My preference would be 1, 3, 2 in that order. Not super strong opinion though, my take is that any of them works for the near term until the type dies off.
On Thu, Jul 24, 2025 at 6:46 PM Ed Seidl <etse...@apache.org> wrote: > If INT96 is to remain deprecated, I'd prefer 1. If we want a defined > ordering for INT96 I'd prefer 3 to maintaining a "known good" list. > > As to the forward compatibility issue with rust, that's already an issue > with logical types (and any other unions in the spec). We're currently > trying to work that [1]. > > Cheers, > Ed > > [1] https://github.com/apache/arrow-rs/issues/7909 > > On 2025/07/24 08:19:13 Gang Wu wrote: > > For 1 and 2, do we need to maintain an allow-list for known writer > > implementations > > as well as their versions officially? My feeling is no. Perhaps it is the > > responsibility > > of interesting implementations to maintain it internally because many > > projects may > > not even care about INT96 stats. > > > > For 3, I think it is a bug of implementations who fail on new column > order. > > If we want > > to move forward [1] by adding a new column order for IEEE754 total order, > > this bug > > should be fixed anyway. > > > > [1] https://github.com/apache/parquet-format/pull/221 > > > > On Thu, Jul 24, 2025 at 1:30 AM Micah Kornfield <emkornfi...@gmail.com> > > wrote: > > > > > Just to follow up on this, I think the last issues remaining are > updating > > > the spec. > > > > > > There is already a draft PR ( > > > https://github.com/apache/parquet-format/pull/504) for updating the > spec. > > > > > > I think there are three main options: > > > 1. Keep ordering for int96 undefined with an implementation note (the > > > current PR does this). > > > 2. Formalize ordering as now defined using the timestamp ordering. > > > 3. Formalize ordering as now defined using the timestamp ordering and > > > define a new SortOrder required for writers/readers to use stats. > > > > > > The main trade-offs are for options 1 and 2, we potentially need to > allow > > > list implementations that are known to produce valid stats (e.g. older > > > versions of Rust were writing stats that didn't conform to Timestamp > > > ordering). > > > > > > For item #3, the main issue is that not all readers might be forward > > > compatible for a new sort order. In particular Rust readers would > break on > > > any new files [1]. > > > > > > Given this I suggest we move forward with the currently opened PR and > not > > > officially formalize this in th spec. Implementations will need to > > > allow-list for known good writers. > > > > > > Thanks, > > > Micah > > > > > > > > > [1] https://github.com/apache/arrow-rs/issues/7909 > > > > > > > > > > > > On Mon, Jun 30, 2025 at 8:55 AM Alkis Evlogimenos > > > <alkis.evlogime...@databricks.com.invalid> wrote: > > > > > > > I also checked internally with the Spark OSS team and the plan for > having > > > > INT64 timestamps in Spark by default is to make the change when > Delta v5 > > > > and Iceberg v4 are proposed. This is expected to happen around the > first > > > > half of 2026. > > > > > > > > On Wed, Jun 25, 2025 at 8:41 PM Andrew Lamb <andrewlam...@gmail.com> > > > > wrote: > > > > > > > > > We had a good discussion about this at the sync today. Here is my > > > > summary > > > > > > > > > > * Pedantically, according to the current spec[1] there is no > defined > > > > > ordering for Int96 types and thus arrow-rs can not be writing > > > "incorrect" > > > > > values (as there is no definition of correct) > > > > > * Practically speaking, arrow-rs is writing something different > than > > > > Photon > > > > > (Databricks proprietary spark engine) > > > > > * What Photon is doing arguably makes more sense (to use the > ordering > > > of > > > > > the only logical type to use Int96) > > > > > * GH-7686: [Parquet] Fix int96 min/max stats #7687[2] brings > arrow-rs > > > > into > > > > > line with Photon which makes sense to me > > > > > > > > > > Rahul has also filed a ticket in parquet-format to discuss > formalizing > > > > the > > > > > ordering of Int96 statistics[3] > > > > > > > > > > In the interim, I filed a PR[4] in the