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Posted to reviews@spark.apache.org by marmbrus <gi...@git.apache.org> on 2014/05/11 07:26:42 UTC
[GitHub] spark pull request: [SQL] Improve column pruning.
GitHub user marmbrus opened a pull request:
https://github.com/apache/spark/pull/729
[SQL] Improve column pruning.
Fixed a bug that was preventing us from ever pruning beneath Joins.
## TPC-DS Q3
### Before:
```
Aggregate false, [d_year#12,i_brand#65,i_brand_id#64], [d_year#12,i_brand_id#64 AS brand_id#0,i_brand#65 AS brand#1,SUM(PartialSum#79) AS sum_agg#2]
Exchange (HashPartitioning [d_year#12:0,i_brand#65:1,i_brand_id#64:2], 150)
Aggregate true, [d_year#12,i_brand#65,i_brand_id#64], [d_year#12,i_brand#65,i_brand_id#64,SUM(CAST(ss_ext_sales_price#49, DoubleType)) AS PartialSum#79]
Project [d_year#12:6,i_brand#65:59,i_brand_id#64:58,ss_ext_sales_price#49:43]
HashJoin [ss_item_sk#36], [i_item_sk#57], BuildRight
Exchange (HashPartitioning [ss_item_sk#36:30], 150)
HashJoin [d_date_sk#6], [ss_sold_date_sk#34], BuildRight
Exchange (HashPartitioning [d_date_sk#6:0], 150)
Filter (d_moy#14:8 = 12)
HiveTableScan [d_date_sk#6,d_date_id#7,d_date#8,d_month_seq#9,d_week_seq#10,d_quarter_seq#11,d_year#12,d_dow#13,d_moy#14,d_dom#15,d_qoy#16,d_fy_year#17,d_fy_quarter_seq#18,d_fy_week_seq#19,d_day_name#20,d_quarter_name#21,d_holiday#22,d_weekend#23,d_following_holiday#24,d_first_dom#25,d_last_dom#26,d_same_day_ly#27,d_same_day_lq#28,d_current_day#29,d_current_week#30,d_current_month#31,d_current_quarter#32,d_current_year#33], (MetastoreRelation default, date_dim, Some(dt)), None
Exchange (HashPartitioning [ss_sold_date_sk#34:0], 150)
HiveTableScan [ss_sold_date_sk#34,ss_sold_time_sk#35,ss_item_sk#36,ss_customer_sk#37,ss_cdemo_sk#38,ss_hdemo_sk#39,ss_addr_sk#40,ss_store_sk#41,ss_promo_sk#42,ss_ticket_number#43,ss_quantity#44,ss_wholesale_cost#45,ss_list_price#46,ss_sales_price#47,ss_ext_discount_amt#48,ss_ext_sales_price#49,ss_ext_wholesale_cost#50,ss_ext_list_price#51,ss_ext_tax#52,ss_coupon_amt#53,ss_net_paid#54,ss_net_paid_inc_tax#55,ss_net_profit#56], (MetastoreRelation default, store_sales, None), None
Exchange (HashPartitioning [i_item_sk#57:0], 150)
Filter (i_manufact_id#70:13 = 436)
HiveTableScan [i_item_sk#57,i_item_id#58,i_rec_start_date#59,i_rec_end_date#60,i_item_desc#61,i_current_price#62,i_wholesale_cost#63,i_brand_id#64,i_brand#65,i_class_id#66,i_class#67,i_category_id#68,i_category#69,i_manufact_id#70,i_manufact#71,i_size#72,i_formulation#73,i_color#74,i_units#75,i_container#76,i_manager_id#77,i_product_name#78], (MetastoreRelation default, item, None), None
```
### After
```
Aggregate false, [d_year#172,i_brand#225,i_brand_id#224], [d_year#172,i_brand_id#224 AS brand_id#160,i_brand#225 AS brand#161,SUM(PartialSum#239) AS sum_agg#162]
Exchange (HashPartitioning [d_year#172:0,i_brand#225:1,i_brand_id#224:2], 150)
Aggregate true, [d_year#172,i_brand#225,i_brand_id#224], [d_year#172,i_brand#225,i_brand_id#224,SUM(CAST(ss_ext_sales_price#209, DoubleType)) AS PartialSum#239]
Project [d_year#172:1,i_brand#225:5,i_brand_id#224:3,ss_ext_sales_price#209:0]
HashJoin [ss_item_sk#196], [i_item_sk#217], BuildRight
Exchange (HashPartitioning [ss_item_sk#196:2], 150)
Project [ss_ext_sales_price#209:2,d_year#172:1,ss_item_sk#196:3]
HashJoin [d_date_sk#166], [ss_sold_date_sk#194], BuildRight
Exchange (HashPartitioning [d_date_sk#166:0], 150)
Project [d_date_sk#166:0,d_year#172:1]
Filter (d_moy#174:2 = 12)
HiveTableScan [d_date_sk#166,d_year#172,d_moy#174], (MetastoreRelation default, date_dim, Some(dt)), None
Exchange (HashPartitioning [ss_sold_date_sk#194:2], 150)
HiveTableScan [ss_ext_sales_price#209,ss_item_sk#196,ss_sold_date_sk#194], (MetastoreRelation default, store_sales, None), None
Exchange (HashPartitioning [i_item_sk#217:1], 150)
Project [i_brand_id#224:0,i_item_sk#217:1,i_brand#225:2]
Filter (i_manufact_id#230:3 = 436)
