I know that shards are usually balanced amongst the nodes in an
elasticsearch cluster, but is there a way to balance the primaries.
We have a three node cluster with 3 shards and 1 replica. We have
observed recently that all three of the primary shards are assigned to
one node. Based on the fact that indexing is routed to the primary,
this could mean that one machine is dedicatedbto indexing. Is there a
way to balance the primaries against nodes, or is it best to increase
shards to 6? I'm afraid if I do that, there is still no guarantee
that each node will have close to two primaries on it.
Even if you have 3 primaries allocated on a single node, with replication,
other nodes will also be busy indexing. In general, there isn't a lot of
difference between a primary and a replica, so there isn't an effort to
balance primaries (or force it). There are some cases where primaries might
work a bit more, for example, when doing searches / get and explicitly
asking them to be executed on the primary shard, but thats not the common
case.
I know that shards are usually balanced amongst the nodes in an
elasticsearch cluster, but is there a way to balance the primaries.
We have a three node cluster with 3 shards and 1 replica. We have
observed recently that all three of the primary shards are assigned to
one node. Based on the fact that indexing is routed to the primary,
this could mean that one machine is dedicatedbto indexing. Is there a
way to balance the primaries against nodes, or is it best to increase
shards to 6? I'm afraid if I do that, there is still no guarantee
that each node will have close to two primaries on it.
for better peformance is better I use 4 small instance or use a large in the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2 hard drive instance and is 64 bits.
for better peformance is better I use 4 small instance or use a large in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2
hard drive instance and is 64 bits.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large in the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2 hard drive instance and is 64 bits.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large in the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2 hard drive instance and is 64 bits.
we have similar requirements and we decided to go for the large
instances. The search times were ok on the small instances (90% below
200ms) but the indexing suffered significantly (only 30% below 200ms, we
have requirements for indexing as well). In comparison the large
instances handle both search and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large in the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2 hard drive instance and is 64 bits.
we have similar requirements and we decided to go for the large instances.
The search times were ok on the small instances (90% below 200ms) but the
indexing suffered significantly (only 30% below 200ms, we have requirements
for indexing as well). In comparison the large instances handle both search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2
hard drive instance and is 64 bits.
In general, I suggest using the xlarge instances in Amazon, simply because
of the higher IO they provide and better performance consistency (at least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below 200ms) but the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2
hard drive instance and is 64 bits.
In general, I suggest using the xlarge instances in Amazon, simply because
of the higher IO they provide and better performance consistency (at least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below 200ms) but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have 2
hard drive instance and is 64 bits.
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge (more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data locations
does not depend on the number of shards. In other words, even a singel shard
allocated on a node will make use of all the data locations.
In general, I suggest using the xlarge instances in Amazon, simply
because
of the higher IO they provide and better performance consistency (at
least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below 200ms) but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64 bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large have
2
hard drive instance and is 64 bits.
So, I'd better install the machine (m1.xlarge) 4 ES, an ES for each point
data to different HD. It should be better because at the time of the search
are going to be in parallel searches using 4 hds, with different processors.
I set up each instance of ES with 3GB of ram.
If I use the machine (m1.large) I would install only 2 ES, one for each
allocate the same HD and 3GB of ram for each ES.
is it?
****** m1.xlarge Config
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
****** m1.large Config:
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Heya,
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge (more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data locations
does not depend on the number of shards. In other words, even a singel
shard
allocated on a node will make use of all the data locations.
-shay.banon
In general, I suggest using the xlarge instances in Amazon, simply
because
of the higher IO they provide and better performance consistency (at
least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below 200ms)
but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64
bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt
whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a
large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large
have 2
hard drive instance and is 64 bits.
So, I'd better install the machine (m1.xlarge) 4 ES, an ES for each point
data to different HD. It should be better because at the time of the search
are going to be in parallel searches using 4 hds, with different processors.
I set up each instance of ES with 3GB of ram.
If I use the machine (m1.large) I would install only 2 ES, one for each
allocate the same HD and 3GB of ram for each ES.
is it?
****** m1.xlarge Config
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
****** m1.large Config:
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Heya,
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge (more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data
locations
does not depend on the number of shards. In other words, even a singel
shard
allocated on a node will make use of all the data locations.
