Looking for heavy write optimization

Elastic Stack Elasticsearch
1

hi

I am writing a real time analytics tool using kafka,storm and elasticsearch
and want a elasticsearch that is write optimized for about 80K/sec
inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert my
doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance, anybody has
a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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2

What sort of hardware are you on?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: markw@campaignmonitor.com
web: www.campaignmonitor.com

On 28 May 2014 13:44, Zealot Yin 0xmalloc@gmail.com wrote:

hi

I am writing a real time analytics tool using kafka,storm and
elasticsearch and want a elasticsearch that is write optimized for about
80K/sec inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert my
doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance, anybody
has a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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3

CPU E5-2620 12 cores
MEM 64G
df -lhT
Filesystem Type Size Used Avail Use% Mounted on
/dev/sda3 ext2 1.4T 379G 962G 29% /home

uname -a
2.6.32_1-9-0-0 10 17:22:16 CST 2013 x86_64 x86_64 x86_64 GNU/Linux

elasticsearch started with bin/elasticsearch -Xms10g -Xmx10g
-Des.index.store.type=niofs -d

On Wednesday, May 28, 2014 11:49:17 AM UTC+8, Mark Walkom wrote:

What sort of hardware are you on?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: ma...@campaignmonitor.com <javascript:>
web: www.campaignmonitor.com

On 28 May 2014 13:44, Zealot Yin <0xma...@gmail.com <javascript:>> wrote:

hi

I am writing a real time analytics tool using kafka,storm and
elasticsearch and want a elasticsearch that is write optimized for about
80K/sec inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert my
doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance, anybody
has a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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For more options, visit https://groups.google.com/d/optout.

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4

and each machine has 3 instance

On Wednesday, May 28, 2014 11:55:49 AM UTC+8, Zealot Yin wrote:

CPU E5-2620 12 cores
MEM 64G
df -lhT
Filesystem Type Size Used Avail Use% Mounted on
/dev/sda3 ext2 1.4T 379G 962G 29% /home

uname -a
2.6.32_1-9-0-0 10 17:22:16 CST 2013 x86_64 x86_64 x86_64 GNU/Linux

elasticsearch started with bin/elasticsearch -Xms10g -Xmx10g
-Des.index.store.type=niofs -d

On Wednesday, May 28, 2014 11:49:17 AM UTC+8, Mark Walkom wrote:

What sort of hardware are you on?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: ma...@campaignmonitor.com
web: www.campaignmonitor.com

On 28 May 2014 13:44, Zealot Yin 0xma...@gmail.com wrote:

hi

I am writing a real time analytics tool using kafka,storm and
elasticsearch and want a elasticsearch that is write optimized for about
80K/sec inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert my
doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance, anybody
has a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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For more options, visit https://groups.google.com/d/optout.

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For more options, visit https://groups.google.com/d/optout.

5

You're probably running into I/O issues with multiple instances per
physical, are you monitoring your disk performance?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: markw@campaignmonitor.com
web: www.campaignmonitor.com

On 28 May 2014 13:56, Zealot Yin 0xmalloc@gmail.com wrote:

and each machine has 3 instance

On Wednesday, May 28, 2014 11:55:49 AM UTC+8, Zealot Yin wrote:

CPU E5-2620 12 cores
MEM 64G
df -lhT
Filesystem Type Size Used Avail Use% Mounted on
/dev/sda3 ext2 1.4T 379G 962G 29% /home

uname -a
2.6.32_1-9-0-0 10 17:22:16 CST 2013 x86_64 x86_64 x86_64 GNU/Linux

elasticsearch started with bin/elasticsearch -Xms10g -Xmx10g
-Des.index.store.type=niofs -d

On Wednesday, May 28, 2014 11:49:17 AM UTC+8, Mark Walkom wrote:

What sort of hardware are you on?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: ma...@campaignmonitor.com
web: www.campaignmonitor.com

On 28 May 2014 13:44, Zealot Yin 0xma...@gmail.com wrote:

hi

I am writing a real time analytics tool using kafka,storm and
elasticsearch and want a elasticsearch that is write optimized for about
80K/sec inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert
my doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance, anybody
has a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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.
For more options, visit https://groups.google.com/d/optout.

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6

io-util > 50% + and sometime 100%
i will try one big instance in one machine right now
do you have any* configure optimization suggestion*?

