I just want to up this post.
I have the same problem. My docs have a nested structure and the nested
part can have more then 5K records. When i do a search on the elasticsearch
the response time is very slow when i have this large docs with nested
Another interesting thing: when i do a sort operation on this kind of
document the response time is very slow too.
Anyone have an ideia on what is the best practices to use nested types in
In the moment we have a cluster with 4 machines and each machine has 4GB of
RAM. Our cluster start to slow down when search on the complex documents
On Thursday, July 25, 2013 5:02:27 AM UTC-3, george wrote:
We inserted a document of size 10MB (Original document is around 45MB).
Indexing took around 13 secs Searching took around 800ms. We have some
mvel scripts running on the ES server as well.
I am attaching a sample doc that we insert in our ES node and the
corresponding query. This doc is small for the sake of clarity. In our big
docs the # of points will increase to almost 160K. Please let me know if
there are any issues in our query.
Can we use multisearch so that we get a parent AND only the child docs of
that parent matching a filter criteria. I thought multisearch queries have
to be independent of each other. We have the first query that matches the
parent which has atleast a child matching a criteria. Another query to
fetch the matched child document which has the parent from the previous
query. How can these be combined. Its a join based on parent id; Is it
possible in multisearch?
On Wed, Jul 24, 2013 at 5:32 PM, Igor Motov-3 [via ElasticSearch Users] <[hidden
email] http://user/SendEmail.jtp?type=node&node=4038631&i=0> wrote:
I need to know more about the structure of your documents, how often
different parts of you document change and what queries you run on your
documents in order to recommend one or another. But your understanding of
parent/child issue is correct, you will have to execute 2 queries in order
to get both parents and children, but you can combine them into single
On Wednesday, July 24, 2013 2:05:51 AM UTC-4, george wrote:
Thanks for your reply. Sorry for not being clear. I am facing issue
indexing the data. We have 6GB ES_HEAP_SIZE. I am using the Java client.
got Out of memory exception and another time I tried I got
Will try few more options and will update you if I am able to insert the
In our example, we have a type called "nested" and around 160K nested
documnets. In case of such big documents, do you suggest us using
parent/child relationship? Reading the docs, it seems like we can
data either from parent or from the child , but not from both using
has_child/has_parent filter. This means that if we need data from both
parent and child doc, do we have to issue 2 queries - 1 query to fetch
parent documents that has child documents matching a particular filter.
fire another query to fetch the matching child document which has the
parent. Is there any way to have a single query?
View this message in context: http://elasticsearch-users.
Sent from the ElasticSearch Users mailing list archive at Nabble.com.
You received this message because you are subscribed to the Google Groups
To unsubscribe from this group and stop receiving emails from it, send an
email to [hidden email]
For more options, visit https://groups.google.com/groups/opt_out.
If you reply to this email, your message will be added to the
To unsubscribe from Indexing very large document in ES, click here.
Sheeba Ann George
query.txt (12K) Download Attachment
IBI_small.txt.zip (101K) Download Attachment
View this message in context: Re: Indexing very large document in ES
Sent from the ElasticSearch Users mailing list archive
http://elasticsearch-users.115913.n3.nabble.com/ at Nabble.com.
You received this message because you are subscribed to the Google Groups "elasticsearch" group.
To unsubscribe from this group and stop receiving emails from it, send an email to firstname.lastname@example.org.
To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/570ebf49-bdf2-4a58-b045-36060b9e3fe8%40googlegroups.com.
For more options, visit https://groups.google.com/d/optout.