-shay.banon
In general, I suggest using the xlarge instances in Amazon, simply
because
of the higher IO they provide and better performance consistency (at
least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below 200ms)
but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle
both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64
bits
and have two hard drive.
Today I have 300GB of index which is distributed in three machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt
whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a
large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large
have 2
hard drive instance and is 64 bits.
For my experimenting with the lucene, is better distribute the load between
the drives. Using an ES for each hard drive, I guarantee a better
distribution between HD. Ex: One shard of 15GB per HD. During the seach i
will have better parallelism since I have one HD and one processor for a
specific search.
ex: When the User do a search we have the parallel processing of 4 hds and 4
processors, ensuring a faster response, since it was set up only one shard
by ES.
So, I'd better install the machine (m1.xlarge) 4 ES, an ES for each point
data to different HD. It should be better because at the time of the search
are going to be in parallel searches using 4 hds, with different processors.
I set up each instance of ES with 3GB of ram.
If I use the machine (m1.large) I would install only 2 ES, one for each
allocate the same HD and 3GB of ram for each ES.
is it?
****** m1.xlarge Config
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
****** m1.large Config:
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Heya,
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge
(more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data
locations
does not depend on the number of shards. In other words, even a singel
shard
allocated on a node will make use of all the data locations.
-shay.banon
In general, I suggest using the xlarge instances in Amazon, simply
because
of the higher IO they provide and better performance consistency (at
least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below 200ms)
but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle
both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have
and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is 64
bits
and have two hard drive.
Today I have 300GB of index which is distributed in three
machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt
whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a
large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and large
have 2
hard drive instance and is 64 bits.
In master version, you can specify several data locations so a single
instance can use several drives, I thought you were referring to that in
your previous mail.
For my experimenting with the lucene, is better distribute the load between
the drives. Using an ES for each hard drive, I guarantee a better
distribution between HD. Ex: One shard of 15GB per HD. During the seach i
will have better parallelism since I have one HD and one processor for a
specific search.
ex: When the User do a search we have the parallel processing of 4 hds and
4 processors, ensuring a faster response, since it was set up only one shard
by ES.
So, I'd better install the machine (m1.xlarge) 4 ES, an ES for each
point data to different HD. It should be better because at the time of the
search are going to be in parallel searches using 4 hds, with different
processors.
I set up each instance of ES with 3GB of ram.
If I use the machine (m1.large) I would install only 2 ES, one for each
allocate the same HD and 3GB of ram for each ES.
is it?
****** m1.xlarge Config
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
****** m1.large Config:
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Heya,
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge
(more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data
locations
does not depend on the number of shards. In other words, even a singel
shard
allocated on a node will make use of all the data locations.
-shay.banon
In general, I suggest using the xlarge instances in Amazon, simply
because
of the higher IO they provide and better performance consistency
(at
least
based on what users have seen).
we have similar requirements and we decided to go for the large
instances.
The search times were ok on the small instances (90% below
200ms) but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances handle
both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you have
and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15 LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is
64
bits
and have two hard drive.
Today I have 300GB of index which is distributed in three
machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt
whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15 small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use a
large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and
large
have 2
hard drive instance and is 64 bits.
Using the version of the master, if I set 4 shard, I guarantee that I will
have a shard in each hd?
Like if i have four shard, each shard of 15GB, I guarantee you'll have one
shard of 15GB in each HD?
In master version, you can specify several data locations so a single
instance can use several drives, I thought you were referring to that in
your previous mail.
For my experimenting with the lucene, is better distribute the load
between the drives. Using an ES for each hard drive, I guarantee a better
distribution between HD. Ex: One shard of 15GB per HD. During the seach i
will have better parallelism since I have one HD and one processor for a
specific search.
ex: When the User do a search we have the parallel processing of 4 hds
and 4 processors, ensuring a faster response, since it was set up only one
shard by ES.
So, I'd better install the machine (m1.xlarge) 4 ES, an ES for each
point data to different HD. It should be better because at the time of the
search are going to be in parallel searches using 4 hds, with different
processors.
I set up each instance of ES with 3GB of ram.
