Concurrent searches over same dataset degrades performance

Elastic Stack Elasticsearch
1

Hi,

I was trying Filtered query (default search type) to fetch first 8k out of
approx 170k matched records. I noticed that on an average query took around
500ms (response.getTookInMillis()). But, when I tried 4 concurrent searches
over same dataset (in ideal scenario dataset will be different), I noticed
that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important, but,
curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each doc
contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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2

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan vishal423@gmail.com wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k out of
approx 170k matched records. I noticed that on an average query took around
500ms (response.getTookInMillis()). But, when I tried 4 concurrent searches
over same dataset (in ideal scenario dataset will be different), I noticed
that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important, but,
curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each doc
contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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3

Sorry I overlooked it, you use getTookInMillis()

Maybe the extra time is spent because you use a range filter which is not
cached?

Jörg

On Fri, Apr 17, 2015 at 3:02 PM, joergprante@gmail.com <
joergprante@gmail.com> wrote:

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan vishal423@gmail.com
wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k out
of approx 170k matched records. I noticed that on an average query took
around 500ms (response.getTookInMillis()). But, when I tried 4 concurrent
searches over same dataset (in ideal scenario dataset will be different), I
noticed that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important,
but, curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each doc
contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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4

ES query time as given by search response object
(response.getTookInMillis())

Regards,
Vishal

On Friday, April 17, 2015 at 6:32:56 PM UTC+5:30, Jörg Prante wrote:

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan <vish...@gmail.com
<javascript:>> wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k out
of approx 170k matched records. I noticed that on an average query took
around 500ms (response.getTookInMillis()). But, when I tried 4 concurrent
searches over same dataset (in ideal scenario dataset will be different), I
noticed that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important,
but, curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each doc
contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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5

I doubt that's the cause as it should also affect sequential searches.

Regards,
Vishal

On Friday, April 17, 2015 at 6:34:24 PM UTC+5:30, Jörg Prante wrote:

Sorry I overlooked it, you use getTookInMillis()

Maybe the extra time is spent because you use a range filter which is not
cached?

Jörg

On Fri, Apr 17, 2015 at 3:02 PM, joerg...@gmail.com <javascript:> <
joerg...@gmail.com <javascript:>> wrote:

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan <vish...@gmail.com
<javascript:>> wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k out
of approx 170k matched records. I noticed that on an average query took
around 500ms (response.getTookInMillis()). But, when I tried 4 concurrent
searches over same dataset (in ideal scenario dataset will be different), I
noticed that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important,
but, curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each doc
contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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6

Do you round-robin the four concurrent searches over the cluster nodes?

Jörg

On Fri, Apr 17, 2015 at 3:38 PM, Vishal Mahajan vishal423@gmail.com wrote:

I doubt that's the cause as it should also affect sequential searches.

Regards,
Vishal

On Friday, April 17, 2015 at 6:34:24 PM UTC+5:30, Jörg Prante wrote:

Sorry I overlooked it, you use getTookInMillis()

Maybe the extra time is spent because you use a range filter which is not
cached?

Jörg

On Fri, Apr 17, 2015 at 3:02 PM, joerg...@gmail.com joerg...@gmail.com
wrote:

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan vish...@gmail.com
wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k out
of approx 170k matched records. I noticed that on an average query took
around 500ms (response.getTookInMillis()). But, when I tried 4 concurrent
searches over same dataset (in ideal scenario dataset will be different), I
noticed that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important,
but, curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each doc
contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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7

I have single node cluster. Not sure what you mean by round robin in
concurrent searches.

Regards,
Vishal
On Apr 17, 2015 7:26 PM, "joergprante@gmail.com" joergprante@gmail.com
wrote:

Do you round-robin the four concurrent searches over the cluster nodes?

Jörg

On Fri, Apr 17, 2015 at 3:38 PM, Vishal Mahajan vishal423@gmail.com
wrote:

I doubt that's the cause as it should also affect sequential searches.

Regards,
Vishal

On Friday, April 17, 2015 at 6:34:24 PM UTC+5:30, Jörg Prante wrote:

Sorry I overlooked it, you use getTookInMillis()

Maybe the extra time is spent because you use a range filter which is
not cached?

Jörg

On Fri, Apr 17, 2015 at 3:02 PM, joerg...@gmail.com joerg...@gmail.com
wrote:

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan vish...@gmail.com
wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k
out of approx 170k matched records. I noticed that on an average query took
around 500ms (response.getTookInMillis()). But, when I tried 4 concurrent
searches over same dataset (in ideal scenario dataset will be different), I
noticed that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important,
but, curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each
doc contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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8

You can not expect a single node cluster can work faster when being
searched concurrently. Four concurrent searches require four times the
resources, such as CPU and memory.

Jörg

On Fri, Apr 17, 2015 at 4:21 PM, Vishal Mahajan vishal423@gmail.com wrote:

I have single node cluster. Not sure what you mean by round robin in
concurrent searches.

Regards,
Vishal
On Apr 17, 2015 7:26 PM, "joergprante@gmail.com" joergprante@gmail.com
wrote:

Do you round-robin the four concurrent searches over the cluster nodes?

Jörg

On Fri, Apr 17, 2015 at 3:38 PM, Vishal Mahajan vishal423@gmail.com
wrote:

I doubt that's the cause as it should also affect sequential searches.

Regards,
Vishal

On Friday, April 17, 2015 at 6:34:24 PM UTC+5:30, Jörg Prante wrote:

Sorry I overlooked it, you use getTookInMillis()

Maybe the extra time is spent because you use a range filter which is
not cached?

Jörg

On Fri, Apr 17, 2015 at 3:02 PM, joerg...@gmail.com <joerg...@gmail.com

wrote:

What time do you measure? The ES query time, or the network latency?

Jörg

On Fri, Apr 17, 2015 at 2:25 PM, Vishal Mahajan vish...@gmail.com
wrote:

Hi,

I was trying Filtered query (default search type) to fetch first 8k
out of approx 170k matched records. I noticed that on an average query took
around 500ms (response.getTookInMillis()). But, when I tried 4 concurrent
searches over same dataset (in ideal scenario dataset will be different), I
noticed that the performance degraded and each query took more than 1sec on
average. Is this degradation in search response expected?
I still haven't tried with scroll and scan as order is not important,
but, curious to know if anything wrong with query or the way I executed.

I am executing search on single index having around 850k docs (each
doc contains around 5 fields), with 1g allocated to ES and using java node
client to execute searches. Following is the query JSON:

{
"from" : 0,
"size" : 8000,
"query" : {
"filtered" : {
"query" : {
"match_all" : { }
},
"filter" : {
"and" : {
"filters" : [ {
"term" : {
"details" : "Holiday"
}
}, {
"range" : {
"createdOn" : {
"from" : 0,
"to" : 1429260645351,
"include_lower" : true,
"include_upper" : true
}
}
}, {
"terms" : {
"priority" : [ 1, 2 ]
}
} ]
}
}
}
},

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