This repository has been archived by the owner on May 9, 2024. It is now read-only.
[SPARK-8978][Streaming] Implements the DirectKafkaRateController #18
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
huitseeker
force-pushed
the
SPARK-8978
branch
5 times, most recently
from
b69ec1d to
1503e05
Compare
| if (ratePerSec > 0) { | ||
| protected def maxMessagesPerPartition: Option[Long] = { | ||
| val estimatedRate = rateController.getLatestRate().toInt | ||
| val effectiveRatePerSec = if (estimatedRate > 0) (ratePerSec min estimatedRate) else ratePerSec |
There was a problem hiding this comment.
The estimated rate is per stream, not per Kafka partition (like the configuration parameter above). Shouldn't this be accounted for in here?
huitseeker
force-pushed
the
SPARK-8978
branch
3 times, most recently
from
eccb008 to
2fa8a60
Compare
|
Refer to this link for build results (access rights to CI server needed): Build Log Test FAILed. |
…ements the ReceiverRateController
|
Refer to this link for build results (access rights to CI server needed): Build Log Test FAILed. |
|
Refer to this link for build results (access rights to CI server needed): Build Log Test FAILed. |
|
Refer to this link for build results (access rights to CI server needed): Build Log Test FAILed. |
dragos
force-pushed
the
topic/streaming-bp/dynamic-rate
branch
from
13ada97 to
0c51959
Compare
|
ok to test |
|
Refer to this link for build results (access rights to CI server needed): Build Log Test FAILed. |
|
ok to test |
|
Refer to this link for build results (access rights to CI server needed): Build Log Test FAILed. |
fdp-ci
pushed a commit
that referenced
this pull request
Aug 27, 2019
## What changes were proposed in this pull request? This PR aims at improving the way physical plans are explained in spark. Currently, the explain output for physical plan may look very cluttered and each operator's string representation can be very wide and wraps around in the display making it little hard to follow. This especially happens when explaining a query 1) Operating on wide tables 2) Has complex expressions etc. This PR attempts to split the output into two sections. In the header section, we display the basic operator tree with a number associated with each operator. In this section, we strictly control what we output for each operator. In the footer section, each operator is verbosely displayed. Based on the feedback from Maryann, the uncorrelated subqueries (SubqueryExecs) are not included in the main plan. They are printed separately after the main plan and can be correlated by the originating expression id from its parent plan. To illustrate, here is a simple plan displayed in old vs new way. Example query1 : ``` EXPLAIN SELECT key, Max(val) FROM explain_temp1 WHERE key > 0 GROUP BY key HAVING max(val) > 0 ``` Old : ``` *(2) Project [key#2, max(val)#15] +- *(2) Filter (isnotnull(max(val#3)#18) AND (max(val#3)#18 > 0)) +- *(2) HashAggregate(keys=[key#2], functions=[max(val#3)], output=[key#2, max(val)#15, max(val#3)#18]) +- Exchange hashpartitioning(key#2, 200) +- *(1) HashAggregate(keys=[key#2], functions=[partial_max(val#3)], output=[key#2, max#21]) +- *(1) Project [key#2, val#3] +- *(1) Filter (isnotnull(key#2) AND (key#2 > 0)) +- *(1) FileScan parquet default.explain_temp1[key#2,val#3] Batched: true, DataFilters: [isnotnull(key#2), (key#2 > 0)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/explain_temp1], PartitionFilters: [], PushedFilters: [IsNotNull(key), GreaterThan(key,0)], ReadSchema: struct<key:int,val:int> ``` New : ``` Project (8) +- Filter (7) +- HashAggregate (6) +- Exchange (5) +- HashAggregate (4) +- Project (3) +- Filter (2) +- Scan parquet default.explain_temp1 (1) (1) Scan parquet default.explain_temp1 [codegen id : 1] Output: [key#2, val#3] (2) Filter [codegen id : 1] Input : [key#2, val#3] Condition : (isnotnull(key#2) AND (key#2 > 0)) (3) Project [codegen id : 1] Output : [key#2, val#3] Input : [key#2, val#3] (4) HashAggregate [codegen id : 1] Input: [key#2, val#3] (5) Exchange Input: [key#2, max#11] (6) HashAggregate [codegen id : 2] Input: [key#2, max#11] (7) Filter [codegen id : 2] Input : [key#2, max(val)#5, max(val#3)#8] Condition : (isnotnull(max(val#3)#8) AND (max(val#3)#8 > 0)) (8) Project [codegen id : 2] Output : [key#2, max(val)#5] Input : [key#2, max(val)#5, max(val#3)#8] ``` Example