Hiya
It's a bit more verbose, but yes you can do queries like that easily. I've
assumed that all of your fields are "exact value" not_analyzed string
fields, rather than full text fields:
GET /_search
{
"_source": [ "col1", "col2" ],
"query": {
"filtered": {
"filter": {
"bool": {
"must": [
{
"bool": {
"should": [
{ "terms": { "col3": [ "some", "value" ]}},
{ "missing": { "field": "col3" }}
]
}
},
{
"bool": {
"should": [
{ "terms": { "col4": [ "another", "set", "values" ]}},
{ "missing": { "field": "col4" }}
]
}
},
{ "term": { "col5": "hello" }}
],
"must_not": [
{ "term": { "col6": "world" }}
]
}
}
}
},
"sort": "col7"
}
All of those lookups use filters, so would be cached, making all future
executions very fast indeed.
On 18 April 2014 08:37, Paul <paulj3...@gmail.com> wrote:
> Hi,
>
> We're looking to move our infrastructure to ElasticSearch and I have some
> concerns. We plan on using this more as a database and less than a search
> engine. I know there are some companies out there that are doing this, but
> I have some queries that, with one SQL command I can get the results I
> need, whereas ElasticSearch I would need to do filters of queries, etc.
>
>
> An example, using SQL parlance, how would I do the following statement:
>
> select col1, col2 from mytable where col3 in ["", "some", "value] and col4
> in ["another", "set", "", "values"] and col5 = "hello" and col6 not in
> "world" order by col7.
>
> This is an example of some data I would be querying, and I would be
> performing 1000's of queries at a time.
>
>
>
> So my question: Can ElasticSearch do this and if so, how can I do the
> above query.
>
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