domoritz commented on pull request #10332:
URL: https://github.com/apache/arrow/pull/10332#issuecomment-841602502
@kou can we add this to the 4.0.1 release since it fixes build issues
(https://issues.apache.org/jira/browse/ARROW-12734)?
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domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841601667
I think there was some misunderstanding here. Despite the performance
degration, we can still merge this change as it simplifies the setup and fixes
Rollup builds. I re-opened
github-actions[bot] commented on pull request #10332:
URL: https://github.com/apache/arrow/pull/10332#issuecomment-841601571
https://issues.apache.org/jira/browse/ARROW-12578
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domoritz opened a new pull request #10332:
URL: https://github.com/apache/arrow/pull/10332
By @alippai
Reopened https://github.com/apache/arrow/pull/10181
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houqp commented on a change in pull request #55:
URL: https://github.com/apache/arrow-datafusion/pull/55#discussion_r632895922
##
File path: datafusion/src/logical_plan/plan.rs
##
@@ -141,7 +137,7 @@ pub enum LogicalPlan {
/// Produces rows from a table provider by
domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841599204
String decoding is really really slow. Would you want to help with the
materialization (https://issues.apache.org/jira/browse/ARROW-10220) @alippai?
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github-actions[bot] commented on pull request #10331:
URL: https://github.com/apache/arrow/pull/10331#issuecomment-841597553
https://issues.apache.org/jira/browse/ARROW-12796
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domoritz opened a new pull request #10331:
URL: https://github.com/apache/arrow/pull/10331
Supports getting the results as JSON.
Here is an example snippet.
```json
[
{
"name": "name: 'lat', length: 1,000,000, type: Float32, test: gt, value:
0",
"ops":
Jimexist commented on a change in pull request #328:
URL: https://github.com/apache/arrow-datafusion/pull/328#discussion_r632883017
##
File path: datafusion/src/physical_plan/functions.rs
##
@@ -1358,6 +1366,18 @@ impl fmt::Display for ScalarFunctionExpr {
}
}
+///
Jimexist commented on pull request #307:
URL: https://github.com/apache/arrow-datafusion/pull/307#issuecomment-841586169
closing this as we are aligned on using `NullArray`.
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Jimexist closed pull request #307:
URL: https://github.com/apache/arrow-datafusion/pull/307
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github-actions[bot] commented on pull request #10330:
URL: https://github.com/apache/arrow/pull/10330#issuecomment-841580077
https://issues.apache.org/jira/browse/ARROW-11673
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edponce opened a new pull request #10330:
URL: https://github.com/apache/arrow/pull/10330
This PR provides functionality to cast Dictionary indices between integral
types.
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nealrichardson closed pull request #10325:
URL: https://github.com/apache/arrow/pull/10325
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nealrichardson commented on a change in pull request #10327:
URL: https://github.com/apache/arrow/pull/10327#discussion_r632858178
##
File path: r/R/dplyr-functions.R
##
@@ -109,6 +109,39 @@ nse_funcs$as.numeric <- function(x) {
Expression$create("cast", x, options =
nealrichardson commented on pull request #9615:
URL: https://github.com/apache/arrow/pull/9615#issuecomment-841545022
I think this needs rebase, and then that should expose the other place where
`Table__from_dots` is called that needs `options_use_threads()` passed to it
(which is the
alippai edited a comment on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841541780
I'm closing this, as we agree that we don't want to remove the Buffer API.
Additional ideas for speedup:
Encode:
Use TextEncoder..encodeInto() and
alippai closed pull request #10181:
URL: https://github.com/apache/arrow/pull/10181
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alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841541780
I'm closing this, as we agree that we don't want to remove the TextEncoder
API.
