Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/21747
To backport this fix, we need to backport another improvement PR that
allows accessing SQLConf at executor side, which violates the backport rule. I
think it's ok to have this fix in 2.4 only
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22326
Some thoughts:
1. This rule is a little tricky as it only handles python udf accessing
attributes from both side. If it only accesses one side, we assume it can be
pushed down later
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22484
LGTM, cc @dongjoon-hyun for sign-off
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/19868
Can we also update the title?
```
Avoid iterating all partition paths when
spark.sql.hive.verifyPartitionPath=true
```
This is not true, we didn't fix the problem
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22529
LGTM
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22492
The next version is very likely to be 2.5.0...
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22522
I think this change is necessary, but I'd like to migrate one benchmark to
use this new trait as an example. We can migrate others in follow up PRs
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22522#discussion_r219672131
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/RunBenchmarkWithCodegen.scala
---
@@ -0,0 +1,52 @@
+/*
+ * Licensed
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22522#discussion_r219672121
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/RunBenchmarkWithCodegen.scala
---
@@ -0,0 +1,52 @@
+/*
+ * Licensed
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22407
LGTM except one comment
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22407#discussion_r219672065
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala ---
@@ -1045,6 +1045,36 @@ class DataFrameFunctionsSuite extends
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/19868
@jinxing64 Let's not talk too much about the problem of
`spark.sql.hive.verifyPartitionPath`. We should just introduce
`spark.sql.files.ignoreMissingFiles` and say this can replace
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22513
thanks, merging to master!
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Github user cloud-fan commented on the issue:
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LGTM
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/18544#discussion_r219505379
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveSessionCatalog.scala ---
@@ -131,14 +131,14 @@ private[sql] class HiveSessionCatalog
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/18544#discussion_r219505121
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveSessionCatalog.scala ---
@@ -131,14 +131,14 @@ private[sql] class HiveSessionCatalog
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
sorry, I screwed up my local branch and made a wrong conclusion. Turning
off the precise precision for integral literals can fix the regression. So it's
better to add a config
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22375#discussion_r219452615
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvalHelper.scala
---
@@ -223,8 +223,16 @@ trait
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
Sorry my mistake. I'm talking about the specific query reported at
https://issues.apache.org/jira/browse/SPARK-22036?focusedCommentId=16618104=com.atlassian.jira.plugin.system.issuetabpanels
Github user cloud-fan closed the pull request at:
https://github.com/apache/spark/pull/20276
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/20276
I'm closing it since `AnalysisBarrier` is no longer there. We should
revisit the whole self-join problem and fix it in 3.0, with breaking changes if
necessary
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22513
LGTM
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
I tried to add a new config, but decided to not do it. The problem is, when
users hit SPARK-25454, they must turn off both the
`DECIMAL_OPERATIONS_ALLOW_PREC_LOSS` and the new config
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22513
Please also explain which module(core or sql?) these benchmark classes
should be, in the PR description.
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22513#discussion_r219414758
--- Diff:
core/src/main/scala/org/apache/spark/sql/execution/benchmark/BenchmarkBase.scala
---
@@ -15,7 +15,7 @@
* limitations under the License
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22513#discussion_r219414641
--- Diff:
core/src/main/scala/org/apache/spark/sql/execution/benchmark/Benchmark.scala ---
@@ -15,7 +15,7 @@
* limitations under the License
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/18544#discussion_r219413664
--- Diff: sql/hive/src/test/scala/org/apache/spark/sql/hive/UDFSuite.scala
---
@@ -193,4 +193,29 @@ class UDFSuite
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/18544#discussion_r219412088
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/catalog/SessionCatalogSuite.scala
---
@@ -1440,6 +1441,8 @@ abstract class
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22511
is this a long-standing bug?
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this seems like a big change, will we hit perf regression?
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Github user cloud-fan commented on the issue:
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cc @jiangxb1987
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retest this please
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22508
LGTM, merging to master/2.4!
