Hi All, As per the above proposal, I have worked on a POC ( https://github.com/apache/iceberg/pull/8488).
*But to move things forward, first we need to merge the spec PR (https://github.com/apache/iceberg/pull/7105 <https://github.com/apache/iceberg/pull/7105>). *I don't see any blocker for the spec. Please review and approve if it is ok. One topic that came up during the review is whether to write stats synchronously or asynchronously. My suggestion is that we need to support both. I think we can first have an async writing implementation. But we also need to support sync stats writing with writes (controlled by a table property). Some engines like Trino, Dremio can make use of the sync writing of the stats. Currently Puffin stats also supports sync writing from Trino. Thanks, Ajantha On Mon, May 22, 2023 at 10:15 PM Ryan Blue <b...@tabular.io> wrote: > Thanks, Ajantha. I think it's safe to say that we should continue assuming > that we will have one partition stats file. I agree that it should be small > and we don't want to block the progress here. > > On Mon, May 22, 2023 at 5:07 AM Ajantha Bhat <ajanthab...@gmail.com> > wrote: > >> Hi Anton and Ryan, >> >> The Partition stats spec PR <https://github.com/apache/iceberg/pull/7105> >> didn't >> move forward as Anton wanted to conduct some experiments to conclude >> whether single-file writing or multiple files is better. >> I conducted the experiments myself and attached some numbers in the PR. >> >> I would like to take this forward. >> Please let me know what you think (can comment on the PR). >> >> As the output file is very small and initially the stats are computed >> asynchronously, >> I think writing them as a single file should be good enough. >> In future, If we need faster stats writing (along with each write >> operation) we can also implement multiple stats files. >> >> Just like how copy-on-write and merge-on-read are serving their use cases >> in Iceberg, >> we might have to support both single-file writing and multiple-file >> writing in the long run. >> >> Thanks, >> Ajantha >> >> On Wed, May 17, 2023 at 1:38 AM Mayur Srivastava < >> mayur.srivast...@twosigma.com> wrote: >> >>> I agree, it totally depends on the way “last modified time” per >>> partition is implemented. >>> >>> I’m concerned about performance of computing partition stats (and >>> storage + the size of table metadata files) if the implementation requires >>> users to keep around all snapshots. (I described one of my use case in this >>> thread earlier.) >>> >>> >>> >>> *From:* Pucheng Yang <py...@pinterest.com.INVALID> >>> *Sent:* Monday, May 15, 2023 11:46 AM >>> *To:* dev@iceberg.apache.org >>> *Subject:* Re: [Proposal] Partition stats in Iceberg >>> >>> >>> >>> Hi Mayur, can you elaborate your concern? I don't know how this is going >>> to be implemented so not sure where the performance issue is. >>> >>> >>> >>> On Mon, May 15, 2023 at 7:55 AM Mayur Srivastava < >>> mayur.srivast...@twosigma.com> wrote: >>> >>> Thanks Ryan. >>> >>> For most partition stats, I’m ok with compaction and keeping fewer >>> snapshots. My concern was for supporting last modified time. I guess, if we >>> need to keep all snapshots to support last modified time, it could have >>> impact on metadata access performance. >>> >>> >>> >>> Thanks, >>> >>> Mayur >>> >>> >>> >>> *From:* Ryan Blue <b...@tabular.io> >>> *Sent:* Wednesday, May 3, 2023 2:00 PM >>> *To:* dev@iceberg.apache.org >>> *Subject:* Re: [Proposal] Partition stats in Iceberg >>> >>> >>> >>> Mayur, your use case may require a lot of snapshots, but we generally >>> recommend expiring them after a few days. You can tag snapshots to keep >>> them around longer than that. >>> >>> >>> >>> On Tue, May 2, 2023 at 4:52 PM Mayur Srivastava < >>> mayur.p.srivast...@gmail.com> wrote: >>> >>> Thanks for the response. >>> >>> One of the use cases that we have is where one business day of data is >>> added at a time to a DAY partitioned table. With 25 years of this data, >>> there will be ~6250 partitions and as many snapshots. Are these many >>> snapshots recommended to be kept around? >>> >>> >>> >>> On Tue, May 2, 2023 at 7:45 PM Szehon Ho <szehon.apa...