HiveTableScan [i_brand_id#224,i_item_sk#217,i_brand#225,i_manufact_id#230], (MetastoreRelation default, item, None), None
```
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/marmbrus/spark fixPruning
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/729.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #729
----
commit 5feeff0746c534d3ba614946a34cfa973662736f
Author: Michael Armbrust <mi...@databricks.com>
Date: 2014-05-11T05:02:15Z
Improve column pruning.
----
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by pwendell <gi...@git.apache.org>.
Github user pwendell commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-43046539
#721 was merged instead of this... I'll merge it.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by yhuai <gi...@git.apache.org>.
Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/729#discussion_r12565390
--- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala ---
@@ -25,13 +25,13 @@ import org.apache.spark.sql.catalyst.types._
object Optimizer extends RuleExecutor[LogicalPlan] {
val batches =
- Batch("ConstantFolding", Once,
+ Batch("ConstantFolding", FixedPoint(100),
--- End diff --
Hi Michael, can you let me know why we want to run ConstandFolding more than once? Thanks:)
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by yhuai <gi...@git.apache.org>.
Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-42913020
Seems we are adding more `Project`s (for example, `Project [i_brand_id#224:0,i_item_sk#217:1,i_brand#225:2]` after `Filter (i_manufact_id#70:13 = 436)`). Do we need those `Project`s after we have pruned those leaf nodes (e.g. `HiveTableScan`)?
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by yhuai <gi...@git.apache.org>.
Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-43009684
LGTM
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/729
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by rxin <gi...@git.apache.org>.
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/729#discussion_r12607721
--- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala ---
@@ -25,13 +25,13 @@ import org.apache.spark.sql.catalyst.types._
object Optimizer extends RuleExecutor[LogicalPlan] {
val batches =
- Batch("ConstantFolding", Once,
+ Batch("ConstantFolding", FixedPoint(100),
--- End diff --
It might be good to come up with some example and add it as inline comments.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-42762607
Merged build triggered.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by rxin <gi...@git.apache.org>.
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-43040913
Thanks. Merged!
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/729#discussion_r12565415
--- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala ---
@@ -25,13 +25,13 @@ import org.apache.spark.sql.catalyst.types._
object Optimizer extends RuleExecutor[LogicalPlan] {
val batches =
- Batch("ConstantFolding", Once,
+ Batch("ConstantFolding", FixedPoint(100),
--- End diff --
Constant folding includes a bunch of rules that might work together. I don't have a specific example in mind though.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by marmbrus <gi...@git.apache.org>.
Github user marmbrus commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-42913442
That extra project is removing `i_manufact_id` before the shuffle, which is not needed after filtering.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-42763487
Merged build finished. All automated tests passed.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-42762609
Merged build started.
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[GitHub] spark pull request: [SQL] Improve column pruning.
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/729#issuecomment-42763488
All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/14883/
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