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Github user cloud-fan commented on the issue:
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Can you explain how do we fix the problem?
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lgtm, merging to master/2.4!
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/19868
Basically we need to introduce this new
`spark.sql.files.ignoreMissingFiles` config in detail. And them explain how can
we use it to replace `spark.sql.hive.verifyPartitionPath
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22458
LGTM. If there are more properties like `originalViewText` which are
useless to Spark and only need to be displayed, I'd suggest we create a map for
them, instead of adding more and more fields
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22505
thanks, merging to master/2.4!
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22316#discussion_r219368724
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala ---
@@ -416,7 +426,7 @@ class RelationalGroupedDataset protected
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22316#discussion_r219368791
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala ---
@@ -416,7 +426,7 @@ class RelationalGroupedDataset protected
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22316#discussion_r219368334
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala ---
@@ -330,6 +331,15 @@ class RelationalGroupedDataset protected
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22506
LGTM
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22450
totally agree, thanks for looking into it!
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22462
ds v2 is pre-beta, so not a critical bug to me. I'm OK to fix it in 2.4 if
someone is willing to pay the effort for fixing the conflict
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
why do we care about breaking operations when turning off a behavior change
config? The config is prepared for this case: if a user hit a problem of the
new behavior, he can use this config
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22450
given how complex it is, I feel we can start the design at 2.5 and
implement it at 3.0, what do you think
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22450
@dilipbiswal showed that DB2 and presto treat `1e100` as double instead of
decimal. We should consider this option and see what's the consequence
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
This PR is a no-op if users don't turn off #20023 . The benefit of this PR
is: before we fully fix that bug, if a user hit it, he can turn off #20023 to
temporarily work around it. So I don't see
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
2.3.2 and 2.4.0 are both in the RC stage, I don't want to spend a lot of
time to fix this long-standing bug and block 2 releases. cc @jerryshao too
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
yea, that's why I change the test to use `1e6 * 1000`, instead of `1000e6`.
The point is, we know there is a bug and it's hard to fix. What I'm trying
to do here is not fixing the bug
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
> So I think we can just add a check for avoiding a non-negative scale in
DecimalType.fromLiteral.
Can you open a PR for it? I did some experiments locally and this seems not
w
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22450
@mgaido91 well, your long explanation makes me think we should have a
design doc about it, and have more people to review it and ensure we cover all
the corner cases. And seems there are more
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22494
Maybe we should also consider to turn off
DECIMAL_OPERATIONS_ALLOW_PREC_LOSS by default.
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Github user cloud-fan commented on the issue:
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cc @mgaido91 @gatorsmile
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GitHub user cloud-fan opened a pull request:
https://github.com/apache/spark/pull/22494
[SPARK-22036][SQL][followup] DECIMAL_OPERATIONS_ALLOW_PREC_LOSS should
cover all the behavior changes
## What changes were proposed in this pull request?
https://github.com/apache/spark
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22365
retest this please
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22492
Since this changes public API, shall we also revert it from master?
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Github user cloud-fan commented on the issue:
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thanks, merging to master/2.4!
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22462
thanks, merging to master!
Since the ds v2 is very different between master and 2.4, it may not worth
to backport this PR to 2.4 and fix conflicts
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22481
thanks, merging to master/2.4!
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Github user cloud-fan commented on the issue:
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LGTM
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LGTM
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22408#discussion_r219039187
--- Diff: docs/sql-programming-guide.md ---
@@ -1879,6 +1879,66 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22408#discussion_r219038798
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala ---
@@ -735,6 +735,60 @@ class DataFrameFunctionsSuite extends
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22408#discussion_r219038350
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala ---
@@ -735,6 +735,60 @@ class DataFrameFunctionsSuite extends
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22408#discussion_r219037301
--- Diff: docs/sql-programming-guide.md ---
@@ -1879,6 +1879,66 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22408#discussion_r219037194
--- Diff: docs/sql-programming-guide.md ---
@@ -1879,6 +1879,66 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22408#discussion_r219037086
--- Diff: docs/sql-programming-guide.md ---
@@ -1879,6 +1879,66 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22365#discussion_r219034294
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala ---
@@ -370,29 +370,76 @@ final class DataFrameStatFunctions private
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22365
LGTM
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Github user cloud-fan commented on the issue:
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+1 for adding the note
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22443
thanks, merging to master!
