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From Aaron Morton <>
Subject Re: Read Latency
Date Tue, 19 Oct 2010 20:27:06 GMT

 Just wondering how many bytes you are returning to the client to get an idea of how slow
it is. 

The call to fastbinary is decoding the wireformat and creating the Python objects. When you
ask for 600,000 columns your are creating a lot of python objects. Each column will be a ColumnOrSuperColumn,
wrapping a Column, which has probably 2 Strings. So 2.4 million python objects.

Here's  my rough test script. 

def go(count):
    start = time.time()
    buffer = [
            "column_name_%s" % i, "row_size of something something", 0, 0))
        for i in range(count)
    print "Done in %s" % (time.time() - start)

On my machine that takes 13 seconds for 600,000 and 0.04 for 10,000. The fastbinary module
is running a lot faster because it's all in c.  It's not a great test but I think it gives
an idea of what you are asking for.

I think there is an element of python been slower than other languages. But IMHO you are asking
for a lot of data. Can you ask for less data? 

Out of interest are you able to try the avro client? It's still experimental (0.7 only) but
may give you something to compare it against. 

On 20 Oct, 2010,at 07:23 AM, Wayne <> wrote:

It is an entire row which is 600,000 cols. We pass a limit of 10million to make sure we get
it all. Our issue is that it seems Thrift itself has more overhead/latency added to a read
that Cassandra takes itself to do the read. If cfstats for the slowest node reports 2.25s
to us it is not acceptable that the data comes back to the client in 5.5s. After working with
Jonathon we have optimized Cassandra itself to return the quorum read in 2.7s but we still
have 3s getting lost in the thrift call (fastbinary.decode_binary).

We have seen this pattern totally hold for ms reads as well for a few cols, but it is easier
to look at things in seconds. If Cassandra can get the data off of the disks in 2.25s we expect
to have the data in a Python object in under 3s. That is a totally realistic expectation from
our experience. All latency needs to be pushed down to disk random read latency as that should
always be what takes the longest. Everything else is passing through memory.

On Tue, Oct 19, 2010 at 2:06 PM, aaron morton <> wrote:
I'm calling cassandra from Python and have not seen too many 3 second reads.

Your last email with log messages in it looks like your are asking for 10,000,000 columns.
How much data is this request actually transferring to the client? The column names suggest
only a few.

DEBUG [pool-1-thread-64] 2010-10-18 19:25:28,867 (line 471) strongread reading
data for SliceFromReadCommand(table='table', key='key1', column_parent='QueryPath(columnFamilyName='fact',
superColumnName='null', columnName='null')', start='503a', finish='503a7c', reversed=false,
count=10000000) from 698@/x.x.x.6


On 20 Oct 2010, at 06:18, Jonathan Ellis wrote:

> I would expect C++ or Java to be substantially faster than Python.
> However, I note that Hector (and I believe Pelops) don't yet use the
> newest, fastest Thrift library.
> On Tue, Oct 19, 2010 at 8:21 AM, Wayne <> wrote:
>> The changes seems to do the trick. We are down to about 1/2 of the original
>> quorum read performance. I did not see any more errors.
>> More than 3 seconds on the client side is still not acceptable to us. We
>> need the data in Python, but would we be better off going through Java or
>> something else to increase performance? All three seconds are taken up in
>> Thrift itself (fastbinary.decode_binary(self, iprot.trans, (self.__class__,
>> self.thrift_spec))) so I am not sure what other options we have.
>> Thanks for your help.
> --
> Jonathan Ellis
> Project Chair, Apache Cassandra
> co-founder of Riptano, the source for professional Cassandra support

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