parquet-format repo to at > least > > > > try > > > > > and clarify the intent of the changes to arrow-rs and parquet-java > > > > > > > > > > Thanks, > > > > > Andrew > > > > > > > > > > > > > > > [1]: > > > > > > > > > > > > > > > > > > https://github.com/apache/parquet-format/blob/cf943c197f4fad826b14ba0c40eb0ffdab585285/src/main/thrift/parquet.thrift#L1079 > > > > > [2]: https://github.com/apache/arrow-rs/pull/7687 > > > > > [3]: https://github.com/apache/parquet-format/issues/502 > > > > > [4]: https://github.com/apache/parquet-format/pull/504 > > > > > > > > > > > > > > > On Wed, Jun 25, 2025 at 10:52 AM Rahul Sharma > > > > > <rahul.sha...@databricks.com.invalid> wrote: > > > > > > > > > > > I have prepared a doc > > > > > > < > > > > > > > > > > > > > > > > > > > https://docs.google.com/document/d/1Ox0qHYBgs_3-pNqn9V8zVQm_W6qP0lsbd2XwQnQVz1Y/edit?tab=t.0 > > > > > > > > > > > > > to summarize and have all the relevant links in one place. > > > > > > > > > > > > On Wed, Jun 25, 2025 at 1:32 PM Alkis Evlogimenos > > > > > > <alkis.evlogime...@databricks.com.invalid> wrote: > > > > > > > > > > > > > Spark needs to start writing INT64 nanos first to be able to > > > replace > > > > > > INT96 > > > > > > > which is in nanos if data is at nano granularity. This is why I > > > > linked > > > > > > that > > > > > > > ticket which is a prerequisite to switching to INT64 in many > cases. > > > > > > > > > > > > > > I understand the concerns around changing a deprecated aspect > of > > > the > > > > > > > parquet spec. The reason we decided to bring this forward is > > > because: > > > > > > > 1. there are a lot of parquet files with the right INT96 stats > > > > outthere > > > > > > > (Photon has been writing them for years) > > > > > > > 2. all engines ignore the INT96 stats so Photon writing them > didn't > > > > > break > > > > > > > anyone > > > > > > > 3. Spark is (slowly) moving away from INT96 > > > > > > > 4. our change is very narrow, backwards compatible and can > improve > > > > > > current > > > > > > > workloads while (3) is ongoing > > > > > > > > > > > > > > Let's discuss more at the sync tonight. > > > > > > > > > > > > > > > If we are going to standardize an ordering for INT96, rather > than > > > > > > parsing > > > > > > > "created_by" fields, wouldn't it make more sense to add a new > > > > > ColumnOrder > > > > > > > value (like what's proposed for PARQUET-2249 [1])? Then we > don't > > > need > > > > > to > > > > > > > maintain a list of known good writers. > > > > > > > > > > > > > > We do not have to add another ColumnOrder value since INT96 is > a > > > > > > *physical* > > > > > > > type and can only take timestamps in the specified format. > This was > > > > > > > arguably a design wart as it should have been a > > > > > FIXED_LEN_BYTE_ARRAY(12) > > > > > > > with logical type INT96_TIMESTAMP, for which a different > > > ColumnOrder > > > > > > would > > > > > > > make sense. In this case we are lucky this is a physical type > > > without > > > > > > > logical type attached because otherwise, we couldn't have made > this > > > > > > change > > > > > > > in a backwards compatible way as easily. > > > > > > > > > > > > > > On Sat, Jun 21, 2025 at 12:57 AM Ed Seidl <etse...@apache.org> > > > > wrote: > > > > > > > > > > > > > > > If we are going to standardize an ordering for INT96, rather > than > > > > > > parsing > > > > > > > > "created_by" fields, wouldn't it make more sense to add a new > > > > > > ColumnOrder > > > > > > > > value (like what's proposed for PARQUET-2249 [1])? Then we > don't > > > > need > > > > > > to > > > > > > > > maintain a list of known good writers. > > > > > > > > > > > > > > > > Ed > > > > > > > > > > > > > > > > [1] https://github.com/apache/parquet-format/pull/221 > > > > > > > > > > > > > > > > On 2025/06/19 10:15:13 Andrew Lamb wrote: > > > > > > > > > > While INT96 is now deprecated, it's still the default > > > timestamp > > > > > > type > > > > > > > in > > > > > > > > > > Spark, resulting in a significant amount of existing data > > > > written > > > > > > in > > > > > > > > this > > > > > > > > > > format. > > > > > > > > > > > > > > > > > > I