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From "Pushkar Prasad" <pushkar.pra...@airtightnetworks.net>
Subject RE: Unable to fetch large amount of rows
Date Wed, 20 Mar 2013 17:41:37 GMT
Hi aaron.

 

I added pagination, and things seem to have started performing much better.
With 1000 page size, now able to fetch 500K records in 25-30 seconds.
However, I'd like to point you to some interesting observations:

 

+ Did run cfhistograms, the results are interesting (Note: row cache is
disabled):

+++ When query made on node on which all the records are present

        + 75% time is spent on disk latency

        + Example: When 50 K entries were fetched, it took 2.65 seconds, out
of which 1.92 seconds were spent in disk latency

+++ When query made on node on which all the records are not present

        + Considerable amount of time is spent on things other than disk
latency (probably deserialization/serialization, network, etc.)

        + Example: When 50 K entries were fetched, it took 5.74 seconds, out
of which 2.21 seconds were spent in disk latency.

 

I've used Astyanax to run the above queries. The results were same when run
with different data points. Compaction has not been done after data
population yet.

 

I've a few questions:

1) Is it necessary to fetch the records in natural order of comparator
column in order to get a high throughput? I'm trying to fetch all the
records for a particular partition ID without any ordering on comparator
column. Would that slow down the response? Consider that timestamp is
partitionId, and MacAddress is natural comparator column. 

    + If my query is 

        -   select * from schema where timestamp = '..' ORDER BY MacAddress,
would that be faster than, say

        -   select * from schema where timestamp = '..' 

2) Why does response time suffer when query is made on a node on which
records to be returned are not present? In order to be able to get better
response when queried from a different node, can something be done?

 

Thanks

Pushkar

  _____  

From: aaron morton [mailto:aaron@thelastpickle.com] 
Sent: 20 March 2013 15:02
To: user@cassandra.apache.org
Subject: Re: Unable to fetch large amount of rows

 

The query returns fine if I request for lesser number of entries (takes 15
seconds for returning 20K records). 

That feels a little slow, but it depends on the data model, the query type
and the server and a bunch of other things. 

 

However, as I increase the limit on
number of entries, the response begins to slow down. It results in
TimedOutException.

Make many smaller requests. 

This is often faster.

 

Isn't it the case that all the data for a partitionID is stored sequentially
in disk?

Yes and no. 

In each file all the columns on one partition / row are stored in comparator
order. But there may be many files. 

 

If that is so, then why does fetching this data take such a long
amount of time?

You need to work out where the time is being spent. 

Add timing to your app, use nodetool proxyhistograms to see how long the
requests takes at the co-ordinator, use nodetool histograms to see how long
it takes at the disk level. 

 

Look at your data model, are you reading data in the natural order of the
comparator. 

 

If disk throughput is 40 MB/s, then assuming sequential
reads, the response should come pretty quickly.

There is more involved than doing one read from disk and returning it. 

 

If it is stored
sequentially, why does C* take so much time to return the records?

It is always going to take time to read 500,000 columns. It will take time
on the client to allocate the 2 to 4 million objects needed to represent
them. And once it comes to allocating those objects it will probably take
more than 40MB in ram. 

 

Do some tests at a smaller scale, start with 500 or 1000 columns then get
bigger, to get a feel for what is practical in your environment. Often it's
better to make many smaller / constant size requests. 

 

Cheers

 

-----------------

Aaron Morton

Freelance Cassandra Consultant

New Zealand

 

@aaronmorton

http://www.thelastpickle.com

 

On 19/03/2013, at 9:38 PM, Pushkar Prasad
<pushkar.prasad@airtightnetworks.net> wrote:





Aaron,

Thanks for your reply. Here are the answers to questions you had asked:

I am trying to read all the rows which have a particular TimeStamp. In my
data base, there are 500 K entries for a particular TimeStamp. That means
about 40 MB of data.

The query returns fine if I request for lesser number of entries (takes 15
seconds for returning 20K records). However, as I increase the limit on
number of entries, the response begins to slow down. It results in
TimedOutException.

Isn't it the case that all the data for a partitionID is stored sequentially
in disk? If that is so, then why does fetching this data take such a long
amount of time? If disk throughput is 40 MB/s, then assuming sequential
reads, the response should come pretty quickly. Is it not the case that the
data I am trying to fetch would be sequentially stored? If it is stored
sequentially, why does C* take so much time to return the records? And if
data is stored sequentially, is there any alternative that would allow me to
fetch all the records quickly (by sequential disk fetch)?

Thanks
Pushkar

-----Original Message-----
From: aaron morton [mailto:aaron@thelastpickle.com] 
Sent: 19 March 2013 13:11
To: user@cassandra.apache.org
Subject: Re: Unable to fetch large amount of rows




I have 1000 timestamps, and for each timestamp, I have 500K different

MACAddress.
So you are trying to read about 2 million columns ? 
500K MACAddresses each with 3 other columns? 




When I run the following query, I get RPC Timeout exceptions:

What is the exception? 
Is it a client side socket timeout or a server side TimedOutException ?

If my understanding is correct then try reading fewer columns and/or check
the server side for logs. It sounds like you are trying to read too much
though. 

Cheers



-----------------
Aaron Morton
Freelance Cassandra Consultant
New Zealand

@aaronmorton
http://www.thelastpickle.com

On 19/03/2013, at 3:51 AM, Pushkar Prasad
<pushkar.prasad@airtightnetworks.net> wrote:




Hi,

I have following schema:

TimeStamp
MACAddress
Data Transfer
Data Rate
LocationID

PKEY is (TimeStamp, MACAddress). That means partitioning is on TimeStamp,

and data is ordered by MACAddress, and stored together physically (let me
know if my understanding is wrong). I have 1000 timestamps, and for each
timestamp, I have 500K different MACAddress.




When I run the following query, I get RPC Timeout exceptions:


Select * from db_table where Timestamp='...'

>From my understanding, this should give all the rows with just one disk

seek, as all the records for a particular timeStamp. This should be very
quick, however, clearly, that doesn't seem to be the case. Is there
something I am missing here? Your help would be greatly appreciated.




Thanks
PP





 


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