ElasticSearch equivalent query for SQL group by multiple columns - elasticsearch

Question

I have a few million documents with name and version (both of type keyword) as properties in each. What is the equivalent Elastic query for group by name, version?
I have tried the following query:
{
"size":0,
"query": {
"bool": {
"filter": {
"range": {
"time": {
"gte": "2017-01-28",
"lte": "2017-02-28"
}
}
}
}
},
"aggs": {
"group_by_name": {
"terms": {
"field": "name"
},
"aggs": {
"group_by_version": {
"terms": {
"field": "version"
}
}
}
}
}
}
However the results are not same as doing Group by name, version.
The results are grouped by name and within each group, they are grouped by version.
How do I modify the above query to group by name, version tuple and return results in descending order?
Your help is greatly appreciated.
Update:
What i get is:
{
"took": 1424,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"hits": {
"total": 115,
"max_score": 0,
"hits": []
},
"aggregations": {
"group_by_name": {
"doc_count_error_upper_bound": 2,
"sum_other_doc_count": 115,
"buckets": [
{
"key": "product1",
"doc_count": 50,
"group_by_version": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 50,
"buckets": [
{
"key": "1.0",
"doc_count": 40
},
{
"key": "2.0",
"doc_count": 10
},
]
}
},
{
"key": "product3",
"doc_count": 35,
"group_by_version": {
"doc_count_error_upper_bound": 4,
"sum_other_doc_count": 35,
"buckets": [
{
"key": "8.0",
"doc_count": 20
},
{
"key": "9.0",
"doc_count": 15
}
]
}
},
{
"key": "product2",
"doc_count": 30,
"group_by_version": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 30,
"buckets": [
{
"key": "4.0",
"doc_count": 25
},
{
"key": "5.0",
"doc_count": 5
}
]
}
}
]
}
}
}
What i want is:
name, version count
product1 1.0 40
product2 4.0 25
product3 8.0 20
product3 9.0 15
product1 2.0 10
product2 5.0 5