aggregation

I need to do get some data grouped by day of week and hour, for example curl -XGET http://localhost:9200/testing/hello/_search?pretty=true -d ' { "size": 0, "aggs": { "articles_over_time" : { "date_histogram" : { "field" : "date", "interval" : "hour", "format": "E - k" } } } } ' Gives me this: { "took" : 2, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "failed" : 0 }, "hits" : { "total" : 2857, "max_score" : 0.0, "hits" : [ ] }, "aggregations" : { "articles_over_time" : { "buckets" : [ { "key_as_string" : "Fri - 17", "key" : 1391792400000, "doc_count" : 6 }, ... { "key_as

I must apply a certain transformation fn(argument) . Here argument is equal to value , but not when it is negative. When you get a first negative value , then you "wait" until it sums up with consecutive values and this sum becomes positive. Then you do fn(argument) . See the table I want to get: value argument --------------------- 2 2 3 3 -10 0 4 0 3 0 10 7 1 1 I could have summed all values and apply fn to the sum, but fn can be different for different rows and it is essential to know the row number to choose a concrete fn. As want a Postgres SQL solution, looks like window functions fit,

Lets say we have 3 layers project. DB, Business, Web and aggregating pom. Project |-DB | |-pom.xml |-Business | |-pom.xml |-pom.xml All modules are ment to be released and branched together, so Aggregator pom is configured to assign the same version to all submodules. We have the following versions: DB-0.1-SNAPSHOT Business-0.1-SNAPSHOT which depends on DB-0.1-SNAPSHOT Web-0.1-SNAPSHOT which depends on Business-0.1-SNAPSHOT When doing release:prepare , all versions updated to 0.1, but prepare fails because there is no DB-0.1 in dependency yet. One solution is to create different projects for

I have a data-set which contains observations for several weeks with 2 minutes frequency. I want to increase the time interval from 2 minute to 5 minute. The problem is that, frequency of the observations are not always the same. I mean, theoretically, every 10 minute there should be 5 observation but usually it is not the case. Please let me know how I can aggregate the observations based on average function and with respect to the time and date of the observations. In other words aggregation based on every 5 minutes while number of observations are not the same for each 5 minute time

I am really new to elasticsearch world. Let's say I have a nested aggregation on two fields : field1 and field2 : { ... aggs: { field1: { terms: { field: 'field1' }, aggs: { field2: { terms: { field: 'field2' } } } } } } This piece of code works perfectly and gives me something like this : aggregations: { field1: { buckets: [{ key: "foo", doc_count: 123456, field2: { buckets: [{ key: "bar", doc_count: 34323 },{ key: "baz", doc_count: 10 },{ key: "foobar", doc_count: 36785 }, ... ] },{ key: "fooOO", doc_count: 423424, field2: { buckets: [{ key: "bar", doc_count: 35 },{ key: "baz", doc_count:

I have a table like this in PostgreSQL. I want to perform aggregation functions like mean and max for every 16 records based on ID (which is primary key). For example I have to calculate mean value for first 16 records and second 16 records and so on. +-----+------------- | ID | rainfall | +-----+----------- | | 1 | 110.2 | | 2 | 56.6 | | 3 | 65.6 | | 4 | 75.9 | +-----+------------ The 1st approach that comes to mind is to use row_number() to annotate the table, then group by blocks of 16 rows. SELECT min(id) as first_id, max(id) AS last_id, avg(rainfall) AS avg_this_16 FROM ( SELECT id,