[
https://issues.apache.org/jira/browse/SOLR-14614?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Aroop updated SOLR-14614:
-------------------------
Description:
For the Data Analytics use cases the standard use case is:
# Find a pattern
# Then Aggregate by certain dimensions
# Then compute metrics (like count, sum, avg)
# Sort by a dimension or metric
# look at top-n
This functionality has been available over many different interfaces in the
past on solr, but only streaming expressions have the ability to deliver
results in a scalable, performant and stable manner for systems that have large
data to the tune of Big data systems.
However, one barrier to entry is the query interface, not being simple enough
in streaming expressions.
to give an example of how involved the corresponding streaming expression can
get, to get it to work on large scale systems,
{code:java}
qt=/stream&aggregationMode=facet&expr=
select( top( rollup(sort(by%3D"city+asc",
+plist(
select(facet(collection1,+q%3D"(*:*+AND+name:alex)",+buckets%3D"city",+bucketSizeLimit%3D"2010",+bucketSorts%3D"count(*)+desc",+count(*)),+city,+count(*)+as+Nj3bXa),
select(facet(collection2,+q%3D"(*:*+AND+name:alex)",+buckets%3D"city",+bucketSizeLimit%3D"2010",+bucketSorts%3D"count(*)+desc",+count(*)),+city,+count(*)+as+Nj3bXa)
)),
+over%3D"city",+sum(Nj3bXa)),
+n%3D"10",+sort%3D"sum(Nj3bXa)+desc"),
+city,+sum(Nj3bXa)+as+Nj3bXa)
{code}
This is a query on an alias with 2 collections behind it representing 2 data
partitions, which is a requirement of sorts in big data systems. This is one of
the only ways to get information from Billions of records in a matter of
seconds. But one can see how involved this syntax can be in the current scheme
and is a barrier to entry for new adopters.
This Jira is to track the work of creating a simplified analytics endpoint
augmenting streaming expressions.
a starting proposal is to have the endpoint have these query parameters:
{code:java}
/analytics?action=aggregate&q=*:*&fq=name:alex&dimensions=city&metrics=count&sort=count&sortOrder=desc&limit=10{code}
This is equivalent to a sql that an analyst would write:
{code:java}
select city, count(*) from collection where name = 'alex'
group by city order by count(*) desc limit 10;{code}
On the solr side this would get translated to the best possible streaming
expression using *rollups, top, sort, plist* etc.; but all done transparently
to the user.
Heres to making the power of Streaming expressions simpler to use for all.
was:
For the Data Analytics use cases the standard use case is:
# Find a pattern
# Then Aggregate by certain dimensions
# Then compute metrics (like count, sum, avg)
# Sort by a dimension or metric
# look at top-n
This functionality has been available over many different interfaces in the
past on solr, but only streaming expressions have the ability to deliver
results in a scalable, performant and stable manner for systems that have large
data to the tune of Big data systems.
However, one barrier to entry is the query interface, not being simple enough
in streaming expressions.
This Jira is to track the work of creating a simplified analytics endpoint
augmenting streaming expressions.
a starting proposal is to have the endpoint have these query parameters:
{code:java}
/analytics?action=aggregate&q=*:*&fq=name:alex*&dimensions=age,city&metrics=count&sort=count&sortOrder=desc&limit=10{code}
This is equivalent to a sql that an analyst would write:
{code:java}
select age, city, count(*) from collection where name like 'alex%'
group by age, city order by age desc limit 10;{code}
On the solr side this would get translated to the best possible streaming
expression using *rollups, top, sort, plist* etc.; but all done transparently
to the user.
> Add Simplified Aggregation Interface to Streaming Expression
> ------------------------------------------------------------
>
> Key: SOLR-14614
> URL: https://issues.apache.org/jira/browse/SOLR-14614
> Project: Solr
> Issue Type: Improvement
> Security Level: Public(Default Security Level. Issues are Public)
> Components: query, query parsers, streaming expressions
> Affects Versions: 7.7.2, 8.4.1
> Reporter: Aroop
> Priority: Major
>
> For the Data Analytics use cases the standard use case is:
> # Find a pattern
> # Then Aggregate by certain dimensions
> # Then compute metrics (like count, sum, avg)
> # Sort by a dimension or metric
> # look at top-n
> This functionality has been available over many different interfaces in the
> past on solr, but only streaming expressions have the ability to deliver
> results in a scalable, performant and stable manner for systems that have
> large data to the tune of Big data systems.
> However, one barrier to entry is the query interface, not being simple enough
> in streaming expressions.
> to give an example of how involved the corresponding streaming expression can
> get, to get it to work on large scale systems,
> {code:java}
> qt=/stream&aggregationMode=facet&expr=
> select( top( rollup(sort(by%3D"city+asc",
> +plist(
>
> select(facet(collection1,+q%3D"(*:*+AND+name:alex)",+buckets%3D"city",+bucketSizeLimit%3D"2010",+bucketSorts%3D"count(*)+desc",+count(*)),+city,+count(*)+as+Nj3bXa),
>
> select(facet(collection2,+q%3D"(*:*+AND+name:alex)",+buckets%3D"city",+bucketSizeLimit%3D"2010",+bucketSorts%3D"count(*)+desc",+count(*)),+city,+count(*)+as+Nj3bXa)
> )),
> +over%3D"city",+sum(Nj3bXa)),
> +n%3D"10",+sort%3D"sum(Nj3bXa)+desc"),
> +city,+sum(Nj3bXa)+as+Nj3bXa)
> {code}
> This is a query on an alias with 2 collections behind it representing 2 data
> partitions, which is a requirement of sorts in big data systems. This is one
> of the only ways to get information from Billions of records in a matter of
> seconds. But one can see how involved this syntax can be in the current
> scheme and is a barrier to entry for new adopters.
>
> This Jira is to track the work of creating a simplified analytics endpoint
> augmenting streaming expressions.
> a starting proposal is to have the endpoint have these query parameters:
> {code:java}
> /analytics?action=aggregate&q=*:*&fq=name:alex&dimensions=city&metrics=count&sort=count&sortOrder=desc&limit=10{code}
> This is equivalent to a sql that an analyst would write:
> {code:java}
> select city, count(*) from collection where name = 'alex'
> group by city order by count(*) desc limit 10;{code}
> On the solr side this would get translated to the best possible streaming
> expression using *rollups, top, sort, plist* etc.; but all done transparently
> to the user.
>
> Heres to making the power of Streaming expressions simpler to use for all.
>
>
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