Hey all,
We have been testing the new 1.3.1 release on our current load and
queries, and have found that under same conditions, same queries, the es
cluster we have just starts to max out cpu and the thread pools fill up and
the query times just keep going up until eventually we have the restart
nodes just to clear things.
on our older (.20.6) version, we do have big queries. Think 100+ terms, but
they were all wrapped in a filter and cached. We almost never did any
scoring, and if we did, it was only on a few terms.
so, a query may look like the following:
"query": {
"filtered": {
"query": {
"constant_score": {
"query": {
"bool": {
"must": [
{
"bool": {
"should": {
"bool": {
"should": [
{
"term": {
"content": "smyrna"
}
},
{
"term": {
"title": "smyrna"
}
}
]
}
}
}
}
]
}
},
"boost": 1
}
},
"filter": {
"bool": {
"must": [
{
"bool": {
"must": [
{
"bool": {
"must": {
"bool": {
"should": [
{
"bool": {
"must": [
{
"terms": {<fill in long lists of ids
here}
and this filter is broken up into multiple sections, each filter is
given a cache name and cache key
so, what could have changed between .20.6 and 1.3.1 that would cause this
sort of non-scored filter query to suddenly spend so much cpu time running?
i did a thread dump and it is setting multiple threads in the .scorer state
of the filteredquery.
not sure if that matters.
any help in trying to figure out where the es is spending its time on all
of this would be helpful. we at least have marvel up and running now and
that tells us that cpu gets pegged and the avg query times, but not sure
how to start debugging the query side to see could be changed under the
hoods to cause such a drastic change.
Thanks,
Scott
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