Additional ideas for speedup:
Encode:
Use TextEncoder..encodeInto() and pre-allocate
nealrichardson commented on a change in pull request #10269:
URL: https://github.com/apache/arrow/pull/10269#discussion_r632849602
##
File path: r/R/record-batch.R
##
@@ -161,7 +161,18 @@ RecordBatch$create <- function(..., schema = NULL) {
out <-
trxcllnt edited a comment on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841535011
We do have [separate
entry-points](https://github.com/apache/arrow/blob/master/js/gulp/package-task.js#L49-L51)
today, so that's totally fine. We'd need to have some
trxcllnt commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841535011
We do have [separate
entry-points](https://github.com/apache/arrow/blob/master/js/gulp/package-task.js#L49-L51)
today, so that's totally fine. We'd need to have some shared
alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841533090
What do you think about shipping different entry files for node and browser
and solve this issue compile time?
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trxcllnt edited a comment on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841530218
Node didn't used to make the TextEncoder/TextDecoder globals, so if we want
to support the faster way in node we should figure out a way to control this at
the
trxcllnt commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841530218
Node didn't used to make the TextEncoder/TextDecoder globals, so if we want
to support node we should figure out a way to control this at the packaging or
import stages.
--
alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841529879
Performance: I ran microbenchmarks for TextEncoder vs Buffer+utils and
Buffer based is 50% percent faster for small, ascii strings. As we are using
larger strings or we switch
trxcllnt commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841529749
@alippai if you change the conditional to this and re-run `yarn build -t
es2015 -m cjs`, you can force it to use `Buffer.from`:
```ts
const useNativeEncoders = !_Buffer
domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841527729
Idk what causes the differences. @trxcllnt just ran a benchmark to compare
buffer vs no buffer.
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alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841526434
@domoritz what's happening? Am I reading the code wrong and it's actually
hitting https://github.com/apache/arrow/blob/master/js/src/util/utf8.ts#L35-L38
somehow, or is it just
domoritz edited a comment on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841524268
Master
Parse "tracks":
Table.from
x 5,289 ops/sec ±10.58% (76 runs sampled)
avg: 0.19ms
1.14% of a frame @ 60FPS
Parse "tracks":
domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841524268
Master
Parse "tracks":
Table.from
x 5,289 ops/sec ±10.58% (76 runs sampled)
avg: 0.19ms
1.14% of a frame @ 60FPS
Parse "tracks":
github-actions[bot] commented on pull request #10329:
URL: https://github.com/apache/arrow/pull/10329#issuecomment-841522714
Thanks for opening a pull request!
If this is not a [minor
PR](https://github.com/apache/arrow/blob/master/CONTRIBUTING.md#Minor-Fixes).
Could you
kszucs opened a new pull request #10329:
URL: https://github.com/apache/arrow/pull/10329
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alippai edited a comment on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841520624
During benchmarking it I realized that we already use TextEncoder and
TextDecoder only.
`useNativeEncoders` is always evaluated to `true` in all supported Node
alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841520624
During bencharking it I realized that we already use TextEncoder and
TextDecoder only.
`useNativeEncoders` is always evaluated to `true` in all supported Node
versions and
domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841519307
Caching keys is https://issues.apache.org/jira/browse/ARROW-10220 (cc
@bmschmidt).
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kou commented on pull request #10300:
URL: https://github.com/apache/arrow/pull/10300#issuecomment-841518230
Great!
Can we also generate `.jar` that doesn't need to bundle C++ libraries as the
next step? Then we don't need to generate any `.jar` in our release process.
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alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841514959
Dictionary may work as well, indeed. My understanding was that the buffer ->
string conversions happen only once for every dictionary value and it's cloned
later.
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kou commented on pull request #10325:
URL: https://github.com/apache/arrow/pull/10325#issuecomment-841513829
I think that this is a needless change. The original sentence is enough
readable.
Can we close this?
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trxcllnt commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841512673
@alippai that's the script. The categorical dictionaries are strings and
will show up in the output like this:
```
Get "tracks" values by index:
name: 'origin',
alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841512097
@domoritz I agree that some benchmarks should be added, I'll took into that
this weekend.