@dongjoon-hyun Can you create an umbrella JIRA for updating all the
benchmark and take care of it? Thanks
Github user cloud-fan commented on the issue:
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LGTM, thanks!
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22462#discussion_r219028235
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/streaming/sources/StreamingDataSourceV2Suite.scala
---
@@ -143,15 +185,18 @@ class
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22464
just one PR including 4 commits
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https://github.com/apache/spark/pull/22408#discussion_r219019453
--- Diff: docs/sql-programming-guide.md ---
@@ -1879,6 +1879,80 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22408
Since it's a little risky to backport
https://github.com/apache/spark/pull/22448 , I'd like to merge this PR without
https://github.com/apache/spark/pull/22448 . Can you fix the conflict? thanks
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22448#discussion_r219019108
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercionSuite.scala
---
@@ -366,7 +366,29 @@ class TypeCoercionSuite
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22448#discussion_r219018725
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -106,6 +107,22 @@ object TypeCoercion
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22448#discussion_r219018069
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala
---
@@ -89,10 +90,10 @@ object TypeCoercion
Github user cloud-fan commented on the issue:
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thanks, merging to master!
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22464
@viirya Thanks for doing it! To ease the review, can you revert these 4
commits sequentially with `git revert commit-hash`? Thanks!
https://github.com/apache/spark/pull/22344
https
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22462#discussion_r219016643
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/streaming/sources/StreamingDataSourceV2Suite.scala
---
@@ -204,6 +249,37 @@ class
Github user cloud-fan commented on the issue:
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thanks, merging to master/2.4!
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Github user cloud-fan closed the pull request at:
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22470
@mgaido91 you are right, this still has behavior changes if the intermedia
result exceed the max precision. Since most of the storages don't support
negative scale(hive, parquet, etc.), I think
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22450
My major concern is:
1. how to prove `Divide` is the only one having problems of negative scale?
2. how to prove the fix here is corrected and covers all the corner cases?
I'm
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22465#discussion_r219011641
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -1561,6 +1561,13 @@ object SQLConf {
"are perf
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/21169
If we don't care about backward compatibility, I'd like to remove these 2
functions as they don't make sense according to how Spark defines timestamp.
This PR is a best effort to make these 2
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22475
LGTM
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LGTM, thanks for adding it!
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Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22469#discussion_r218877589
--- Diff: docs/sql-programming-guide.md ---
@@ -1879,6 +1879,7 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22402
thanks, merging to master/2.4!
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cc @mgaido91 @hvanhovell @gatorsmile
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Github user cloud-fan commented on the issue:
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I feel there are more places we need to fix for negative scale. I couldn't
find any design doc for negative scale in Spark and I believe we supported it
by accident.
That said, fixing
GitHub user cloud-fan opened a pull request:
https://github.com/apache/spark/pull/22470
[SPARK-25454][SQL] should not generate negative scale as possible as we can
## What changes were proposed in this pull request?
An alternative fix of https://github.com/apache/spark/pull
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22450#discussion_r218808837
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecision.scala
---
@@ -40,10 +40,13 @@ import
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/22355
thanks, merging to master!
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https://github.com/apache/spark/pull/22450#discussion_r218765559
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/DecimalPrecision.scala
---
@@ -129,16 +129,17 @@ object DecimalPrecision
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/22465#discussion_r218761706
--- Diff: sql/core/src/test/resources/sql-tests/inputs/operators.sql ---
@@ -26,6 +26,15 @@ select 5 div 0;
select 5 div null;
select null div 5
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