wasting resources on repairing data
which is already repaired.

Primary range repair ensures that when you run repair on a node, it ONLY repairs the data
which is owned by the node. Thus, no node repairs data which is not owned by it and must be
repaired by other node. Redundant work is eliminated.

Even in pr, each time you run pr on all nodes, you repair 100% of data. Why to repair complete
data in each cycle?? ..even data which has not even changed since the last repair cycle?

This is where Incremental repair comes as an improvement. Once repaired, a data would be marked
repaired so that the next repair cycle could just focus on repairing the delta. Now, lets
go back to the example of 5 node cluster with RF =3.This time we run incremental repair on
all nodes. When you repair entire data on node A, all 3 replicas are marked as repaired. Even
if you run inc repair on all ranges on the second node, you would not re-repair the already
repaired data. Thus, there is no advantage of repairing only the data owned by the node (primary
range of the node). You can run inc repair on all the data present on a node and Cassandra
would make sure that when you repair data on other nodes, you only repair unrepaired data.


Sent from Yahoo Mail on Android<>

On Tue, Jun 6, 2017 at 4:27 PM, Chris Stokesmore
<<>> wrote:
Hi all,

Wondering if anyone had any thoughts on this? At the moment the long running repairs cause
us to be running them on two nodes at once for a bit of time, which obivould increases the
cluster load.

On 2017-05-25 16:18 (+0100), Chris Stokesmore <<>>
> Hi,>
> We are running a 7 node Cassandra 2.2.8 cluster, RF=3, and had been running repairs with
the -pr option, via a cron job that runs on each node once per week.>
> We changed that as some advice on the Cassandra IRC channel said it would cause more
anticompaction and
says 'Performing partitioner range repairs by using the -pr option is generally considered
a good choice for doing manual repairs. However, this option cannot be used with incremental
repairs (default for Cassandra 2.2 and later)'
> Only problem is our -pr repairs were taking about 8 hours, and now the non-pr repair
are taking 24+ - I guess this makes sense, repairing 1/7 of data increased to 3/7, except
I was hoping to see a speed up after the first loop through the cluster as each repair will
be marking much more data as repaired, right?>
> Is running -pr with incremental repairs really that bad? >
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