[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16752304#comment-16752304
]
Bruce Robbins commented on SPARK-26711:
---
[~hyukjin.kwon] Ok, that worked. I had in my mind a more verbose fix. I will
open a PR with the one line change.
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16752103#comment-16752103
]
Hyukjin Kwon commented on SPARK-26711:
--
Just open a PR that replace one line after manually testing it. I don't think
we should update the benchmark again since you're going to update it in
https://github.com/apache/spark/pull/23336
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16752102#comment-16752102
]
Hyukjin Kwon commented on SPARK-26711:
--
Oh, right. Sounds a good lead to follow. We can just add `lazy val decimalTry`
to that val in that case. Can you try and make a PR?
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16751655#comment-16751655
]
Bruce Robbins commented on SPARK-26711:
---
Re: 7 minutes vs. 50 seconds:
Looking at the code, it appears the difference is this:
Before the timestamp inference change, options.prefersDecimal was checked
before attempting to convert the String to a BigDecimal. If
options.prefersDecimal is disabled, we would not bother with the conversion.
After the timestamp inference change, we always attempt to convert the String
to a BigDecimal regardless of the setting of options.prefersDecimal (we still
use options.prefersDecimal to determine what type to return)
My guess is that attempting to convert every string to a BigDecimal is very
expensive.
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16750748#comment-16750748
]
Hyukjin Kwon commented on SPARK-26711:
--
Hm, the results say something is wrong hm. 50 sec <> 7 mins sounds serious.
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16750741#comment-16750741
]
Bruce Robbins commented on SPARK-26711:
---
[~hyukjin.kwon]
inferTimestamp=: ~13 min
inferTimestamp=false: ~7 min
7 minutes is a lot better than 13 minutes, but still not as good as 50 seconds.
A quick look in the profiler shows that in the case where inferTimestamp is
_disabled_, Spark is spending 96% of its time here:
{code:java}
val bigDecimal = decimalParser(field)
{code}
That line did change in the original commit.
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16750713#comment-16750713
]
Hyukjin Kwon commented on SPARK-26711:
--
So how was the time if {{inferTimestamp}} was enable/disabled? It would be odd
even if there's regression with {{inferTimestamp}} disabled. It just compares
one if-else.
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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[jira] [Commented] (SPARK-26711) JSON Schema inference takes 15 times longer
[
https://issues.apache.org/jira/browse/SPARK-26711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16750704#comment-16750704
]
Bruce Robbins commented on SPARK-26711:
---
ping [~maxgekk] [~hyukjin.kwon]
> JSON Schema inference takes 15 times longer
> ---
>
> Key: SPARK-26711
> URL: https://issues.apache.org/jira/browse/SPARK-26711
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Bruce Robbins
>Priority: Major
>
> I noticed that the first benchmark/case of JSONBenchmark ("JSON schema
> inferring", "No encoding") was taking an hour to run, when it used to run in
> 4-5 minutes.
> The culprit seems to be this commit:
> [https://github.com/apache/spark/commit/d72571e51d]
> A quick look using a profiler, and it seems to be spending 99% of its time
> doing some kind of exception handling in JsonInferSchema.scala.
> You can reproduce in the spark-shell by recreating the data used by the
> benchmark
> {noformat}
> scala> :paste
> val rowsNum = 100 * 1000 * 1000
> spark.sparkContext.range(0, rowsNum, 1)
> .map(_ => "a")
> .toDF("fieldA")
> .write
> .option("encoding", "UTF-8")
> .json("utf8.json")
> // Entering paste mode (ctrl-D to finish)
> // Exiting paste mode, now interpreting.
> rowsNum: Int = 1
> scala>
> {noformat}
> Then you can run the test by hand starting spark-shell as so (emulating
> SqlBasedBenchmark):
> {noformat}
> bin/spark-shell --driver-memory 8g \
> --conf "spark.sql.autoBroadcastJoinThreshold=1" \
> --conf "spark.sql.shuffle.partitions=1" --master "local[1]"
> {noformat}
> On commit d72571e51d:
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548297682225
> res0: Long = 815978 <== 13.6 minutes
> scala>
> {noformat}
> On the previous commit (86100df54b):
> {noformat}
> scala> val start = System.currentTimeMillis; spark.read.json("utf8.json");
> System.currentTimeMillis-start
> start: Long = 1548298927151
> res0: Long = 50087 <= 50 seconds
> scala>
> {noformat}
> I also tried {{spark.read.option("inferTimestamp",
> false).json("utf8.json")}}, but that option didn't seem to make a difference
> in run time. Edit: {{inferTimestamp}} does, in fact, have an impact: It
> halves the run time. However, that means even with {{inferTimestamp}}, the
> run time is still 7 times slower than before.
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