Query2 (subquery): ``` SELECT * FROM explain_temp1 WHERE KEY = (SELECT Max(KEY) FROM explain_temp2 WHERE KEY = (SELECT Max(KEY) FROM explain_temp3 WHERE val > 0) AND val = 2) AND val > 3 ``` Old: ``` *(1) Project [key#2, val#3] +- *(1) Filter (((isnotnull(KEY#2) AND isnotnull(val#3)) AND (KEY#2 = Subquery scalar-subquery#39)) AND (val#3 > 3)) : +- Subquery scalar-subquery#39 : +- *(2) HashAggregate(keys=[], functions=[max(KEY#26)], output=[max(KEY)apache#45]) : +- Exchange SinglePartition : +- *(1) HashAggregate(keys=[], functions=[partial_max(KEY#26)], output=[max#47]) : +- *(1) Project [key#26] : +- *(1) Filter (((isnotnull(KEY#26) AND isnotnull(val#27)) AND (KEY#26 = Subquery scalar-subquery#38)) AND (val#27 = 2)) : : +- Subquery scalar-subquery#38 : : +- *(2) HashAggregate(keys=[], functions=[max(KEY#28)], output=[max(KEY)apache#43]) : : +- Exchange SinglePartition : : +- *(1) HashAggregate(keys=[], functions=[partial_max(KEY#28)], output=[max#49]) : : +- *(1) Project [key#28] : : +- *(1) Filter (isnotnull(val#29) AND (val#29 > 0)) : : +- *(1) FileScan parquet default.explain_temp3[key#28,val#29] Batched: true, DataFilters: [isnotnull(val#29), (val#29 > 0)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/explain_temp3], PartitionFilters: [], PushedFilters: [IsNotNull(val), GreaterThan(val,0)], ReadSchema: struct<key:int,val:int> : +- *(1) FileScan parquet default.explain_temp2[key#26,val#27] Batched: true, DataFilters: [isnotnull(key#26), isnotnull(val#27), (val#27 = 2)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/explain_temp2], PartitionFilters: [], PushedFilters: [IsNotNull(key), IsNotNull(val), EqualTo(val,2)], ReadSchema: struct<key:int,val:int> +- *(1) FileScan parquet default.explain_temp1[key#2,val#3] Batched: true, DataFilters: [isnotnull(key#2), isnotnull(val#3), (val#3 > 3)], Format: Parquet, Location: InMemoryFileIndex[file:/user/hive/warehouse/explain_temp1], PartitionFilters: [], PushedFilters: [IsNotNull(key), IsNotNull(val), GreaterThan(val,3)], ReadSchema: struct<key:int,val:int> ``` New: ``` Project (3) +- Filter (2) +- Scan parquet default.explain_temp1 (1) (1) Scan parquet default.explain_temp1 [codegen id : 1] Output: [key#2, val#3] (2) Filter [codegen id : 1] Input : [key#2, val#3] Condition : (((isnotnull(KEY#2) AND isnotnull(val#3)) AND (KEY#2 = Subquery scalar-subquery#23)) AND (val#3 > 3)) (3) Project [codegen id : 1] Output : [key#2, val#3] Input : [key#2, val#3] ===== Subqueries ===== Subquery:1 Hosting operator id = 2 Hosting Expression = Subquery scalar-subquery#23 HashAggregate (9) +- Exchange (8) +- HashAggregate (7) +- Project (6) +- Filter (5) +- Scan parquet default.explain_temp2 (4) (4) Scan parquet default.explain_temp2 [codegen id : 1] Output: [key#26, val#27] (5) Filter [codegen id : 1] Input : [key#26, val#27] Condition : (((isnotnull(KEY#26) AND isnotnull(val#27)) AND (KEY#26 = Subquery scalar-subquery#22)) AND (val#27 = 2)) (6) Project [codegen id : 1] Output : [key#26] Input : [key#26, val#27] (7) HashAggregate [codegen id : 1] Input: [key#26] (8) Exchange Input: [max#35] (9) HashAggregate [codegen id : 2] Input: [max#35] Subquery:2 Hosting operator id = 5 Hosting Expression = Subquery scalar-subquery#22 HashAggregate (15) +- Exchange (14) +- HashAggregate (13) +- Project (12) +- Filter (11) +- Scan parquet default.explain_temp3 (10) (10) Scan parquet default.explain_temp3 [codegen id : 1] Output: [key#28, val#29] (11) Filter [codegen id : 1] Input : [key#28, val#29] Condition : (isnotnull(val#29) AND (val#29 > 0)) (12) Project [codegen id : 1] Output : [key#28] Input : [key#28, val#29] (13) HashAggregate [codegen id : 1] Input: [key#28] (14) Exchange Input: [max#37] (15) HashAggregate [codegen id : 2] Input: [max#37] ``` Note: I opened this PR as a WIP to start getting feedback. I will be on vacation starting tomorrow would not be able to immediately incorporate the feedback. I will start to work on them as soon as i can. Also, currently this PR provides a basic infrastructure for explain enhancement. The details about individual operators will be implemented in follow-up prs ## How was this patch tested? Added a new test `explain.sql` that tests basic scenarios. Need to add more tests. Closes apache#24759 from dilipbiswal/explain_feature. Authored-by: Dilip Biswal <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This depends on #16