@gmail.com> >>> wrote: >>> >>> >>> >>> Does snapshot expiration needs to be disabled for this to work? Thanks, >>> Mayur >>> >>> >>> Yes, the snapshot that last updated the partition needs to be around for >>> this to work. >>> >>> >>> >>> Szehon, the query you shared requires a SparkSQL job to be run which >>> means latency will be high. However, I am glad you are also thinking of >>> adding these directly to the partition table and it seems we share the same >>> interests. >>> >>> >>> Yea the partitions table currently still goes through SparkSQL, so it >>> will be the same. Maybe you mean add this to partition stats? We do need >>> to reconcile partition table and partition stats at some point though. Not >>> sure if it was designed/discussed yet, I think there was some thoughts on >>> short-circuiting Partitions table to read from Partition stats, if stats >>> exist for the current snapshot. >>> >>> >>> >>> Thanks >>> >>> Szehon >>> >>> >>> >>> On Tue, May 2, 2023 at 4:34 PM Pucheng Yang <py...@pinterest.com.invalid> >>> wrote: >>> >>> Thanks Ryan and Szehon! >>> >>> >>> >>> Szehon, the query you shared requires a SparkSQL job to be run which >>> means latency will be high. However, I am glad you are also thinking of >>> adding these directly to the partition table and it seems we share the same >>> interests. I am looking forward to the work in the phase 2 implementation. >>> Let me know if I can help, thanks. >>> >>> >>> >>> On Tue, May 2, 2023 at 4:28 PM Szehon Ho <szehon.apa...@gmail.com> >>> wrote: >>> >>> Yea I agree, I had a handy query for the last update time of partition. >>> >>> >>> >>> SELECT >>> >>> e.data_file.partition, >>> >>> MAX(s.committed_at) AS last_modified_time >>> >>> FROM db.table.snapshots s >>> >>> JOIN db.table.entries e >>> >>> WHERE s.snapshot_id = e.snapshot_id >>> >>> GROUP BY by e.data_file.partition >>> >>> >>> >>> It's a bit lengthy currently. >>> >>> >>> >>> I have been indeed thinking to look at adding these fields to the >>> Partitions table directly, after Ajantha's pending changes to add delete >>> files to this table. >>> >>> >>> >>> Thanks >>> >>> Szehon >>> >>> >>> >>> On Tue, May 2, 2023 at 4:08 PM Ryan Blue <b...@tabular.io> wrote: >>> >>> Pucheng, >>> >>> >>> >>> Rather than using the changelog, I'd just look at the metadata tables. >>> You should be able to query the all_entries metadata table to see file >>> additions or deletions for a given snapshot. Then from there you can join >>> to the snapshots table for timestamps and aggregate to the partition level. >>> >>> >>> >>> Ryan >>> >>> >>> >>> On Fri, Apr 28, 2023 at 12:49 PM Pucheng Yang < >>> py...@pinterest.com.invalid> wrote: >>> >>> Hi Ajantha and the community, >>> >>> >>> >>> I am interested and I am wondering where we can see the latest progress >>> of this feature? >>> >>> >>> >>> Regarding the partition stats in Iceberg, I am specifically curious if >>> we can consider a new field called "last modified time" to be included for >>> the partitions stats (or have a plugable way to allow users to >>> configure partition stats they need). My use case is to find out if a >>> partition is changed or not given two snapshots (old and new) with a >>> quick and light way process. I previously was suggested by the community to >>> use the change log (CDC) but I think that is too heavy (I guess, since it >>> requires to run SparkSQL procedure) and it is over do the work (I don't >>> need what rows are changed, I just need true or false for whether a >>> partition is changed). >>> >>> >>> >>> Thanks >>> >>> >>> >>> On Tue, Feb 7, 2023 at 11:36 AM Mayur Srivastava < >>> mayur.srivast...@twosigma.com> wrote: >>> >>> Thanks Ajantha. >>> >>> >>> >>> > It should be very easy to add a few more fields to it like the latest >>> sequence number or last modified time per partition. >>> >>> >>> >>> Among sequence number and modified time, which one do you think is more >>> likely to be available in Iceberg partition stats? Note that we would like >>> to avoid compaction change the sequence number or modified time stats. >>> >>> >>> >>> Thanks, >>> >>> Mayur >>> >>> >>> >>> *From:* Ajantha Bhat <ajanthab...