An update: we found a mistake that we picked the Spark 3.2 release date based on the scheduled release date of 3.1. However, 3.1 was delayed and released on March 2. In order to have a full 6 months development for 3.2, the target release date for 3.2 should be September 2.
I'm updating the release dates in https://github.com/apache/spark-website/pull/331 Thanks, Wenchen On Thu, Mar 11, 2021 at 11:17 PM Dongjoon Hyun <dongjoon.h...@gmail.com> wrote: > Thank you, Xiao, Wenchen and Hyukjin. > > Bests, > Dongjoon. > > > On Thu, Mar 11, 2021 at 2:15 AM Hyukjin Kwon <gurwls...@gmail.com> wrote: > >> Just for an update, I will send a discussion email about my idea late >> this week or early next week. >> >> 2021년 3월 11일 (목) 오후 7:00, Wenchen Fan <cloud0...@gmail.com>님이 작성: >> >>> There are many projects going on right now, such as new DS v2 APIs, ANSI >>> interval types, join improvement, disaggregated shuffle, etc. I don't >>> think it's realistic to do the branch cut in April. >>> >>> I'm +1 to release 3.2 around July, but it doesn't mean we have to cut >>> the branch 3 months earlier. We should make the release process faster and >>> cut the branch around June probably. >>> >>> >>> >>> On Thu, Mar 11, 2021 at 4:41 AM Xiao Li <gatorsm...@gmail.com> wrote: >>> >>>> Below are some nice-to-have features we can work on in Spark 3.2: Lateral >>>> Join support <https://issues.apache.org/jira/browse/SPARK-28379>, >>>> interval data type, timestamp without time zone, un-nesting arbitrary >>>> queries, the returned metrics of DSV2, and error message standardization. >>>> Spark 3.2 will be another exciting release I believe! >>>> >>>> Go Spark! >>>> >>>> Xiao >>>> >>>> >>>> >>>> >>>> Dongjoon Hyun <dongjoon.h...@gmail.com> 于2021年3月10日周三 下午12:25写道： >>>> >>>>> Hi, Xiao. >>>>> >>>>> This thread started 13 days ago. Since you asked the community about >>>>> major features or timelines at that time, could you share your roadmap or >>>>> expectations if you have something in your mind? >>>>> >>>>> > Thank you, Dongjoon, for initiating this discussion. Let us keep it >>>>> open. It might take 1-2 weeks to collect from the community all the >>>>> features we plan to build and ship in 3.2 since we just finished the 3.1 >>>>> voting. >>>>> > TBH, cutting the branch this April does not look good to me. That >>>>> means, we only have one month left for feature development of Spark 3.2. >>>>> Do >>>>> we have enough features in the current master branch? If not, are we able >>>>> to finish major features we collected here? Do they have a timeline or >>>>> project plan? >>>>> >>>>> Bests, >>>>> Dongjoon. >>>>> >>>>> >>>>> >>>>> On Wed, Mar 3, 2021 at 2:58 PM Dongjoon Hyun <dongjoon.h...@gmail.com> >>>>> wrote: >>>>> >>>>>> Hi, John. >>>>>> >>>>>> This thread aims to share your expectations and goals (and maybe work >>>>>> progress) to Apache Spark 3.2 because we are making this together. :) >>>>>> >>>>>> Bests, >>>>>> Dongjoon. >>>>>> >>>>>> >>>>>> On Wed, Mar 3, 2021 at 1:59 PM John Zhuge <jzh...@apache.org> wrote: >>>>>> >>>>>>> Hi Dongjoon, >>>>>>> >>>>>>> Is it possible to get ViewCatalog in? The community already had >>>>>>> fairly detailed discussions. >>>>>>> >>>>>>> Thanks, >>>>>>> John >>>>>>> >>>>>>> On Thu, Feb 25, 2021 at 8:57 AM Dongjoon Hyun < >>>>>>> dongjoon.h...@gmail.com> wrote: >>>>>>> >>>>>>>> Hi, All. >>>>>>>> >>>>>>>> Since we have been preparing Apache Spark 3.2.0 in master branch >>>>>>>> since December 2020, March seems to be a good time to share our >>>>>>>> thoughts >>>>>>>> and aspirations on Apache Spark 3.2. >>>>>>>> >>>>>>>> According to the progress on Apache Spark 3.1 release, Apache Spark >>>>>>>> 3.2 seems to be the last minor release of this year. Given the >>>>>>>> timeframe, >>>>>>>> we might consider the following. (This is a small set. Please add your >>>>>>>> thoughts to this limited list.) >>>>>>>> >>>>>>>> # Languages >>>>>>>> >>>>>>>> - Scala 2.13 Support: This was expected on 3.1 via SPARK-25075 but >>>>>>>> slipped out. Currently, we are trying to use Scala 2.13.5 