On Wednesday, May 28, 2014 11:59:45 AM UTC+8, Mark Walkom wrote:

You're probably running into I/O issues with multiple instances per
physical, are you monitoring your disk performance?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: ma...@campaignmonitor.com <javascript:>
web: www.campaignmonitor.com

On 28 May 2014 13:56, Zealot Yin <0xma...@gmail.com <javascript:>> wrote:

and each machine has 3 instance

On Wednesday, May 28, 2014 11:55:49 AM UTC+8, Zealot Yin wrote:

CPU E5-2620 12 cores
MEM 64G
df -lhT
Filesystem Type Size Used Avail Use% Mounted on
/dev/sda3 ext2 1.4T 379G 962G 29% /home

uname -a
2.6.32_1-9-0-0 10 17:22:16 CST 2013 x86_64 x86_64 x86_64 GNU/Linux

elasticsearch started with bin/elasticsearch -Xms10g -Xmx10g
-Des.index.store.type=niofs -d

On Wednesday, May 28, 2014 11:49:17 AM UTC+8, Mark Walkom wrote:

What sort of hardware are you on?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: ma...@campaignmonitor.com
web: www.campaignmonitor.com

On 28 May 2014 13:44, Zealot Yin 0xma...@gmail.com wrote:

hi

I am writing a real time analytics tool using kafka,storm and
elasticsearch and want a elasticsearch that is write optimized for about
80K/sec inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert
my doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance,
anybody has a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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7

You could test with a single index and get an idea of write performance on
single one. One nice thing about ES is it scales almost linear, more
concurrent indices setup for writing, better write performance.

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8

For maximum write performance, you should

  • use fastest disk subsystem (SSD)
  • use RAID 0 with expensive controller to max out IO bandwidth
  • do not run more than one ES instance per server
  • do not use virtual servers, use physical servers
  • for ES data folder, disable acess time flag (noatime), check filesystem
    settings for more tweaking
  • use mlockall and mmapfs (niofs is not faster than mmapfs)
  • us bulk indexing (note that UDP is not reliable network protocol)
  • reserve enough off-heap memory for mmapfs (you do not need large heaps
    for fast bulk indexing)
  • monitor network bandwidth for enough capacity
  • for high sustainable bulk write ES configuration, see
    Elasticsearch configuration for high sustainable bulk feed · GitHub
  • on SSD, disable Linux CFQ scheduler for noop scheduler, see Drew Raines'
    presentation https://speakerdeck.com/drewr/life-after-ec2

Jörg

On Wed, May 28, 2014 at 7:07 AM, 熊贻青 xiong.jaguar@gmail.com wrote:

You could test with a single index and get an idea of write performance on
single one. One nice thing about ES is it scales almost linear, more
concurrent indices setup for writing, better write performance.

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9

Hi,

I see Jorg already provided a nice list of suggestions. But check that FS
type - ext2! That's ancient! Try ext3, ext4, or xfs. If you turn off
journaling things will be faster. You are using UDP you said, so you must
be OK with some data loss.

Btw. SPM http://sematext.com/spm/ can monitor all 3 things you mentioned

  • Kafka - Storm - ES. May be helpful to have all these metrics in a single
    UI when optimizing things.

Otis

Performance Monitoring * Log Analytics * Search Analytics
Solr & Elasticsearch Support * http://sematext.com/

On Tuesday, May 27, 2014 11:55:49 PM UTC-4, Zealot Yin wrote:

CPU E5-2620 12 cores
MEM 64G
df -lhT
Filesystem Type Size Used Avail Use% Mounted on
/dev/sda3 ext2 1.4T 379G 962G 29% /home

uname -a
2.6.32_1-9-0-0 10 17:22:16 CST 2013 x86_64 x86_64 x86_64 GNU/Linux

elasticsearch started with bin/elasticsearch -Xms10g -Xmx10g
-Des.index.store.type=niofs -d

On Wednesday, May 28, 2014 11:49:17 AM UTC+8, Mark Walkom wrote:

What sort of hardware are you on?

Regards,
Mark Walkom

Infrastructure Engineer
Campaign Monitor
email: ma...@campaignmonitor.com
web: www.campaignmonitor.com

On 28 May 2014 13:44, Zealot Yin 0xma...@gmail.com wrote:

hi

I am writing a real time analytics tool using kafka,storm and
elasticsearch and want a elasticsearch that is write optimized for about
80K/sec inserts(7 machine cluster).

For the purpose of high performance i using bulk udp to batch insert my
doc(each doc is about 300B, only 4 field are indexed),and i'm using index.store.type=niofs
for index store(mmap cause io-util 100%),but it's still seem not good
enough for my scene, all thing i need is writing performance, anybody
has a idea for this problem?

here is my conf:

bootstrap.mlockall: true

threadpool.bulk.type: fixed

threadpool.bulk.size: 30

threadpool.bulk.queue_size: 500

index.refresh_interval: 50s

indices.store.throttle.type: merge

indices.store.throttle.max_bytes_per_sec: 80mb

indices.memory.index_buffer_size: 30%

indices.ttl.bulk_size: 100000

indices.memory.min_shard_index_buffer_size: 200mb

bulk.udp.enabled : true

bulk.udp.bulk_actions : 10000

bulk.udp.bulk_size : 20mb

bulk.udp.flush_interval : 10s

bulk.udp.concurrent_requests : 4000

bulk.udp.receive_buffer_size : 10mb

index.cache.field.expire: 10m

index.cache.field.max_size: 500000

index.cache.field.type: soft

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For more options, visit https://groups.google.com/d/optout.

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