Attributes are unmaintained and unused.
They have become more of a liability than a benefit.
This change eliminates them from the codebase.
The only user-visible change (assuming that attrs are not used) is that the attrs field will no longer appear in row JSON.
This changes Count(Precall()) operations to execute the precall directly inside of the count operation, bypassing the transformation to a Precomputed() call.
Eliminating the Precomputed() step causes Count(Distinct()) to work properly on negative integers.
Back out support for sorting on fields (only count and aggregate
supported for now).
Fix bug where default return of "true" caused sort to be unstable. (If
they are equal, Less should return false)
Fix bug where limit was being applied before sorting.
Fix bug where offset was not actually allowed to be an argument to
GroupBy (weird! guess we weren't testing that very well)
Apply "having" after calculating Count(Distinct) aggregate so that
having can apply to that.
Switch to stable sort to make testing easier.
This replaces the former TopK BSI building algorithm, as the row cache was too expensive.
Additionally, BSI addition has been optimized with specialized adders inside of roaring.
Use "" strings for fixed string names. In startCall(), look up the
lowercase conversion of a call name in a table mapping all-lowercase
representations to canonical case, so we don't have to chase down
everyplace in the rest of the code base that assumes "Row" is
capitalized exactly like that.
PQL always produces decimals, which have effectively-arbitrary range,
but can convert them to floats when required; the executor then requests
this conversion in the handful of cases (SetRowAttrs and SetColumnAttrs)
where it wants floats rather than decimals.
Not yet fixed: The "Range" call may also be wrong now. It was specifying
an "fvalue" but is now effectively getting what used to be called a
"dvalue". However, so far as I can tell, that didn't work before either.
a) All tests green under -race for both PILOSA_TXSRC=roaring and PILOSA_TXSRC=badger.
b) Distinct is merged back into mainline pilosa.
Seebs notes on the Distinct work:
merge Distinct plugin back into main source tree, convert to Tx
We drop all references to the Preemptively Deprecated Don't You Dare
Use This extension interface, and move the one and only extension we had
(Distinct) into the main executor.
Also this fixes an arguable bug, which is that Container.AsBitmap()
would panic on a nil parameter, but it should have returned an empty
bitmap, because a nil *Ccontainer is a valid empty container. This
simplifies logic significantly in Distinct.
Fixes#569#570#571#572#573#584#585
- all tests green on RoaringTx
- RoaringTx on by default
- blueGreenTx testing framework available for A-vs-B comparison
of Tx implementations
- flag -tx added to server command line but not wired to
change NewIndex() selection yet.
- 918 green tests, 14 tests red on BadgerTx.
A full list of the 14 red tests on BadgerTx follows.
Note that these red tests represent not defects in BadgerDB
or BadgerTx but rather failures of the pre-existing pilosa infrastructure to yet
be fully adapted from files to using a transactional storage engine.
As such these are tests that RBF should not be expected to
pass yet either.
Fixing the pilosa infrastructure to allow these tests
to go green under Badger is the next and highest priority
order of business, but RBF can get much testing benefit
from the 918 green tests we do have, and hence we merge
as much as we have today.
The 14 red tests when NewIndex() is set to use
BadgerTx are as follows. Note in particular
that pilosa cluster resizing is not working yet under a
transactional store.
TestCluster_ResizeStates/Multiple_nodes,_with_data
TestImportClearRestart/0MaxOpN10000
TestImportClearRestart/1MaxOpN10000
TestImportClearRestart/2MaxOpN10000
TestImportClearRestart/3MaxOpN10000
TestExecutor_Execute_Existence/Row
TestExecutor_ForeignIndex
TestExecutor_Execute_CountDistinct/Distinct
TestExecutor_Execute_CountDistinct/Count(Distinct)
TestExecutor_Execute_CountDistinct/GroupBy(Distinct)
TestExecutor_BareDistinct
TestExecutor_Execute_TopNDistinct/TopN
TestHolderSyncer_IntField/BasicSync
TestHolderSyncer_IntField/MultiShard
This modifies the parser to properly "unquote" incoming strings. So if
a string comes in double or single quoted, we approximately follow Go
rules for removing the quotes and processing escape sequences.
The differences from Go are:
1. we only support backslash, quote, tab and newline escape
sequenences.
2. Single quoted strings are supported and work just like double
quoted strings.
3. The peg parser won't actually accept backquoted strings (I don't
think)
Fixes: #411
This commit introduces a new type: pql.Decimal
We use that instead of float64 in order to ensure
that the string representation is consistent.
One unfortunate discovery during implementation is
that the RowAttrs and ColAttrs support floats, and
the PEG file was treating them as such. So I had
to split the PEG definitions into float-specific
items and decimal-specific items.
After a few experiments with pkg/plugin, I'm ready to concede that the
people warning me it was unsuitable for production use were in fact
correct.
In the brave new world, the "ext" package is moved to its own module
outside pilosa. This means that importing it doesn't imply any need to
version-check against pilosa; we can just use versioned copies of the
ext package, which can be public because it doesn't contain anything
we need to care about keeping proprietary.
Then we can, conditional on build tags, import modules from a
neighboring repo which contains the actual implementations, and if
they're imported, their init functions register them.
This PR is meant to get all columns from an index
based on the TrackExistence row.
`All()` is a PQL function that can be used as a typical
row object. Optional arguments are `limit` and `offset`.
There is a TODO in the `StringWithSubj` method because the value
types really depend on the subject type (for example, `count` uses
uint64, while `sum` uses int64). I'm waiting to address this
until we decide how to handle sums of floats (Decimal), because
that will affect this logic as well.
This PR adds support for a `having` argument in a `GroupBy` query.
Usage looks like this:
```
GroupBy(Rows(a), having=Condition(count > 10))
GroupBy(Rows(a), aggregate=Sum(field=b), having=Condition(sum > 100))
```
had to workaround some cruft in the parser that was trying to only
support a BETWEEN query as LTE, LTE. Now we have operations for all
combinations of LT and LTE.
unrelated - changed the port a test was binding to as it conflicted
with a port I was using locally.