via >>>>>>>> SPARK-34505 >>>>>>>> and investigating the publishing issue. Thank you for your >>>>>>>> contributions >>>>>>>> and feedback on this. >>>>>>>> >>>>>>>> - Java 17 LTS Support: Java 17 LTS will arrive in September 2017. >>>>>>>> Like Java 11, we need lots of support from our dependencies. Let's see. >>>>>>>> >>>>>>>> - Python 3.6 Deprecation(?): Python 3.6 community support ends at >>>>>>>> 2021-12-23. So, the deprecation is not required yet, but we had better >>>>>>>> prepare it because we don't have an ETA of Apache Spark 3.3 in 2022. >>>>>>>> >>>>>>>> - SparkR CRAN publishing: As we know, it's discontinued so far. >>>>>>>> Resuming it depends on the success of Apache SparkR 3.1.1 CRAN >>>>>>>> publishing. >>>>>>>> If it succeeds to revive it, we can keep publishing. Otherwise, I >>>>>>>> believe >>>>>>>> we had better drop it from the releasing work item list officially. >>>>>>>> >>>>>>>> # Dependencies >>>>>>>> >>>>>>>> - Apache Hadoop 3.3.2: Hadoop 3.2.0 becomes the default Hadoop >>>>>>>> profile in Apache Spark 3.1. Currently, Spark master branch lives on >>>>>>>> Hadoop >>>>>>>> 3.2.2's shaded clients via SPARK-33212. So far, there is one on-going >>>>>>>> report at YARN environment. We hope it will be fixed soon at Spark 3.2 >>>>>>>> timeframe and we can move toward Hadoop 3.3.2. >>>>>>>> >>>>>>>> - Apache Hive 2.3.9: Spark 3.0 starts to use Hive 2.3.7 by default >>>>>>>> instead of old Hive 1.2 fork. Spark 3.1 removed hive-1.2 profile >>>>>>>> completely >>>>>>>> via SPARK-32981 and replaced the generated hive-service-rpc code with >>>>>>>> the >>>>>>>> official dependency via SPARK-32981. We are steadily improving this >>>>>>>> area >>>>>>>> and will consume Hive 2.3.9 if available. >>>>>>>> >>>>>>>> - K8s Client 4.13.2: During K8s GA activity, Spark 3.1 upgrades K8s >>>>>>>> client dependency to 4.12.0. Spark 3.2 upgrades it to 4.13.2 in order >>>>>>>> to >>>>>>>> support K8s model 1.19. >>>>>>>> >>>>>>>> - Kafka Client 2.8: To bring the client fixes, Spark 3.1 is using >>>>>>>> Kafka Client 2.6. For Spark 3.2, SPARK-33913 upgraded to Kafka 2.7 with >>>>>>>> Scala 2.12.13, but it was reverted later due to Scala 2.12.13 issue. >>>>>>>> Since >>>>>>>> KAFKA-12357 fixed the Scala requirement two days ago, Spark 3.2 will go >>>>>>>> with Kafka Client 2.8 hopefully. >>>>>>>> >>>>>>>> # Some Features >>>>>>>> >>>>>>>> - Data Source v2: Spark 3.2 will deliver much richer DSv2 with >>>>>>>> Apache Iceberg integration. Especially, we hope the on-going function >>>>>>>> catalog SPIP and up-coming storage partitioned join SPIP can be >>>>>>>> delivered >>>>>>>> as a part of Spark 3.2 and become an additional foundation. >>>>>>>> >>>>>>>> - Columnar Encryption: As of today, Apache Spark master branch >>>>>>>> supports columnar encryption via Apache ORC 1.6 and it's documented via >>>>>>>> SPARK-34036. Also, upcoming Apache Parquet 1.12 has a similar >>>>>>>> capability. >>>>>>>> Hopefully, Apache Spark 3.2 is going to be the first release to have >>>>>>>> this >>>>>>>> feature officially. Any feedback is welcome. >>>>>>>> >>>>>>>> - Improved ZStandard Support: Spark 3.2 will bring more benefits >>>>>>>> for ZStandard users: 1) SPARK-34340 added native ZSTD JNI buffer pool >>>>>>>> support for all IO operations, 2) SPARK-33978 makes ORC datasource >>>>>>>> support >>>>>>>> ZSTD compression, 3) SPARK-34503 sets ZSTD as the default codec for >>>>>>>> event >>>>>>>> log compression, 4) SPARK-34479 aims to support ZSTD at Avro data >>>>>>>> source. >>>>>>>> Also, the upcoming Parquet 1.12 supports ZSTD (and supports JNI buffer >>>>>>>> pool), too. I'm expecting more benefits. >>>>>>>> >>>>>>>> - Structure Streaming with RocksDB backend: According to the latest >>>>>>>> update, it looks active enough for merging to master branch in Spark >>>>>>>> 3.2. >>>>>>>> >>>>>>>> Please share your thoughts and let's build better Apache Spark 3.2 >>>>>>>> together. >>>>>>>> >>>>>>>> Bests, >>>>>>>> Dongjoon. >>>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> John Zhuge >>>>>>> >>>>>>
