Elastic search Multiple Aggregation

Question

I have two elastic search queries

1. For Get transaction information for a particular day
2. For get transaction information for all days

How can i combine these two quires into a single query? Am struggling to write a signle query for these two similar needs. Please help me to solve this issue. Thank you

{
  "query": {
    "filtered": {
      "query": {
        "match": {
          "payment_type": "paypal"
        }
      },
      "filter": {
        "range": {
          "transaction_date": {
            "from": "2014-11-10",
            "to": "2014-11-10"
          }
        }
      }
    }
  },
  "aggs": {
    "daily_price_sum": {
      "sum": {
        "field": "price"
      }
    },
    "daily_post_sum": {
      "sum": {
        "field": "purchased_post_count"
      }
    }
  }
}


{
  "size": 0, 
  "query": {
    "match": {
      "payment_type": "paypal"
    }
  },
  "aggs": {
    "daily_price_sum": {
      "sum": {
        "field": "price"
      }
    },
    "daily_post_sum": {
      "sum": {
        "field": "purchased_post_count"
      }
    }
  }
}

Answer 1

If you are using ES of version less than 1.4.0, you can make use of Filter Aggregations. Query for the same is as below:

{
   "size": 0,
   "query": {
      "match": {
         "payment_type": "paypal"
      }
   },
   "aggs": {
      "daily_price_sum": {
         "sum": {
            "field": "price"
         }
      },
      "daily_post_sum": {
         "sum": {
            "field": "purchased_post_count"
         }
      },
      "one_day_aggs": {
         "filter": {
            "range": {
               "transaction_date": {
                  "from": "2014-11-10",
                  "to": "2014-11-10"
               }
            }
         },
         "aggs": {
            "daily_price_sum": {
               "sum": {
                  "field": "price"
               }
            },
            "daily_post_sum": {
               "sum": {
                  "field": "purchased_post_count"
               }
            }
         }
      }
   }
}

But if you are using ES 1.4.0, then you can use Filters Aggregation to make the query more compact. Query for the same is as below:

{
   "size": 0,
   "query": {
      "match": {
         "payment_type": "paypal"
      }
   },
   "aggs": {
      "transactions": {
         "filters": {
            "filters": {
               "one_day": {
                  "range": {
                     "transaction_date": {
                        "from": "2014-11-10",
                        "to": "2014-11-10"
                     }
                  }
               },
               "all_days": {
                  "match_all": {}
               }
            }
         },
         "aggs": {
            "daily_price_sum": {
               "sum": {
                  "field": "price"
               }
            },
            "daily_post_sum": {
               "avg": {
                  "field": "purchased_post_count"
               }
            }
         }
      }
   }
}

I also see that you are not interested in the query hits but only on the aggregation values. In that case, you can improve the performance of these aggregations by making use of Shard Query Cache which is present in ES 1.4.0. For making use of this, enable shard query cache as mentioned in the link and add the following parameter to the _search operation: search_type=count.