Reynold, my point is that Spark should aim to follow the SQL standard instead of rolling its own type system. If I understand correctly, the existing implementation is similar to TIMESTAMP WITH LOCAL TIMEZONE data type in Oracle.. In addition, there are the standard TIMESTAMP and TIMESTAMP WITH TIMEZONE data types which are missing from Spark. So, it is better (for me) if instead of extending the existing types, Spark would just implement the additional well-defined types properly. Just trying to copy-paste CREATE TABLE between SQL engines should not be an exercise of flags and incompatibilities.
Regarding the current behaviour, if I remember correctly I had to force our spark O/S user into UTC so Spark wont change my timestamps. Ofir Manor Co-Founder & CTO | Equalum Mobile: +972-54-7801286 | Email: ofir.ma...@equalum.io On Thu, May 25, 2017 at 1:33 PM, Reynold Xin <r...@databricks.com> wrote: > Zoltan, > > Thanks for raising this again, although I'm a bit confused since I've > communicated with you a few times on JIRA and on private emails to explain > that you have some misunderstanding of the timestamp type in Spark and some > of your statements are wrong (e.g. the except text file part). Not sure why > you didn't get any of those. > > > Here's another try: > > > 1. I think you guys misunderstood the semantics of timestamp in Spark > before session local timezone change. IIUC, Spark has always assumed > timestamps to be with timezone, since it parses timestamps with timezone > and does all the datetime conversions with timezone in mind (it doesn't > ignore timezone if a timestamp string has timezone specified). The session > local timezone change further pushes Spark to that direction, but the > semantics has been with timezone before that change. Just run Spark on > machines with different timezone and you will know what I'm talking about. > > 2. CSV/Text is not different. The data type has always been "with > timezone". If you put a timezone in the timestamp string, it parses the > timezone. > > 3. We can't change semantics now, because it'd break all existing Spark > apps. > > 4. We can however introduce a new timestamp without timezone type, and > have a config flag to specify which one (with tz or without tz) is the > default behavior. > > > > On Wed, May 24, 2017 at 5:46 PM, Zoltan Ivanfi <z...@cloudera.com> wrote: > >> Hi, >> >> Sorry if you receive this mail twice, it seems that my first attempt did >> not make it to the list for some reason. >> >> I would like to start a discussion about SPARK-18350 >> <https://issues.apache.org/jira/browse/SPARK-18350> before it gets >> released because it seems to be going in a different direction than what >> other SQL engines of the Hadoop stack do. >> >> ANSI SQL defines the TIMESTAMP type (also known as TIMESTAMP WITHOUT TIME >> ZONE) to have timezone-agnostic semantics - basically a type that expresses >> readings from calendars and clocks and is unaffected by time zone. In the >> Hadoop stack, Impala has always worked like this and recently Presto also >> took steps <https://github.com/prestodb/presto/issues/7122> to become >> standards compliant. (Presto's design doc >> <https://docs.google.com/document/d/1UUDktZDx8fGwHZV4VyaEDQURorFbbg6ioeZ5KMHwoCk/edit> >> also contains a great summary of the different semantics.) Hive has a >> timezone-agnostic TIMESTAMP type as well (except for Parquet, a major >> source of incompatibility that is already being addressed >> <https://issues.apache.org/jira/browse/HIVE-12767>). A TIMESTAMP in >> SparkSQL, however, has UTC-normalized local time semantics (except for >> textfile), which is generally the semantics of the TIMESTAMP WITH TIME ZONE >> type. >> >> Given that timezone-agnostic TIMESTAMP semantics provide standards >> compliance and consistency with most SQL engines, I was wondering whether >> SparkSQL should also consider it in order to become ANSI SQL compliant and >> interoperable with other SQL engines of the Hadoop stack. Should SparkSQL >> adapt this semantics in the future, SPARK-18350 >> <https://issues.apache.org/jira/browse/SPARK-18350> may turn out to be a >> source of problems. Please correct me if I'm wrong, but this change seems >> to explicitly assign TIMESTAMP WITH TIME ZONE semantics to the TIMESTAMP >> type. I think SPARK-18350 would be a great feature for a separate TIMESTAMP >> WITH TIME ZONE type, but the plain unqualified TIMESTAMP type would be >> better becoming timezone-agnostic instead of gaining further timezone-aware >> capabilities. (Of course becoming timezone-agnostic would be a behavior >> change, so it must be optional and configurable by the user, as in Presto.) >> >> I would like to hear your opinions about this concern and about TIMESTAMP >> semantics in general. Does the community agree that a standards-compliant >> and interoperable TIMESTAMP type is desired? Do you perceive SPARK-18350 as >> a potential problem in achieving this or do I misunderstand the effects of >> this change? >> >> Thanks, >> >> Zoltan >> >> --- >> >> List of links in case in-line links do not work: >> >> - >> >> SPARK-18350: https://issues.apache.org/jira/browse/SPARK-18350 >> - >> >> Presto's change: https://github.com/prestodb/presto/issues/7122 >> - >> >> Presto's design doc: https://docs.google.com/docume >> nt/d/1UUDktZDx8fGwHZV4VyaEDQURorFbbg6ioeZ5KMHwoCk/edit >> >> <https://docs.google.com/document/d/1UUDktZDx8fGwHZV4VyaEDQURorFbbg6ioeZ5KMHwoCk/edit> >> >> >> >