agree with Gang and Antoine that the better solution is > to > > > > change > > > > > > > Spark > > > > > > > > > to write non deprecated parquet data types. > > > > > > > > > > > > > > > > > > It seems there is an issue in the Spark JIRA to do this[1] > but > > > > the > > > > > > only > > > > > > > > > feedback on the associated PR [2] is that it is a breaking > > > > change. > > > > > > > > > > > > > > > > > > If Spark is going to keep writing INT96 timestamps > > > indefinitely, > > > > I > > > > > > > > suggest > > > > > > > > > we un-deprecate the INT96 timestamps to reflect the > ecosystem > > > > > reality > > > > > > > > that > > > > > > > > > they will be here for a while rather than pretending they > are > > > > > really > > > > > > > > > deprecated. > > > > > > > > > > > > > > > > > > Andrew > > > > > > > > > > > > > > > > > > [1]: https://issues.apache.org/jira/browse/SPARK-51359 > > > > > > > > > [2]: > > > > > > > > https://github.com/apache/spark/pull/50215#issuecomment-2715147840 > > > > > > > > > > > > > > > > > > p.s. as an aside, is anyone from DataBricks pushing spark > to > > > > change > > > > > > > > > timestamp type? Or will the focus be to improve INT96 > > > timestamps > > > > > > > > instead? > > > > > > > > > > > > > > > > > > > > > > > > > > > On Wed, Jun 18, 2025 at 10:50 PM Gang Wu <ust...@gmail.com > > > > > > wrote: > > > > > > > > > > > > > > > > > > > It seems not adding too much value to improve a > deprecated > > > > > feature > > > > > > > > > > especially > > > > > > > > > > when there are abundant Parquet implementations in the > wild. > > > > > IIRC, > > > > > > > > > > parquet-java > > > > > > > > > > is planning to release 1.16.0 for new data types like > variant > > > > and > > > > > > > > geometry. > > > > > > > > > > It is > > > > > > > > > > also the last version to support Java 8. All deprecated > APIs > > > > > might > > > > > > > get > > > > > > > > > > removed > > > > > > > > > > from 2.0.0 so I'm not sure if older Spark versions are > able > > > to > > > > > > > > leverage the > > > > > > > > > > int96 > > > > > > > > > > stats. The right way to go is to push forward the > adoption of > > > > > > > timestamp > > > > > > > > > > logical > > > > > > > > > > types. > > > > > > > > > > > > > > > > > > > > Best, > > > > > > > > > > Gang > > > > > > > > > > > > > > > > > > > > On Thu, Jun 19, 2025 at 12:31 AM Micah Kornfield < > > > > > > > > emkornfi...@gmail.com> > > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > > > Hi Alkis, > > > > > > > > > > > Is this the right thread link? It seems to be a > discussion > > > > on > > > > > > > > Timestamp > > > > > > > > > > > Nano support (which IIUC won't use int96, but I'm not > sure > > > > this > > > > > > > > covers > > > > > > > > > > > changing the behavior for existing timestamps, which I > > > think > > > > > are > > > > > > at > > > > > > > > > > either > > > > > > > > > > > millisecond or microsecond granularity)? > > > > > > > > > > > > > > > > > > > > > > there will be customers that want to interface with > legacy > > > > > > systems > > > > > > > > > > > > with INT96. This is why we decided in doing both. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > It might help to elaborate on the time-frame here. > Since > > > it > > > > > > > appears > > > > > > > > > > > reference implementations of parquet are not currently > > > > writing > > > > > > > > > > statistics, > > > > > > > > > > > if we merge these changes when they will be picked up > in > > > > Spark? > > > > > > > > Would the > > > > > > > > > > > plan be to backport the parquet-java to older version > of > > > > Spark > > > > > > > > (otherwise > > > > > > > > > > > the legacy systems wouldn't really make use or emit > stats > > > > > > anyways)? > > > > > > > > What > > > > > > > > > > > is the delta between Spark picking up these changes and > > > > > > > > transitioning off > > > > > > > > > > > of Int96 by default? Is the expectation that even > once > > > the > > > > > > > default > > > > > > > > is > > > > > > > > > > > changed in spark to not use int96, there will be a > large > > > > number > > > > > > of > > > > > > > > users > > > > > > > > > > > that will override the default to write int96? > > > > > > > > > > > > > > > > > > > > > > Thanks, > > > > > > > > > > > Micah > > > > > > > > > > > > > > > > > > > > > > On Wed, Jun 18, 2025 at 1:35 AM Alkis Evlogimenos > > > > > > > > > > > <alkis.evlogime...