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From Ilya Kasnacheev <ilya.kasnach...@gmail.com>
Subject Re: Ignite Performance Issues when seeding data from Spark
Date Mon, 03 Dec 2018 06:33:38 GMT

This is somewhat expected since memory grids are very fast. Disk-based
database can't match memory grid's in-memory performance numbers.

Still, it should not degrade endlessly. What is the version that you are
on? I guess you may see improvements in the coming Apache Ignite 2.7.

DataStreamer should be very fast when used properly so there's no much
point of seeking an alternative.

Please also note that your cloud may start throttling IOPS once you start
endless writes. They allow you a burst period and then scale throughput
down. The solution here is to use more local disk-oriented instance and/or
use dedicated instance. I'm unsure if it applies to the one you're using

Ilya Kasnacheev

пн, 3 дек. 2018 г. в 01:55, kellan <kellan.burket@gmail.com>:

> I'm trying to seed about 500 million rows from a Spark DataFrame into a
> clean
> Ignite database, but running into serious performance issues once Ignite
> runs out of durable memory. I'm running 4 Ignite Nodes on Kubernetes
> cluster
> backed by AWS i3.2xl instances (8 CPUs per node, 60 GB Memory, 2TB SSD
> Local
> Storage). My configuration parameters per node are as follows:
> - 40GB of Available Memory
> - 20GB of Durable Memory
> - 8GB on the Java Heap
> While the nodes still have durable memory, they're writing to the cache at
> the rate of about 35k-40k a second. I'm expecting to take a performance hit
> once I run out of Durable Memory, but as soon as peristence kicks in, write
> performance spikes to about 15k/sec and steadily decreases over time, while
> the number of writes to disk steadily increases. My CPU usage also starts
> to
> slow down until Ignite is writing less than 5k a second and the CPU drops
> to
> less than a half core. I haven't let the performance continue to degrade to
> see what happens, but it shows no sign of beginning to stablize.
> I've tried all of Ignite's performance suggestions, including
> - breaking off the WAL and Storage into different disks
> - using local storage instead of EBS
> - checkpoint throttling
> - write throttling
> - adjusting the checkpoint page buffer size
> - adjusting the number of threads
> - adjusting swappiness
> In the end, I get the same results no matter what I do. Is write
> performance
> really this bad with persistence, and if not, what kind of performance
> should I be expecting and what can I do to improve it?
> Is there an alternative way to seed data that doesn't rely on the
> DataStreamers?
> --
> Sent from: http://apache-ignite-users.70518.x6.nabble.com/

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