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alippai commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841511834
https://github.com/apache/arrow/blob/master/js/test/data/tables/generate.py
isn't this the test data generator script? I see only float and categorical
here, no string.
alamb closed issue #333:
URL: https://github.com/apache/arrow-datafusion/issues/333
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alamb commented on issue #333:
URL:
https://github.com/apache/arrow-datafusion/issues/333#issuecomment-841511146
Closed with https://github.com/apache/arrow-datafusion/pull/337
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jorgecarleitao merged pull request #330:
URL: https://github.com/apache/arrow-datafusion/pull/330
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jorgecarleitao closed issue #329:
URL: https://github.com/apache/arrow-datafusion/issues/329
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jorgecarleitao merged pull request #341:
URL: https://github.com/apache/arrow-datafusion/pull/341
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github-actions[bot] commented on pull request #10328:
URL: https://github.com/apache/arrow/pull/10328#issuecomment-841501243
Revision: aca4a4dcb55436549648dd1309644b979a749ddf
Submitted crossbow builds: [ursacomputing/crossbow @
jonkeane commented on pull request #10328:
URL: https://github.com/apache/arrow/pull/10328#issuecomment-841500916
@github-actions crossbow submit test-r-devdocs
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github-actions[bot] commented on pull request #10328:
URL: https://github.com/apache/arrow/pull/10328#issuecomment-841500784
https://issues.apache.org/jira/browse/ARROW-12785
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jonkeane opened a new pull request #10328:
URL: https://github.com/apache/arrow/pull/10328
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edponce commented on a change in pull request #10317:
URL: https://github.com/apache/arrow/pull/10317#discussion_r632797486
##
File path: cpp/src/arrow/compute/kernels/scalar_string.cc
##
@@ -266,6 +266,52 @@ void EnsureLookupTablesFilled() {}
#endif // ARROW_WITH_UTF8PROC
ianmcook commented on a change in pull request #10327:
URL: https://github.com/apache/arrow/pull/10327#discussion_r632797152
##
File path: r/R/expression.R
##
@@ -76,7 +76,15 @@
Expression <- R6Class("Expression", inherit = ArrowObject,
public = list(
ToString =
domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841497150
I think we should add a benchmark before merging this pull request
@trxcllnt.
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ianmcook commented on a change in pull request #10327:
URL: https://github.com/apache/arrow/pull/10327#discussion_r632795341
##
File path: r/R/expression.R
##
@@ -76,7 +76,15 @@
Expression <- R6Class("Expression", inherit = ArrowObject,
public = list(
ToString =
lidavidm closed pull request #10272:
URL: https://github.com/apache/arrow/pull/10272
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kszucs closed pull request #10300:
URL: https://github.com/apache/arrow/pull/10300
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github-actions[bot] commented on pull request #10327:
URL: https://github.com/apache/arrow/pull/10327#issuecomment-841489435
https://issues.apache.org/jira/browse/ARROW-12781
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ianmcook opened a new pull request #10327:
URL: https://github.com/apache/arrow/pull/10327
- adds base R-flavored `is.*()` functions for checking column types in dplyr
- adds a `$type_id()` method to `Expression` and to some other R6 classes
that were missing it
- changes how
westonpace commented on a change in pull request #10272:
URL: https://github.com/apache/arrow/pull/10272#discussion_r632767457
##
File path: python/pyarrow/array.pxi
##
@@ -2189,6 +2227,18 @@ cdef class StructArray(Array):
if names is not None and fields is not None:
yordan-pavlov commented on issue #200:
URL: https://github.com/apache/arrow-rs/issues/200#issuecomment-841471236
@jorgecarleitao the int32 support can be split out in a separate PR, I added
it now mostly so that I can benchmark how this approach would work for
primitive types.
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alamb commented on pull request #288:
URL: https://github.com/apache/arrow-rs/pull/288#issuecomment-841469082
And the tests are now all
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lidavidm closed pull request #9656:
URL: https://github.com/apache/arrow/pull/9656
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lidavidm commented on pull request #9656:
URL: https://github.com/apache/arrow/pull/9656#issuecomment-841464661
CI passes, so I'll go ahead and merge this.
