We've got a fairly consistent thing of the API splitting data up
into shards before sending it to a field, which it has to do because
of clustering, so we don't intend to support the case where you
have data from another shard in a data set.
Also drop the identical but mislabeled test from TestIntField's
corresponding case.
There's only ever one view in importValue, but there's also only ever
one shard, because importValue is only called by things called from
the API after it has split everything up by shard.
Since we don't always have "snapshots" anymore, the arguable benefit of
avoiding the snapshot is reduced, and the primary expense of
importPositions has been dramatically reduced as well, so let's
just use that all the time, and simplify life.
We also want to make it faster. We don't know how many bits there
are to set or clear in the input set, but we do know exactly how
many bits there are to set AND clear. We can subdivide these into
batches by rows, then process each batch by storing sets at the
bottom and clears at the top. We can also do batches by columns,
reducing the memory overhead of unpacking all the bits at once.
(For extra credit, we could alternate set/clear settings, and
thus do batches of "the clears from row 0, followed by the clears
from row 1" and "the sets from row 1, followed by the sets from
row 2", and so on, but this is too fancy.)
Every caller of importValue is in fact already providing values
with column IDs sorted. As such, we don't need a map for checking
the previously-set columns; we just need to check against the
previous value.
We also implement, but disable for now, a check for sortedness of
inputs. This check was useful in development but it's expensive (about
5% of CPU time for large inputs!) and once we've verified that we
can make it through tests without triggering it, we're probably fine.
With timestamps, we probably want to at least check larger BSI fields,
so we add that. Also, tweak the interpretation of b.N (making each
N count for 10,000 bits) so we can see allocation load at all. But we
also reduce the sparse set to be about one bit per 19 bits, because
if we do one per 70,000, and are doing field-at-a-time imports, we're
getting hundreds of imports to try to match a target of, say, around
a million values.
We also sort the inputs, because ImportValue is about to start requiring
that, since the API does it anyway.
Also, extend this to be available on Fields, because field.ImportValue
is ALSO doing things which could be inefficient or expensive.
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.
When writing things that cause additions to the cache, mark it dirty and
flag it for recomputing, but only sometimes actually do the recalculation,
currently implying a 10-second window. We still mark the cache dirty,
so if a request comes in, we'll get fresh data, but the query will be
slowed down because the recomputation will happen then. But that's better
than doing thousands of recalculations which are never used...
When searching for a small array in a large array, scanning ahead
is productive. The switch from counting indexes to reslicing the
slice appears to improve performance in this case. The fairly arbitrary
value `na << 2` is like `nb / 4 > na` except that it computes faster,
and lets us avoid the expensive overhead unless we have reason to
expect that there's significantly more items in b than in a.
Improvements: Not huge in some cases, but sometimes quite noticeable,
especially as the frequency of overlap increases, which is also
the expensive case in other ways.
name old time/op new time/op delta
ImportMutexSampleData/64K/2Kr/40/none/write-0-8 501ms ± 4% 486ms ± 2% ~ (p=0.052 n=6+5)
ImportMutexSampleData/64K/2Kr/40/none/write-1-8 756ms ± 5% 698ms ± 5% -7.62% (p=0.002 n=6+6)
ImportMutexSampleData/64K/2Kr/80/none/write-0-8 292ms ± 3% 276ms ± 4% -5.46% (p=0.002 n=6+6)
ImportMutexSampleData/64K/2Kr/80/none/write-1-8 511ms ± 6% 482ms ± 4% -5.72% (p=0.015 n=6+6)
ImportMutexSampleData/64K/2Kr/240/none/write-0-8 153ms ± 3% 132ms ± 5% -13.91% (p=0.008 n=5+5)
ImportMutexSampleData/64K/2Kr/240/none/write-1-8 354ms ± 2% 215ms ± 6% -39.41% (p=0.004 n=5+6)
ImportMutexSampleData/1K/2Kr/40/none/write-0-8 565ms ± 3% 543ms ± 3% -3.89% (p=0.015 n=6+6)
ImportMutexSampleData/1K/2Kr/40/none/write-1-8 807ms ± 6% 778ms ± 3% ~ (p=0.180 n=6+6)
ImportMutexSampleData/1K/2Kr/80/none/write-0-8 317ms ± 3% 300ms ± 1% -5.40% (p=0.002 n=6+6)
ImportMutexSampleData/1K/2Kr/80/none/write-1-8 462ms ± 3% 437ms ± 4% -5.31% (p=0.009 n=6+6)
ImportMutexSampleData/1K/2Kr/240/none/write-0-8 141ms ± 1% 119ms ± 2% -15.85% (p=0.004 n=5+6)
ImportMutexSampleData/1K/2Kr/240/none/write-1-8 213ms ± 3% 171ms ± 3% -19.70% (p=0.002 n=6+6)
In BitmapBitmapFilter.ConsiderData, we intersect things solely in order
to perform callbacks on them. Creating these intermediate arrays is
actually somewhat expensive, and all we're going to do with them is
make callbacks anyway.
So, we add a new `intersectCallback`, which behaves similarly to
`intersectionCount`, but which dramatically reduces the amount of memory
allocation associated with doing the callbacks; in some test cases
on mutex data, this code was >90% of all memory allocations, and
getting rid of that helps a lot.
At that point, we no longer need the separate intersectAny check,
because it doesn't save us any time anymore.
The mutex tests had weird and un-idiomatic definitions for b.N, and
in particular would report ludicrously low times for high values of
b.N because they'd still only do a small amount of importing, then
get counted as having done a much larger number of iterations. Also,
the computation of the number of values to create was pretty noticably
wrong so the secondary data set was unduly tiny.
Do tests with ranked cache and larger row counts because we have
reason to suspect that the cache behavior is mattering. We adjust the
range of tests performed to reflect real world data a bit. We also
drop the "don't do large mutex tests" thing because the insanely
bad performance on larger mutex data should be fixed now, we hope.
boltDB's bucket.Put() is quadratic on "new keys put into a bucket during
this transaction", which is why BoltDB has warnings not to use it with over
100k new keys at a time. The translation store logic wasn't actually using
that. The actual value picked is smaller, based on some half-baked benchmarking.
We also avoid heap-allocating separate 16-byte (not 8-byte, of course,
because make(...) is *helping*) chunks twice for each key we insert, instead
allocating a single buffer which we reuse for each new transaction.
Also fixed a check against the nilness of the wrong pointer and generally
made CreateKeys and TranslateKeys a little more similar.
This commit fixes an issue where the root record cache is only
built when a write transaction successfully commits. However, if
no write transactions are occurring then the the cache is never
built and saved so it is recomputed on every read tx.