@gmail.com> >>> *Sent:* Tuesday, February 7, 2023 10:02 AM >>> *To:* dev@iceberg.apache.org >>> *Subject:* Re: [Proposal] Partition stats in Iceberg >>> >>> >>> >>> Hi Hrishi and Mayur, thanks for the inputs. >>> >>> To get things moving I have frozen the scope of phase 1 implementation. >>> (Recently added the delete file stats to phase 1 too). You can find the >>> scope in the "Design for approval" section of the design doc. >>> >>> That said, once we have phase 1 implemented, It should be very easy to >>> add a few more fields to it like the latest sequence number or last >>> modified time per partition. >>> I will be opening up the discussion about phase 2 schema again once >>> phase 1 implementation is done. >>> >>> Thanks, >>> Ajantha >>> >>> >>> >>> On Tue, Feb 7, 2023 at 8:15 PM Mayur Srivastava < >>> mayur.srivast...@twosigma.com> wrote: >>> >>> +1 for the initiative. >>> >>> >>> >>> We’ve been exploring options for storing last-modified-time per >>> partition. It an important building block for data pipelines – especially >>> if there is a dependency between jobs with strong consistency requirements. >>> >>> >>> >>> Is partition stats a good place for storing last-modified-time per >>> partition? >>> >>> >>> >>> Thanks, >>> >>> Mayur >>> >>> >>> >>> *From:* Ajantha Bhat <ajanthab...@gmail.com> >>> *Sent:* Monday, January 23, 2023 11:56 AM >>> *To:* dev@iceberg.apache.org >>> *Subject:* Re: [Proposal] Partition stats in Iceberg >>> >>> >>> >>> Hi All, >>> >>> In the same design document ( >>> https://docs.google.com/document/d/1vaufuD47kMijz97LxM67X8OX-W2Wq7nmlz3jRo8J5Qk/edit?usp=sharing >>> ), >>> I have added a section called >>> *"Design for approval". *It also contains a potential PR breakdown for >>> the phase 1 implementation and future development scope. >>> Please take a look and please vote if you think the design is ok. >>> >>> Thanks, >>> Ajantha >>> >>> >>> >>> On Mon, Dec 5, 2022 at 8:37 PM Ajantha Bhat <ajanthab...@gmail.com> >>> wrote: >>> >>> A big thanks to everyone who was involved in the review and the >>> discussions so far. >>> >>> Please find the meeting minutes from the last iceberg sync about the >>> partition stats. >>> a. Writers should not write the partition stats or any stats as of >>> now. >>> Because it requires bumping the spec to V3. (We can have it as >>> part of the v3 spec later on. But not anytime soon). >>> b. So, there can be an async way of generating the stats like >>> ANALYZE table or call procedure. >>> Which will compute the stats till the current snapshot and store >>> it as a partition stats file. >>> c. In phase 1, partition stats will just store the row_count and >>> file_count per partition value as mentioned in the design document. >>> Later it can be enhanced to store puffin file location and other >>> metrics per partition value. >>> d. These tuples are stored in a single sorted Avro/parquet file (we >>> need to finalize this). >>> e. Each time "analyze table" will rewrite the whole stats file as >>> keeping multiple delta files will just make the read path messy. >>> Also, even with million rows, it can be of a few MB size. >>> Once the writers start writing the stats (V3 spec), we can >>> revisit storing as the delta files if there are any performance issues. >>> >>> The next immediate plan is to >>> a. Get these PRs merged (open points in existing StatictisFile >>> interface added during Puffin) >>> #6267 <https://github.com/apache/iceberg/pull/6267>, #6090 >>> <https://github.com/apache/iceberg/pull/6090>, #6091 >>> <https://github.com/apache/iceberg/pull/6091> >>> b. Figure out how to give accurate stats with row-level deletes and >>> how to mask dropped partition values from stats. >>> https://github.com/apache/iceberg/issues/6042 >>> c. Standardize the `StatictisFile` interface to hold the >>> parquet/Avro stats file (instead of always assuming it as a Puffin file) >>> and introduce a `StatisticsType` enum. >>> d. Conclude the storage format and get approval for the design. >>> >>> I will wait another week or two for some more people to take a look at >>> the document >>> >>> before jumping into the implementation. >>> >>> Thanks, >>> Ajantha. >>> >>> >>> >>> On Sat, Nov 26, 2022 at 8:25 AM Ajantha Bhat <ajanthab...