This refactors the validation code so it is more flexible and performs a
small bit of work to make preparing and executing the query easier.
The general idea is that compilation will eventually do more heavy
lifting in creating the initial plan and prepare will construct an
actual plan rather than just doing some basic field rewriting.
This change at least sets us up for that change in the future and moves
the validation code to the query execution instead of in the parser.
This also frees up the parser to parse the complete AST without worrying
if the query itself is valid. That could be useful for client code that
wants to compile a partial query to an AST and then perform
modifications on the AST for some reason.
The statement rewriting logic should be in the query engine as part of
preparing a query. This creates a shard mapper interface that the query
engine expects and then passes it to the query engine instead of
requiring the query to be preprocessed before being input into the query
engine. This interface is (mostly) the same as the old interface, just
moved to a different package.
The ConditionExpr function is more accurate because it parses the
condition and ensures that time conditions are actually used correctly.
That means that attempting to combine conditions with OR will not result
in the query silently pretending it's an AND and nested conditions work
correctly so there is only one way to read the query.
It also extracts the non-time conditions into a separate condition so we
can stop attempting to parse around the time conditions in lower layers
of the storage engine. This change does not remove those hacks, but a
following commit should be able to sanitize the condition and remove
them.
This change provides a clear separation between the query engine
mechanics and the query language so that the language can be parsed and
dealt with separate from the query engine itself.
Previously pseudo iterators could be created for meta data such
as series, measurement, and tag data. These iterators were created
at a higher level and lacked a lot of the power of the query engine.
This commit moves system iterators down to the series level and
supports the following:
- _name
- _seriesKey
- _tagKey
- _tagValue
- _fieldKey
These can be used as normal fields such as:
SELECT _seriesKey FROM cpu
This will return all the series keys for `cpu`.
When a time zone shift happened at the edge of a time bucket, the logic
was incorrect. When we added an hour to the day with a time grouping of
2 hours, we took the hour away from the previous bucket instead of the
next bucket so the first bucket of the day would be from midnight to 1
AM and the second bucket would include 1 AM to 4 AM (2 AM to 3 AM does
not exist when shifting forwards). The correct buckets should have been
12 AM to 2 AM for the first bucket of the day and 3 AM to 4 AM for the
second (since 2 AM to 3 AM does not exist).
This also modifies the tests to use table tests and sub tests.
* introduced UnsignedValue type
* leveraged existing int64 compression algorithms (RLE, Simple 8B)
* tsm and WAL can read and write UnsignedValue
* compaction is aware of UnsignedValue
* unsigned support to model, cursors and write points
NOTE: there is no support to create unsigned points, as the line
protocol has not been modified.
The language is now defined in a way similar to many HTTP routers with
the left prefix being placed into a parse tree and then eventually
invoking a function to parse the arguments.
This allows dynamically adding additional components to the parse tree
for either query language extensions or enterprise.
This commit adds a new environment variable INFLUXDB_PANIC_CRASH, which
when set to a truthy value, e.g., true, TRUE, 1, will prevent the server
from recovering from a panic.
Recover currently occurs in two places: the HTTP handler and the
QueryExecutor. INFLUXDB_PANIC_CRASH will control both.
Further, this commit adds _internal stats that will monitor the
occurrence of panics all the time (regardless of if INFLUXDB_PANIC_CRASH
has been set to true or not).
The recovered panic frequency can be inspected with the following
queries:
SELECT "recoveredPanics" FROM "_internal"."monitor"."httpd";
SELECT "recoveredPanics" FROM "_internal"."monitor"."queryExecutor";
It didn't properly pass the variable reference when creating the
variable iterator so a null iterator got passed back instead.
Duplicate the `top()` tests in TopInt to also test `bottom()` with the
same queries so `bottom()` stops getting neglected so often.
When a `SELECT ... INTO ...` is used with `top()` or `bottom()` used
with tags, the points will be written with the tags still intact instead
of converted to fields.
The previous version of `top()` and `bottom()` would gather all of the
points to use in a slice, filter them (if necessary), then use a
slightly modified heap sort to retrieve the top or bottom values.
This performed horrendously from the standpoint of memory. Since it
consumed so much memory and spent so much time in allocations (along
with sorting a potentially very large slice), this affected speed too.
These calls have now been modified so they keep the top or bottom points
in a min or max heap. For `top()`, a new point will read the minimum
value from the heap. If the new point is greater than the minimum point,
it will replace the minimum point and fix the heap with the new value.
If the new point is smaller, it discards that point. For `bottom()`, the
process is the opposite.
It will then sort the final result to ensure the correct ordering of the
selected points.
When `top()` or `bottom()` contain a tag to select, they have now been
modified so this query:
SELECT top(value, host, 2) FROM cpu
Essentially becomes this query:
SELECT top(value, 2), host FROM (
SELECT max(value) FROM cpu GROUP BY host
)
This should drastically increase the performance of all `top()` and
`bottom()` queries.
This change refactors the subquery code into a separate builder class to
help allow for more reuse and make the functions smaller and easier to
read.
The previous function that handled most of the code was too big and
impossible to reason through.
This also goes and replaces the complicated logic of aggregates that had
a subquery source with the simpler IteratorMapper. I think the overhead
from the IteratorMapper will be more, but I also believe that the actual
code is simpler and more robust to produce more accurate answers. It
might be a future project to optimize that section of code, but I don't
have any actual numbers for the efficiency of one method and I believe
accuracy and code clarity may be more important at the moment since I am
otherwise incapable of reading my own code.
When LIMIT and OFFSET were used with any functions that were not handled
directly by the query engine (anything other than count, max, min, mean,
first, or last), the input to the function would be limited instead of
receiving the full stream of values it was supposed to receive.
This also fixes a bug that caused the server to hang when LIMIT and
OFFSET were used with a selector. When using a selector, the limit and
offset should be handled before the points go to the auxiliary iterator
to be split into different iterators. Limiting happened afterwards which
caused the auxiliary iterator to hang forever.
`top()` and `bottom()` will now organize the points by time and also
keep the points original time even when a time grouping is used. At the
same time, `top()` and `bottom()` will no longer honor any fill options
that are present since they don't really make sense for these specific
functions.
This also fixes the aggregate and selectors to honor the ordered
iterator option so iterator remain ordered and to also respect the
buckets that are created by the final dimensions of the query so that
two buckets don't overlap each other within the same reducer. A test has
been added for this situation. This should clarify and encourage the use
of the ordered attribute within the query engine.
The Window function will now check before it adjusts the offset whether
it is going to overflow or underflow. If it is going to do either, it
sets the start or end time to MinTime or MaxTime.
Jonathan A. Sternberg
Ben Johnson
Stuart Carnie
Jason Wilder
Jason Wilder
Edd Robinson
Ryan Betts
Joe LeGasse
rw-influxdata
Cory LaNou
Tom Young
zhexuany