@databricks.com.invalid> wrote: > > > > > > > > > > > > > > > > > > > > > > > We are also driving that in parallel: > > > > > > > > > > > > > > > > > > https://lists.apache.org/thread/y2vzrjl1499j5dvbpg3m81jxdhf4b6of > > > > > > > . > > > > > > > > > > > > > > > > > > > > > > > > Even when Spark defaults to INT64 there will be old > > > > versions > > > > > of > > > > > > > > Spark > > > > > > > > > > > > running, there will be customers that want to > interface > > > > with > > > > > > > legacy > > > > > > > > > > > systems > > > > > > > > > > > > with INT96. This is why we decided in doing both. > > > > > > > > > > > > > > > > > > > > > > > > On Wed, Jun 18, 2025 at 9:53 AM Antoine Pitrou < > > > > > > > anto...@python.org > > > > > > > > > > > > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Can we get Spark to stop emitting INT96? They are > not > > > > being > > > > > > an > > > > > > > > > > > > > extremely good community player here. > > > > > > > > > > > > > > > > > > > > > > > > > > Regards > > > > > > > > > > > > > > > > > > > > > > > > > > Antoine. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > On Fri, 13 Jun 2025 15:17:51 +0200 > > > > > > > > > > > > > Alkis Evlogimenos > > > > > > > > > > > > > <alkis.evlogime...@databricks.com.INVALID> > > > > > > > > > > > > > wrote: > > > > > > > > > > > > > > Hi folks, > > > > > > > > > > > > > > > > > > > > > > > > > > > > While INT96 is now deprecated, it's still the > default > > > > > > > timestamp > > > > > > > > > > type > > > > > > > > > > > in > > > > > > > > > > > > > > Spark, resulting in a significant amount of > existing > > > > data > > > > > > > > written > > > > > > > > > > in > > > > > > > > > > > > this > > > > > > > > > > > > > > format. > > > > > > > > > > > > > > > > > > > > > > > > > > > > Historically, parquet-mr/java has not emitted or > read > > > > > > > > statistics > > > > > > > > > > for > > > > > > > > > > > > > INT96. > > > > > > > > > > > > > > This was likely due to the fact that standard > byte > > > > > > comparison > > > > > > > > on > > > > > > > > > > the > > > > > > > > > > > > > INT96 > > > > > > > > > > > > > > representation doesn't align with logical > > > comparisons, > > > > > > > > potentially > > > > > > > > > > > > > leading > > > > > > > > > > > > > > to incorrect min/max values. This is unfortunate > > > > because > > > > > > > > timestamp > > > > > > > > > > > > > filters > > > > > > > > > > > > > > are extremely common and lack of stats limits > > > > > optimization > > > > > > > > > > > > opportunities. > > > > > > > > > > > > > > > > > > > > > > > > > > > > Since its inception Photon < > > > > > > > > > > > https://www.databricks.com/product/photon> > > > > > > > > > > > > > emitted > > > > > > > > > > > > > > and utilized INT96 statistics by employing a > logical > > > > > > > > comparator, > > > > > > > > > > > > ensuring > > > > > > > > > > > > > > their correctness. We have now implemented > > > > > > > > > > > > > > < > https://github.com/apache/parquet-java/pull/3243> > > > the > > > > > > same > > > > > > > > > > support > > > > > > > > > > > > > within > > > > > > > > > > > > > > parquet-java. > > > > > > > > > > > > > > > > > > > > > > > > > > > > We'd like to get the community's thoughts on this > > > > > addition. > > > > > > > We > > > > > > > > > > > > anticipate > > > > > > > > > > > > > > that most users may not be directly affected due > to > > > the > > > > > > > > declining > > > > > > > > > > use > > > > > > > > > > > > of > > > > > > > > > > > > > > INT96. However, we are interested in identifying > any > > > > > > > potential > > > > > > > > > > > > drawbacks > > > > > > > > > > > > > or > > > > > > > > > > > > > > unforeseen issues with this approach. > > > > > > > > > > > > > > > > > > > > > > > > > > > > Cheers > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