@gmail.com> >>> wrote: >>> >>> Hi Ryan, >>> >>> are you saying that you think the partition-level stats should not be >>> required? I think that would be best. >>> >>> I think there is some confusion here. Partition-level stats are >>> required (hence the proposal). >>> But does the writer always write it? (with the append/delete/replace >>> operation) >>> or writer skips writing it and then the user generates it using DML like >>> "Analyze table" was the point of discussion. >>> I think we can have both options with the writer stats writing >>> controlled by a table property "write.stats.enabled" >>> >>> >>> >>> I’m all for improving the interface for retrieving stats. It’s a >>> separate issue >>> >>> Agree. Let us discuss it in a separate thread. >>> >>> Thanks, >>> Ajantha >>> >>> >>> >>> On Sat, Nov 26, 2022 at 12:12 AM Ryan Blue <b...@tabular.io> wrote: >>> >>> Ajantha, are you saying that you think the partition-level stats should >>> not be required? I think that would be best. >>> >>> I’m all for improving the interface for retrieving stats. It’s a >>> separate issue, but I think that Iceberg should provide both access to the >>> Puffin files and metadata as well as a higher-level interface for >>> retrieving information like a column’s NDV. Something like this: >>> >>> int ndv = >>> table.findStat(Statistics.NDV).limitSnapshotDistance(3).forColumn("x"); >>> >>> >>> >>> On Thu, Nov 24, 2022 at 2:31 AM Ajantha Bhat <ajanthab...@gmail.com> >>> wrote: >>> >>> Hi Ryan, >>> Thanks a lot for the review and suggestions. >>> >>> but I think there is also a decision that we need to make before that: >>> Should Iceberg require writers to maintain the partition stats? >>> >>> I think I would prefer to take a lazy approach and not assume that >>> writers will keep the partition stats up to date, >>> >>> in which case we need a way to know which parts of a table are newer >>> than the most recent stats. >>> >>> >>> >>> This is a common problem for existing table-level puffin stats too. Not >>> just for partition stats. >>> As mentioned in the "integration with the current code" section point >>> 8), >>> I was planning to introduce a table property "write.stats.enabled" with >>> a default value set to false. >>> >>> And as per point 7), I was planning to introduce an "ANALYZE table" or >>> "CALL procedure" SQL (maybe table-level API too) to asynchronously >>> compute the stats on demand from the previous checkpoints. >>> >>> But currently, `TableMetadata` doesn't have a clean Interface to provide >>> the statistics file for the current snapshot. >>> If stats are not present, we need another interface to provide a last >>> successful snapshot id for which stats was computed. >>> Also, there is some confusion around reusing the statistics file >>> (because the spec only has a computed snapshot id, not the referenced >>> snapshot id). >>> I am planning to open up a PR to handle these interface updates >>> this week. (same things as you suggested in the last Iceberg sync). >>> This should serve as a good foundation to get insights for lazy & >>> incremental stats computing. >>> >>> >>> Thanks, >>> Ajantha >>> >>> >>> >>> On Thu, Nov 24, 2022 at 12:50 AM Ryan Blue <b...@tabular.io> wrote: >>> >>> Thanks for writing this up, Ajantha! I think that we have all the >>> upstream pieces in place to work on this so it's great to have a proposal. >>> >>> >>> >>> The proposal does a good job of summarizing the choices for how to store >>> the data, but I think there is also a decision that we need to make before >>> that: Should Iceberg require writers to maintain the partition stats? >>> >>> >>> >>> If we do want writers to participate, then we may want to make choices >>> that are easier for writers. But I think that is going to be a challenge. >>> Adding requirements for writers would mean that we need to bump the spec >>> version. Otherwise, we aren't guaranteed that writers will update the files >>> correctly. I think I would prefer to take a lazy approach and not assume >>> that writers will keep the partition stats up to date, in which case we >>> need a way to know which parts of a table are newer than the most recent >>> stats. >>> >>> >>> >>> Ryan >>> >>> >>> >>> On Wed, Nov 23, 2022 at 4:36 AM Ajantha Bhat <ajanthab...