Elastic : make a light count query (vs search query) - r

Question

I am accessing bulk data in elastic through R. For analytics purpose I need to query for data for a relatively long duration (say a month). The data for a month is approx 4.5 million rows and R goes out of memory.
Sample data is below (for 1 day):
dt <- as.Date("2015-09-01", "%Y-%m-%d")
frmdt <- strftime(dt,"%Y-%m-%d")
todt <- as.Date(dt+1)
todt <- strftime(todt,"%Y-%m-%d")
connect(es_base="http://xx.yy.zzz.kk")
start_date <- as.integer(as.POSIXct(frmdt))*1000
end_date <- as.integer(as.POSIXct(todt))*1000
query <- sprintf('{"query":{"range":{"time":{"gte":"%s","lte":"%s"}}}}',start_date,end_date)
s_list <- elastic::Search(index = "organised_2015_09",type = "PROPERTY_SEARCH", body=query ,
fields = c("trackId", "time"), size=1000000)$hits$hits
length(s_list)
[1] 144612
This result for 1 day has 144k records and is 222 MB. Sample list item below:
> s_list[[1]]
$`_index`
[1] "organised_2015_09"
$`_type`
[1] "PROPERTY_SEARCH"
$`_id`
[1] "1441122918941"
$`_version`
[1] 1
$`_score`
[1] 1
$fields
$fields$time
$fields$time[[1]]
[1] 1441122918941
$fields$trackId
$fields$trackId[[1]]
[1] "fd4b4ce88101e58623ba9e6e31971d1f"
Actually a summary count of number of items by "trackId" and "time" (summarize for every day) would suffice for analytics purpose. Hence I tried to transform this into a count query with aggregations. So I constructed the below query:
query < -'{"size" : 0,
"query": {
"filtered": {
"query": {
"match_all": {}
},
"filter": {
"range": {
"time": {
"gte": 1441045800000,
"lte": 1443551400000
}
}
}
}
},
"aggs": {
"articles_over_time": {
"date_histogram": {
"field": "time",
"interval": "day",
"time_zone": "+05:30"
},
"aggs": {
"group_by_state": {
"terms": {
"field": "trackId",
"size": 0
}
}
}
}
}
}'
response <- elastic::Search(index="organised_recent",type="PROPERTY_SEARCH",body=query, search_type="count")
However I did not gain in speed or document size. i think I am missing something but not sure what.