Data Preparation: Section 15 Data
(1) sum (sum), aggs fixed wording, price_of_sum name is taken.
GET /lib7/items/_search { "size":0, "aggs":{ "price_of_sum":{ "sum":{ "field":"price" } } } }
Output:
{ "took": 9, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 5, "max_score": 0, "hits": [] }, "aggregations": { "price_of_sum": { "value": 145 } } }
(2) for the minimum (min)
GET /lib7/items/_search { "size":0, "aggs":{ "price_of_min":{ "min":{ "field":"price" } } } }
Output:
{ "took": 51, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 5, "max_score": 0, "hits": [] }, "aggregations": { "price_of_min": { "value": 25 } } }
(3) selecting the maximum value (max)
GET /lib7/items/_search { "size":0, "aggs":{ "price_of_max":{ "max":{ "field":"price" } } } }
Output:
{ "took": 14, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 5, "max_score": 0, "hits": [] }, "aggregations": { "price_of_max": { "value": 50 } } }
(4) averaging (avg)
GET /lib7/items/_search { "size":0, "aggs":{ "price_of_avg":{ "avg":{ "field":"price" } } } }
Output:
{ "took": 14, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 5, "max_score": 0, "hits": [] }, "aggregations": { "price_of_avg": { "value": 36.25 } } }
The number (5) Find the cardinality (cardinality), mutually different
GET /lib7/items/_search { "size":0, "aggs":{ "price_of_cardi":{ "cardinality":{ "field":"price" } } } }
Execution results are as follows:
{ "took": 38, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 5, "max_score": 0, "hits": [] }, "aggregations": { "price_of_cardi": { "value": 4 } } }
(6) a packet (Terms)
GET /lib7/items/_search { "size":0, "aggs":{ "price_group_by":{ "terms":{ "field":"price" } } } }
Output:
{ "took": 45, "timed_out": false, "_shards": { "total": 5, "successful": 5, "skipped": 0, "failed": 0 }, "hits": { "total": 5, "max_score": 0, "hits": [] }, "aggregations": { "price_group_by": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 25, "doc_count": 1 }, { "key": 30, "doc_count": 1 }, { "key": 40, "doc_count": 1 }, { "key": 50, "doc_count": 1 } ] } } }
(7) For those interested users by age group singing, and the average age of each group in reverse order, from the data section 12
GET /lib3/user/_search { "size":0, "query":{ "match":{ "interests":"changge" } }, "aggs":{ "age_of_group":{ "terms":{ "field":"age", "order":{ "age_of_avg":"desc" } }, "aggs":{ "age_of_avg":{ "avg":{ "field":"age" } } } } } }
Output:
{ "took": 19, "timed_out": false, "_shards": { "total": 3, "successful": 3, "skipped": 0, "failed": 0 }, "hits": { "total": 3, "max_score": 0, "hits": [] }, "aggregations": { "age_of_group": { "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 29, "doc_count": 1, "age_of_avg": { "value": 29 } }, { "key": 23, "doc_count": 1, "age_of_avg": { "value": 23 } }, { "key": 20, "doc_count": 1, "age_of_avg": { "value": 20 } } ] } } }