@gmail.com> >>> wrote: >>> >>> Thanks Piotr for taking a look at it. >>> I have replied to all the comments in the document. >>> I might need your support in standardising the existing `StatisticsFile` >>> interface to adopt partition stats as mentioned in the design. >>> >>> >>> >>> *We do need more eyes on the design. Once I get approval for the design, >>> I can start the implementation. * >>> Thanks, >>> Ajantha >>> >>> >>> >>> On Wed, Nov 23, 2022 at 3:28 PM Piotr Findeisen <pi...@starburstdata.com> >>> wrote: >>> >>> Hi Ajantha, >>> >>> >>> >>> this is very interesting document, thank you for your work on this! >>> >>> I've added a few comments there. >>> >>> >>> >>> I have one high-level design comment so I thought it would be nicer to >>> everyone if I re-post it here >>> >>> >>> >>> is "partition" the right level of keeping the stats? >>> We do this in Hive, but was it an accidental choice? or just the only >>> thing that was possible to be implemented many years ago? >>> >>> >>> >>> Iceberg allows to have higher number of partitions compared to Hive, >>> because it scales better. But that means partition-level may or may not be >>> the right granularity. >>> >>> >>> A self-optimizing system would gather stats on "per query unit" basis -- >>> for example if i partition by [ day x country ], but usually query by day, >>> the days are the "query unit" and from stats perspective country can be >>> ignored. >>> Having more fine-grained partitions may lead to expensive planning time, >>> so it's not theoretical problem. >>> >>> >>> I am not saying we should implement all this logic right now, but I >>> think we should decouple partitioning scheme from stats partitions, to >>> allow query engine to become smarter. >>> >>> >>> >>> >>> >>> cc @Alexander Jo <alex...@starburstdata.com> >>> >>> >>> >>> Best >>> >>> PF >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> On Mon, Nov 14, 2022 at 12:47 PM Ajantha Bhat <ajanthab...@gmail.com> >>> wrote: >>> >>> Hi Community, >>> I did a proposal write-up for the partition stats in Iceberg. >>> Please have a look and let me know what you think. I would like to work >>> on it. >>> >>> >>> https://docs.google.com/document/d/1vaufuD47kMijz97LxM67X8OX-W2Wq7nmlz3jRo8J5Qk/edit?usp=sharing >>> >>> Requirement background snippet from the above document. >>> >>> For some query engines that use cost-based-optimizer instead or along >>> with rule-based-optimizer (like Dremio, Trino, etc), at the planning time, >>> it is good to know the partition level stats like total rows per >>> partition and total files per partition to take decisions for CBO ( >>> like deciding on the join reordering and join type, identifying the >>> parallelism). >>> Currently, the only way to do this is to read the partition info from >>> data_file >>> in manifest_entry of the manifest file and compute partition-level >>> statistics (the same thing that ‘partitions’ metadata table is doing *[see >>> **Appendix A* >>> <https://docs.google.com/document/d/1vaufuD47kMijz97LxM67X8OX-W2Wq7nmlz3jRo8J5Qk/edit#heading=h.s8iywtu7x8m6> >>> *]*). >>> Doing this on each query is expensive. *Hence, this is a proposal for >>> computing and storing partition-level stats for Iceberg tables and using >>> them during queries.* >>> >>> >>> >>> Thanks, >>> Ajantha >>> >>> >>> >>> >>> -- >>> >>> Ryan Blue >>> >>> Tabular >>> >>> >>> >>> >>> -- >>> >>> Ryan Blue >>> >>> Tabular >>> >>> >>> >>> >>> -- >>> >>> Ryan Blue >>> >>> Tabular >>> >>> >>> >>> >>> -- >>> >>> Ryan Blue >>> >>> Tabular >>> >>> > > -- > Ryan Blue > Tabular >
