Reputation: 9879
My Elasticsearch mapping looks like roughly like this:
{
"myIndex": {
"mappings": {
"myType": {
"_timestamp": {
"enabled": true,
"store": true
},
"properties": {
"LastUpdated": {
"type": "date",
"format": "dateOptionalTime"
}
/* lots of other properties */
}
}
}
}
}
So, _timestamp is enabled, and there's also a LastUpated property on every document. LastUpdated can have a different value than _timestamp: sometimes, documents get updated physically (e.g. updates to denormalized data) which updates _timestamp, but LastUpdated remains unchanged because the document hasn't actually been "updated" from a business perspective.
Also, there are many of documents without a LastUpdated value (mostly old data).
What I'd like to do is run an aggregation which counts the number of documents per calendar day (kindly ignore the fact that the dates need to be midnight-aligned, please). For every document, use LastUpdated if it's there, otherwise use _timestamp.
Here's what I've tried:
{
"aggregations": {
"counts": {
"terms": {
"script": "doc.LastUpdated == empty ? doc._timestamp : doc.LastUpdated"
}
}
}
}
The bucketization appears to work to some extent, but the keys in the result looks weird:
buckets: [
{
key: org.elasticsearch.index.fielddata.ScriptDocValues$Longs@7ba1f463doc_count: 300544
}{
key: org.elasticsearch.index.fielddata.ScriptDocValues$Longs@5a298acbdoc_count: 257222
}{
key: org.elasticsearch.index.fielddata.ScriptDocValues$Longs@6e451b5edoc_count: 101117
},
...
]
What's the proper way to run this aggregation and get meaningful keys (i.e. timestamps) in the result?
Upvotes: 0
Views: 76
Reputation: 4489
I've tested and made a groovy script for you,
POST index/type/_search
{
"aggs": {
"counts": {
"terms": {
"script": "ts=doc['_timestamp'].getValue();v=doc['LastUpdated'].getValue();rv=v?:ts;rv",
"lang": "groovy"
}
}
}
}
This returns the required result.
Hope this helps!! Thanks!!
Upvotes: 1