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Posted to user@ignite.apache.org by Naveen <na...@gmail.com> on 2018/11/29 09:39:31 UTC
Effective way to pre-load data around 10 TB
HI
We are using Ignite 2.6.
AS we already know, after the cluster restart, every GET call gets data from
DISK for the first time and loads into RAM and subsequent calls data will
read from RAM only..
First time GET calls are 10 times slower than read from RAM, which we wanted
to avoid by pre-loading the entire data into RAM after the cluster restart.
So here am exploring efficient ways to read entire data once so that it will
pre-load the data into RAM, so GET calls from client will be much faster.
Running ScanQuery on all the partitions of the cache would be good way to
read data very fast in very less time ? OR any other better ways of
achieving the same
Thanks
Naveen
--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/
RE: Effective way to pre-load data around 10 TB
Posted by Stanislav Lukyanov <st...@gmail.com>.
The problem might be in HDD not performing fast enough, and also suffering from random reads
(IgniteCache::preloadPartition at least tries to read sequentially).
Also, do you have enough RAM to store all data? If not, you shouldn’t preload all the data, just the amount that fits into RAM.
Anyway, I think that your best chance is to implement the same thing https://issues.apache.org/jira/browse/IGNITE-8873 does.
E.g. you can try to backport the commit on top of 2.6.
Stan
From: Naveen
Sent: 5 декабря 2018 г. 7:59
To: user@ignite.apache.org
Subject: RE: Effective way to pre-load data around 10 TB
Thanks Stan, this may take little longer time to implement, we are in hurry
to build this functionality of preloading the data.
Can someone correct me how to improve this pre-load process.
This is how we are preloading.
1. Send an Async request for all the partitions with the below code, below
loop will get repeated for all the caches we have
for (int i = 0; i < affinity.partitions(); i++) {
List<String> cacheList = Arrays.asList(cacheName);
affinityRunAsync= compute.affinityRunAsync(cacheList, i, new
DataPreloadTask(cacheList, i));
}
2. Inside DataPreloadTask which is running on the Ignite node.
I just execute scan query for the given partition and iterate thru the
cursor. not doing anything else.
IgniteCache<Object, Object> igniteCache = localIgnite.cache(cacheName);
try (QueryCursor<Cache.Entry<K, V>> cursor = igniteCache.query(new
ScanQuery().setPartition(partitionNo))) {
for (Cache.Entry<K, V> entry : cursor) {
}
}
}
However, this seems to be quite slow. Taking more than 3 hours to read one
cache which has 400 M records. We have 30 such caches to load data, so not
fining this so efficient.
Can we improve this, we do have very powerful machines with 128 CPU, 2 TB
RAM, HDD, our CPU utilization is also not so high when we are preloading the
data.
Changing thread pool size will have any impact this read ???
Thanks
Naveen
--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/
RE: Effective way to pre-load data around 10 TB
Posted by Naveen <na...@gmail.com>.
Thanks Stan, this may take little longer time to implement, we are in hurry
to build this functionality of preloading the data.
Can someone correct me how to improve this pre-load process.
This is how we are preloading.
1. Send an Async request for all the partitions with the below code, below
loop will get repeated for all the caches we have
for (int i = 0; i < affinity.partitions(); i++) {
List<String> cacheList = Arrays.asList(cacheName);
affinityRunAsync= compute.affinityRunAsync(cacheList, i, new
DataPreloadTask(cacheList, i));
}
2. Inside DataPreloadTask which is running on the Ignite node.
I just execute scan query for the given partition and iterate thru the
cursor. not doing anything else.
IgniteCache<Object, Object> igniteCache = localIgnite.cache(cacheName);
try (QueryCursor<Cache.Entry<K, V>> cursor = igniteCache.query(new
ScanQuery().setPartition(partitionNo))) {
for (Cache.Entry<K, V> entry : cursor) {
}
}
}
However, this seems to be quite slow. Taking more than 3 hours to read one
cache which has 400 M records. We have 30 such caches to load data, so not
fining this so efficient.
Can we improve this, we do have very powerful machines with 128 CPU, 2 TB
RAM, HDD, our CPU utilization is also not so high when we are preloading the
data.
Changing thread pool size will have any impact this read ???
Thanks
Naveen
--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/
RE: Effective way to pre-load data around 10 TB
Posted by Stanislav Lukyanov <st...@gmail.com>.
Hi,
Currently the best option is IgniteCache::preloadPartition method added in
https://issues.apache.org/jira/browse/IGNITE-8873.
There is a JIRA ticket to allow pre-loading data before the node joins the cluster:
https://issues.apache.org/jira/browse/IGNITE-10152.
Stan
From: Naveen
Sent: 29 ноября 2018 г. 12:39
To: user@ignite.apache.org
Subject: Effective way to pre-load data around 10 TB
HI
We are using Ignite 2.6.
AS we already know, after the cluster restart, every GET call gets data from
DISK for the first time and loads into RAM and subsequent calls data will
read from RAM only..
First time GET calls are 10 times slower than read from RAM, which we wanted
to avoid by pre-loading the entire data into RAM after the cluster restart.
So here am exploring efficient ways to read entire data once so that it will
pre-load the data into RAM, so GET calls from client will be much faster.
Running ScanQuery on all the partitions of the cache would be good way to
read data very fast in very less time ? OR any other better ways of
achieving the same
Thanks
Naveen
--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/