[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user adrian-wang commented on the pull request: https://github.com/apache/spark/pull/11071#issuecomment-183791219 @srowen you are right. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user srowen commented on the pull request: https://github.com/apache/spark/pull/11071#issuecomment-180793931 @adrian-wang but the `@transient` was applied to the whole reference to the `Map`. This doesn't make sense. The way to avoid a big cache is with weak keys, which has nothing to do with transient or serialization; this is not an instance field anyway. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
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[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
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[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
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[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user adrian-wang commented on a diff in the pull request: https://github.com/apache/spark/pull/11071#discussion_r51851087 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala --- @@ -55,10 +56,19 @@ object DateTimeUtils { // this is year -17999, calculation: 50 * daysIn400Year final val YearZero = -17999 final val toYearZero = to2001 + 7304850 - final val TimeZoneGMT = TimeZone.getTimeZone("GMT") @transient lazy val defaultTimeZone = TimeZone.getDefault + // Reuse the TimeZone object as it is expensive to create in each method call. + final val timeZones = new ConcurrentHashMap[String, TimeZone] --- End diff -- This map could be quite big, because the string varies. Actually `ZoneInfoFile` does provide a cache for different `ID`s. Let's find out whether the boost you mentioned comes from reusing `TimeZone` or `Calendar` instances. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user adrian-wang commented on a diff in the pull request: https://github.com/apache/spark/pull/11071#discussion_r51851099 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala --- @@ -55,10 +56,19 @@ object DateTimeUtils { // this is year -17999, calculation: 50 * daysIn400Year final val YearZero = -17999 final val toYearZero = to2001 + 7304850 - final val TimeZoneGMT = TimeZone.getTimeZone("GMT") @transient lazy val defaultTimeZone = TimeZone.getDefault + // Reuse the TimeZone object as it is expensive to create in each method call. + final val timeZones = new ConcurrentHashMap[String, TimeZone] --- End diff -- This map could be quite big, because the string varies. Actually `ZoneInfoFile` does provide a cache for different `ID`s. Let's find out whether the boost you mentioned comes from reusing `TimeZone` or `Calendar` instances. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user adrian-wang commented on a diff in the pull request: https://github.com/apache/spark/pull/11071#discussion_r51852765 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala --- @@ -55,10 +56,19 @@ object DateTimeUtils { // this is year -17999, calculation: 50 * daysIn400Year final val YearZero = -17999 final val toYearZero = to2001 + 7304850 - final val TimeZoneGMT = TimeZone.getTimeZone("GMT") @transient lazy val defaultTimeZone = TimeZone.getDefault + // Reuse the TimeZone object as it is expensive to create in each method call. + final val timeZones = new ConcurrentHashMap[String, TimeZone] --- End diff -- By use this map we can skip a lot of calls to `getTimeZone`, which is a synchronized method, `ConcurrentHashMap` can help improve performance, that's true. Do we need add a `transient`? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user adrian-wang commented on a diff in the pull request: https://github.com/apache/spark/pull/11071#discussion_r51853631 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala --- @@ -55,10 +56,19 @@ object DateTimeUtils { // this is year -17999, calculation: 50 * daysIn400Year final val YearZero = -17999 final val toYearZero = to2001 + 7304850 - final val TimeZoneGMT = TimeZone.getTimeZone("GMT") @transient lazy val defaultTimeZone = TimeZone.getDefault + // Reuse the TimeZone object as it is expensive to create in each method call. + final val timeZones = new ConcurrentHashMap[String, TimeZone] --- End diff -- Actually, we only need to change all `getTimeZone(String ID)` to `getTimeZone(String ID, boolean fallback)`, (use true as fallback) to workaround the synchronized tag here. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
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[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user carsonwang commented on the pull request: https://github.com/apache/spark/pull/11071#issuecomment-180172808 retest this please --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user carsonwang commented on a diff in the pull request: https://github.com/apache/spark/pull/11071#discussion_r51972422 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/DateTimeUtils.scala --- @@ -55,10 +56,19 @@ object DateTimeUtils { // this is year -17999, calculation: 50 * daysIn400Year final val YearZero = -17999 final val toYearZero = to2001 + 7304850 - final val TimeZoneGMT = TimeZone.getTimeZone("GMT") @transient lazy val defaultTimeZone = TimeZone.getDefault + // Reuse the TimeZone object as it is expensive to create in each method call. + final val timeZones = new ConcurrentHashMap[String, TimeZone] --- End diff -- Added `transient`. The total available timezone IDs should be limited. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark pull request: [SPARK-13185][SQL] Improve the performance of ...
Github user srowen commented on the pull request: https://github.com/apache/spark/pull/11071#issuecomment-180200750 transient is wrong for a static member. What are you trying to do, avoid a large cache? There are ways to do this but its not this. but how many timezones could there be? And are these not already cached? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user carsonwang commented on the pull request: https://github.com/apache/spark/pull/11071#issuecomment-180207538 I have a sub query like this `SELECT a, b, c FROM table UV WHERE (datediff(UV.visitDate, '1997-01-01')>=0 AND datediff(UV.visitDate, '2015-01-01')<=0)) ` When profiling this stage with Spark 1.6, I noticed a lot time was consumed by `DateTimeUtils.stringToDate`. Especially, `TimeZone.getTimeZone` and `Calendar.getInstance` are extremely slow. The table stores `visitDate` as `String` type and has 3 billion records. This means it creates 3 billion `Calendar` and `TimeZone` objects. `TimeZone.getTimeZone` is a synchronized method and will block other threads calling this same method. #10994 fixed one for `DateTimeUtils.stringToDate`. But `DateTimeUtils.stringToTimestamp` has the same issue so I tried to cache the `TimeZone` objects in a map. The total available number of `TimeZone` should be limited. By reusing `Calendar` object instead of creating it each time in the method, I can see more performance improvement. Creating 20 millions `Calendar` objects will take more that 20 seconds on my machine. So we will benefit from reusing it. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user adrian-wang commented on the pull request: https://github.com/apache/spark/pull/11071#issuecomment-180201265 The map key could be like "UTC+01:00". "American/Los Angeles", "PST", etc., they are already cached in `getTimeZone`, but the method itself is a synchronized one. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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GitHub user carsonwang opened a pull request: https://github.com/apache/spark/pull/11071 [SPARK-13185][SQL] Improve the performance of DateTimeUtils by reusing TimeZone and Calendar objects It is expensive to create java TimeZone and Calendar objects in each method of DateTimeUtils. We can reuse the objects to improve the performance. In one of my Sql queries which calls StringToDate many times, the duration of the stage improved from 1.6 minutes to 1.2 minutes. You can merge this pull request into a Git repository by running: $ git pull https://github.com/carsonwang/spark DateTimeUtilsFix Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/11071.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 #11071 commit cb9b157525c05c1a3d33b8c820595cf020a21b43 Author: Carson WangDate: 2016-02-04T08:12:59Z Reuse TimeZone and Calendar objects in DateTimeUtils --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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