If I use the machine (m1.large) I would install only 2 ES, one for
each allocate the same HD and 3GB of ram for each ES.
is it?
****** m1.xlarge Config
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
****** m1.large Config:
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Heya,
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge
(more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data
locations
does not depend on the number of shards. In other words, even a
singel shard
allocated on a node will make use of all the data locations.
-shay.banon
In general, I suggest using the xlarge instances in Amazon,
simply
because
of the higher IO they provide and better performance consistency
(at
least
based on what users have seen).
we have similar requirements and we decided to go for the
large
instances.
The search times were ok on the small instances (90% below
200ms) but
the
indexing suffered significantly (only 30% below 200ms, we have
requirements
for indexing as well). In comparison the large instances
handle both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you
have and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15
LARGE
instance instance. I need to search back in less than 200ms on
average.
In the amazon price of 4 small is the same price of one large.
The small is 32 bit and have only one hard drive. The large is
64
bits
and have two hard drive.
Today I have 300GB of index which is distributed in three
machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt
whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15
small
instance instance. I need to search back in less than 200ms on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use
a large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and
large
have 2
hard drive instance and is 64 bits.
No, as I explained before, using multi drives does not mean that each shard
will be on a single drive, it means that the files composing the Lucene
index will exist on different drives, so a single shard will span all drives
potentially.
Using the version of the master, if I set 4 shard, I guarantee that I will
have a shard in each hd?
Like if i have four shard, each shard of 15GB, I guarantee you'll have one
shard of 15GB in each HD?
In master version, you can specify several data locations so a single
instance can use several drives, I thought you were referring to that in
your previous mail.
For my experimenting with the lucene, is better distribute the load
between the drives. Using an ES for each hard drive, I guarantee a better
distribution between HD. Ex: One shard of 15GB per HD. During the seach i
will have better parallelism since I have one HD and one processor for a
specific search.
ex: When the User do a search we have the parallel processing of 4 hds
and 4 processors, ensuring a faster response, since it was set up only one
shard by ES.
So, I'd better install the machine (m1.xlarge) 4 ES, an ES for each
point data to different HD. It should be better because at the time of the
search are going to be in parallel searches using 4 hds, with different
processors.
I set up each instance of ES with 3GB of ram.
If I use the machine (m1.large) I would install only 2 ES, one for
each allocate the same HD and 3GB of ram for each ES.
is it?
****** m1.xlarge Config
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
****** m1.large Config:
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Heya,
Its tricky to choose between c1.xlarge (more CPU) and m1.xlarge
(more
memory). I suggest going with the m1.xlarge as more memory tend
to outweigh faster CPU.
Regarding the drives. the new option to specify multiple data
locations
does not depend on the number of shards. In other words, even a
singel shard
allocated on a node will make use of all the data locations.
-shay.banon
In general, I suggest using the xlarge instances in Amazon,
simply
because
of the higher IO they provide and better performance consistency
(at
least
based on what users have seen).
we have similar requirements and we decided to go for the
large
instances.
The search times were ok on the small instances (90% below
200ms) but
the
indexing suffered significantly (only 30% below 200ms, we
have
requirements
for indexing as well). In comparison the large instances
handle both
search
and indexing with 95% below 200ms.
Bear in mind this is specific to the type of documents you
have and
the
searches you perform. Go for a 24h test I'd suggest.
Regards,
Pavel
On 13.10.2011 01:26, Gustavo Maia wrote:
correct:
My question would be to build a cluster of 40 SMALL or 15
LARGE
instance instance. I need to search back in less than 200ms
on
average.
In the amazon price of 4 small is the same price of one
large.
The small is 32 bit and have only one hard drive. The large
is 64
bits
and have two hard drive.
Today I have 300GB of index which is distributed in three
machines
that each machine has 6 15k rpm hard drive.
And doing this study was to migrate to the Amazon. So I doubt
whether
this is best 4 small or 1 large.
My question would be to build a cluster of 40 large or 15
small
instance instance. I need to search back in less than 200ms
on
average.
Is it possible to do this using elasticsearch at amazon?
for better peformance is better I use 4 small instance or use
a large
in
the amazon cloud?
Small instance is 32 bits with one hard drive instance, and
large
have 2
hard drive instance and is 64 bits.
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