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lidavidm closed pull request #10324:
URL: https://github.com/apache/arrow/pull/10324
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domoritz commented on pull request #10181:
URL: https://github.com/apache/arrow/pull/10181#issuecomment-841462855
There are discussions about a 4.0.1 release on the mailing list. This pull
request would need to get in soon to be included in the release.
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thisisnic commented on a change in pull request #10269:
URL: https://github.com/apache/arrow/pull/10269#discussion_r632754954
##
File path: r/R/record-batch.R
##
@@ -161,7 +161,18 @@ RecordBatch$create <- function(..., schema = NULL) {
out <-
rok commented on a change in pull request #9758:
URL: https://github.com/apache/arrow/pull/9758#discussion_r632754148
##
File path: cpp/src/arrow/compute/kernels/aggregate_basic.cc
##
@@ -75,48 +75,55 @@ struct CountImpl : public ScalarAggregator {
Status
thisisnic commented on a change in pull request #10269:
URL: https://github.com/apache/arrow/pull/10269#discussion_r632750639
##
File path: r/R/record-batch.R
##
@@ -161,7 +161,18 @@ RecordBatch$create <- function(..., schema = NULL) {
out <-
jorgecarleitao commented on issue #200:
URL: https://github.com/apache/arrow-rs/issues/200#issuecomment-841450481
ccing @nevi-me since he is the expert here.
I'd say let's go for it. @yordan-pavlov , is the PR decomposable or is not
worth the effort trying to split it?
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codecov-commenter commented on pull request #341:
URL: https://github.com/apache/arrow-datafusion/pull/341#issuecomment-841449969
#
github-actions[bot] commented on pull request #10326:
URL: https://github.com/apache/arrow/pull/10326#issuecomment-841447425
https://issues.apache.org/jira/browse/ARROW-12791
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alamb merged pull request #337:
URL: https://github.com/apache/arrow-datafusion/pull/337
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alamb commented on a change in pull request #303:
URL: https://github.com/apache/arrow-datafusion/pull/303#discussion_r632737073
##
File path: datafusion/src/physical_plan/functions.rs
##
@@ -1373,20 +1370,26 @@ impl PhysicalExpr for ScalarFunctionExpr {
}
fn
alamb commented on a change in pull request #328:
URL: https://github.com/apache/arrow-datafusion/pull/328#discussion_r632736152
##
File path: datafusion/src/physical_plan/functions.rs
##
@@ -1358,6 +1366,18 @@ impl fmt::Display for ScalarFunctionExpr {
}
}
+/// null
jorgecarleitao commented on a change in pull request #303:
URL: https://github.com/apache/arrow-datafusion/pull/303#discussion_r632735574
##
File path: datafusion/src/physical_plan/functions.rs
##
@@ -1373,20 +1370,26 @@ impl PhysicalExpr for ScalarFunctionExpr {
}
alamb opened a new pull request #341:
URL: https://github.com/apache/arrow-datafusion/pull/341
Until we get regular arrow-rs releases, I want to keep pulling updates from
arrow-rs into datafusion frequently and thus manually
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Dandandan commented on a change in pull request #303:
URL: https://github.com/apache/arrow-datafusion/pull/303#discussion_r632728287
##
File path: datafusion/src/physical_plan/functions.rs
##
@@ -1373,20 +1370,26 @@ impl PhysicalExpr for ScalarFunctionExpr {
}
fn
Dandandan commented on issue #200:
URL: https://github.com/apache/arrow-rs/issues/200#issuecomment-841434097
Cool, thanks for the update @yordan-pavlov . Let's see, a small slowdown at
some place can be fine if it's offset by other improvements and/or better code
quality or design!
