Re: elastisticsearch_dsl python to create pivot tables

2015-03-31 Thread Mike
tested it. works as expected. Thanks again for your help Am Dienstag, 31. März 2015 00:04:39 UTC+2 schrieb Mike: Thanks Honza. You made my day (my night rather, it is midnight here in Brussels). I quickly tested the code and it gives the same results as the manually chained

Re: elastisticsearch_dsl python to create pivot tables

2015-03-30 Thread Mike
Thanks Honza. (also for the great work you are doing for the python community). I may have mistated my problem. what I am really looking for is to have a bucket, inside a bucket , inside a bucket and then metrics the following expression does this s1.aggs.bucket('xColor',

Re: elastisticsearch_dsl python to create pivot tables

2015-03-30 Thread Mike
Thanks Honza. You made my day (my night rather, it is midnight here in Brussels). I quickly tested the code and it gives the same results as the manually chained expression. I will test with various metrics tomorrow, I will then mark the question as “completed”. Thanks a lot and have a

elastisticsearch_dsl python to create pivot tables

2015-03-30 Thread Mike
the python elasticsearch , elasticsearch dsl packages are life-saver and got me converted to ES. Now I am trying to use elasticsearch dsl package to create pivot tables in ES but am having hard time figuring out how to chain the buckets programmatically. while chaining the buckets / metrics

Re: elastisticsearch_dsl python to create pivot tables

2015-03-30 Thread Honza Král
that's what happens when I try to be quick and don't verify my code - there is an error in my example: b = s.aggs for bucket in xVarBuckets: # this needs to be b = b.bucket instead of what I had previously b = b.bucket(bucket['label'], 'terms', field=bucket['field']) for metric in

Re: elastisticsearch_dsl python to create pivot tables

2015-03-30 Thread Honza Král
Hello, you can access buckets already created using ['name'] syntax, in your case you can do (instead of the chaining): s.aggs['xColor']['xMake']['xCity'].metric(...) s.aggs['xColor']['xMake']['xCity'].metric(...) This way you can add aggregations to already created buckets. Also you can just