During development, I, at some point, decided that the dimensions should
be expanded based on what was available rather than what was present in
the subquery. I don't really know the rationale for this because I
forgot, but it doesn't make sense or seem to be particularly useful.
Expanding dimensions now just uses the values specified in the subquery
rather than expanding to all available dimensions of the measurement in
the subquery.
With the new shard mapper implementation, regexes were just ignored so
it attempted to look up the field type inside of a measurement with no
name (which cannot possibly exist) so it would think the field didn't
exist and map it as the unknown type.
During development, I, at some point, decided that the dimensions should
be expanded based on what was available rather than what was present in
the subquery. I don't really know the rationale for this because I
forgot, but it doesn't make sense or seem to be particularly useful.
Expanding dimensions now just uses the values specified in the subquery
rather than expanding to all available dimensions of the measurement in
the subquery.
With the new shard mapper implementation, regexes were just ignored so
it attempted to look up the field type inside of a measurement with no
name (which cannot possibly exist) so it would think the field didn't
exist and map it as the unknown type.
Previously, only time expressions got propagated inwards. The reason for
this was simple. If the outer query was going to filter to a specific
time range, then it would be unnecessary for the inner query to output
points within that time frame. It started as an optimization, but became
a feature because there was no reason to have the user repeat the same
time clause for the inner query as the outer query. So we allowed an
aggregate query with an interval to pass validation in the subquery if
the outer query had a time range. But `GROUP BY` clauses were not
propagated because that same logic didn't apply to them. It's not an
optimization there. So while grouping by a tag in the outer query
without grouping by it in the inner query was useless, there wasn't any
particular reason to care.
Then a bug was found where wildcards would propagate the dimensions
correctly, but the outer query containing a group by with the inner
query omitting it wouldn't correctly filter out the outer group by. We
could fix that filtering, but on further review, I had been seeing
people make that same mistake a lot. People seem to just believe that
the grouping should be propagated inwards. Instead of trying to fight
what the user wanted and explicitly erase groupings that weren't
propagated manually, we might as well just propagate them for the user
to make their lives easier. There is no useful situation where you would
want to group into buckets that can't physically exist so we might as
well do _something_ useful.
This will also now propagate time intervals to inner queries since the
same applies there. But, while the interval propagates, the following
query will not pass validation since it is still not possible to use a
grouping interval with a raw query (even if the inner query is an
aggregate):
SELECT * FROM (SELECT mean(value) FROM cpu) WHERE time > now() - 5m GROUP BY time(1m)
This also means wildcards will behave a bit differently. They will
retrieve dimensions from the sources in the inner query rather than just
using the dimensions in the group by.
Fixing top() and bottom() to return the correct auxiliary fields.
Unfortunately, we were not copying the buffer with the auxiliary fields
so those values would be overwritten by a later point.
Previously, only time expressions got propagated inwards. The reason for
this was simple. If the outer query was going to filter to a specific
time range, then it would be unnecessary for the inner query to output
points within that time frame. It started as an optimization, but became
a feature because there was no reason to have the user repeat the same
time clause for the inner query as the outer query. So we allowed an
aggregate query with an interval to pass validation in the subquery if
the outer query had a time range. But `GROUP BY` clauses were not
propagated because that same logic didn't apply to them. It's not an
optimization there. So while grouping by a tag in the outer query
without grouping by it in the inner query was useless, there wasn't any
particular reason to care.
Then a bug was found where wildcards would propagate the dimensions
correctly, but the outer query containing a group by with the inner
query omitting it wouldn't correctly filter out the outer group by. We
could fix that filtering, but on further review, I had been seeing
people make that same mistake a lot. People seem to just believe that
the grouping should be propagated inwards. Instead of trying to fight
what the user wanted and explicitly erase groupings that weren't
propagated manually, we might as well just propagate them for the user
to make their lives easier. There is no useful situation where you would
want to group into buckets that can't physically exist so we might as
well do _something_ useful.
This will also now propagate time intervals to inner queries since the
same applies there. But, while the interval propagates, the following
query will not pass validation since it is still not possible to use a
grouping interval with a raw query (even if the inner query is an
aggregate):
SELECT * FROM (SELECT mean(value) FROM cpu) WHERE time > now() - 5m GROUP BY time(1m)
This also means wildcards will behave a bit differently. They will
retrieve dimensions from the sources in the inner query rather than just
using the dimensions in the group by.
Fixing top() and bottom() to return the correct auxiliary fields.
Unfortunately, we were not copying the buffer with the auxiliary fields
so those values would be overwritten by a later point.
Hello,
I have tried this example as it is for now. Encountered an error that AddPoint function expects only one argument. Checked you GoDoc and updated the example in your error handling style. It works like this.
Jason Wilder
Cory LaNou
Jonathan A. Sternberg
Edd Robinson
Paul Dix
Jason Wilder
Mehmet Cetin
Gunnar
Mark Rushakoff