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From Wayne <>
Subject Re: Read Latency
Date Tue, 19 Oct 2010 22:30:47 GMT
I am not sure how many bytes, but we do convert the cassandra object that is
returned in 3s into a dictionary in ~1s and then again into a custom python
object in about ~1.5s. Expectations are based on this timing. If we can
convert what thrift returns into a completely new python object in 1s why
does thrift need 3s to give it to us?

To us it is like the MySQL client we use in python. It is really C wrapped
in python and adds almost zero overhead to the time it takes mysql to return
the data. That is the expectation we have and the performance we are looking
to get to. Disk I/O + 20%.

We are returning one big row and this is not our normal use case but a
requirement for us to use Cassandra. We need to get all data for a specific
value, as this is a secondary index. It is like getting all users in the
state of CA. CA is the key and there is a column for every user id. We are
testing with 600,000 but this will grow to 10+ million in the future.

We can not test .7 as we are only using .6.6. We are trying to evaluate
Cassandra and stability is one concern so .7 is definitely not for us at
this point.


On Tue, Oct 19, 2010 at 4:27 PM, Aaron Morton <>wrote:

>  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 = [
>         ttypes.ColumnOrSuperColumn(column=ttypes.Column(
>             "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.
> Aaron
> 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:
>> Wayne,
>> 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
>> Aaron
>> 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
>> > http://riptanocom <>

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