Thanks Chris for looking at this. I was putting data at roughly the same 50
records per batch max. This issue was purely because of a bug in my
persistence logic that was leaking memory.
Overall, I haven't seen a lot of lag with kinesis + spark setup and I am
able to process records at roughly
curious about why you're only seeing 50 records max per batch.
how many receivers are you running? what is the rate that you're putting
data onto the stream?
per the default AWS kinesis configuration, the producer can do 1000 PUTs
per second with max 50k bytes per PUT and max 1mb per second per
Hi all
Sorry but this was totally my mistake. In my persistence logic, I was
creating async http client instance in RDD foreach but was never closing it
leading to memory leaks.
Apologies for wasting everyone's time.
Thanks,
Aniket
On 12 September 2014 02:20, Tathagata Das
I did change it to be 1 gb. It still ran out of memory but a little later.
The streaming job isnt handling a lot of data. In every 2 seconds, it
doesn't get more than 50 records. Each record size is not more than 500
bytes.
On Sep 11, 2014 10:54 PM, Bharat Venkat bvenkat.sp...@gmail.com wrote:
Which version of spark are you running?
If you are running the latest one, then could try running not a window but
a simple event count on every 2 second batch, and see if you are still
running out of memory?
TD
On Thu, Sep 11, 2014 at 10:34 AM, Aniket Bhatnagar
aniket.bhatna...@gmail.com