--
jorgecarleitao commented on pull request #288:
URL: https://github.com/apache/arrow-rs/pull/288#issuecomment-841433092
@alamb the integration tests were failing about 8h ago, but all good now
afaik. Someone fixed this in apache/arrow :)
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alamb commented on pull request #288:
URL: https://github.com/apache/arrow-rs/pull/288#issuecomment-841432376
The integration test failure seems unrelated (though maybe not?) --
https://github.com/apache/arrow-rs/pull/288/checks?check_run_id=2574974207
I retriggered it to see if it
alamb closed issue #230:
URL: https://github.com/apache/arrow-rs/issues/230
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alamb merged pull request #273:
URL: https://github.com/apache/arrow-rs/pull/273
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alamb commented on a change in pull request #273:
URL: https://github.com/apache/arrow-rs/pull/273#discussion_r632724899
##
File path: arrow/src/util/display.rs
##
@@ -217,6 +231,9 @@ pub fn array_value_to_string(column: ::ArrayRef, row:
usize) -> Result
yordan-pavlov commented on issue #200:
URL: https://github.com/apache/arrow-rs/issues/200#issuecomment-841429737
@alamb thank you for taking the time to review my benchmark results.
I have done some profiling already, and although I haven't spent very long
looking into the results, it's
alamb commented on a change in pull request #303:
URL: https://github.com/apache/arrow-datafusion/pull/303#discussion_r632722624
##
File path: datafusion/src/physical_plan/functions.rs
##
@@ -1373,20 +1370,26 @@ impl PhysicalExpr for ScalarFunctionExpr {
}
fn
alamb commented on a change in pull request #334:
URL: https://github.com/apache/arrow-datafusion/pull/334#discussion_r632720978
##
File path: datafusion/src/logical_plan/builder.rs
##
@@ -289,6 +289,14 @@ impl LogicalPlanBuilder {
}))
}
+pub fn window(
+
thisisnic opened a new pull request #10326:
URL: https://github.com/apache/arrow/pull/10326
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jorgecarleitao commented on a change in pull request #289:
URL: https://github.com/apache/arrow-rs/pull/289#discussion_r632717500
##
File path: change_log.sh
##
@@ -0,0 +1,26 @@
+#!/bin/bash
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more
alamb commented on issue #200:
URL: https://github.com/apache/arrow-rs/issues/200#issuecomment-841423524
> @Dandandan @jorgecarleitao @alamb Let me know what you think - is the
simplification of reading arrow arrays using a single, iterator-based
abstraction worth a performance hit in a
alamb commented on a change in pull request #289:
URL: https://github.com/apache/arrow-rs/pull/289#discussion_r632713588
##
File path: change_log.sh
##
@@ -0,0 +1,26 @@
+#!/bin/bash
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license
alamb commented on pull request #335:
URL: https://github.com/apache/arrow-datafusion/pull/335#issuecomment-841410480
Incorporated into #288
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alamb closed pull request #335:
URL: https://github.com/apache/arrow-datafusion/pull/335
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alamb merged pull request #288:
URL: https://github.com/apache/arrow-datafusion/pull/288
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alamb closed issue #251:
URL: https://github.com/apache/arrow-datafusion/issues/251
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jorgecarleitao commented on a change in pull request #337:
URL: https://github.com/apache/arrow-datafusion/pull/337#discussion_r632701908
##
File path: datafusion/src/logical_plan/plan.rs
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@@ -356,13 +356,15 @@ pub enum Partitioning {
/// after all children have been
alamb commented on pull request #288:
URL: https://github.com/apache/arrow-datafusion/pull/288#issuecomment-841408299
I filed https://github.com/apache/arrow-datafusion/issues/340 to track
possible future work on stateful functions
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alamb commented on issue #340:
URL:
https://github.com/apache/arrow-datafusion/issues/340#issuecomment-841408125
My personal take is that adding some way to mark a `ScalarFunction` as being
`immutable`, `stable` or `volatile` would be valuable for query optimization
(e.g. we could
alamb opened a new issue #340:
URL: https://github.com/apache/arrow-datafusion/issues/340
**Is your feature request related to a problem or challenge? Please describe
what you are trying to do.**
On a PR that added what postgres would term a `stable` function (something
that is not the
codecov-commenter commented on pull request #337:
URL: https://github.com/apache/arrow-datafusion/pull/337#issuecomment-841406715
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