Again there's inconsistency with Hive: the presence of a single Avro partition doesn't change the table-level schema.
The interesting thing is that, when I modified Impala to have a similar behavior, I got the following error from the backend when trying to query the data: WARNINGS: Unresolvable types for column 'tinyint_col': declared column type: TINYINT, table's Avro schema type: int (1 of 2 similar) Hive, however, when presented with such a situation, does an incorrect type coercion of the avro file's "int" into the table's "tinyint" schema. What's incorrect about the type coercion is that it doesn't handle out-of-range values in a sensible way. Rather, it just lets them overflow into the smaller target type -- when I dumped an Avro file containing the int "10000" into an Avro partition of a Parquet table with schema "tinyint", I got the value "16" output from Hive (10000%256=16). This downcasting behavior is consistent with Impala and Hive's behavior with a CAST(10000 as tinyint) expression (see IMPALA-1821) So, I think my proposal here is: 1. Query behavior on existing tables - If the table-level format is non-Avro, - AND the table contains column types incompatible with Avro (eg tinyint), - AND the table has an existing avro partition, - THEN the query will yield an error about incompatible types 2. Try to prevent shooting in the foot - If the table-level format is non-Avro, - AND the table contains column types incompatible with Avro (eg tinyint), - THEN disallow changing the file format of an existing partition to Avro -Todd On Wed, Jul 11, 2018 at 9:32 PM, Todd Lipcon <t...@cloudera.com> wrote: > Turns out it's even a bit more messy. The presence of one or more avro > partitions can change the types of existing columns, even if there is no > explicit avro schema specified for the table: > https://gist.github.com/5018d6ff50f846c72762319eb7cf5ca8 > > Not quite sure how to handle this one in a world where we don't load all > of the partitions up front. Perhaps the best approach is to just throw an > error and then provide a command for the user to "re-sync" the schema to > the appropriate avro-supported types? Hive provides ALTER TABLE <foo> > UPDATE COLUMNS for something like this, though still I don't think that > would iterate over all partitions in the case of a mixed table. > > -Todd > > On Wed, Jul 11, 2018 at 9:03 PM, Bharath Vissapragada < > bhara...@cloudera.com.invalid> wrote: > >> Agreed. >> >> On Wed, Jul 11, 2018 at 8:55 PM Todd Lipcon <t...@cloudera.com.invalid> >> wrote: >> >> > Your commit message there makes sense, Bharath -- we should set >> > 'avroSchema' in the descriptor in case any referenced partition is avro, >> > because the scanner needs that info. However, we don't need to also >> > override the table-level schema. So, I think we can preserve the fix >> that >> > you made while also making the behavior less surprising. >> > >> > -Todd >> > >> > On Wed, Jul 11, 2018 at 8:21 PM, Bharath Vissapragada < >> > bhara...@cloudera.com.invalid> wrote: >> > >> > > I added this functionality >> > > <https://github.com/apache/impala/commit/49610e2cfa40aa10b62 >> 6c5ae41d7f0 >> > > d99d7cabc5> >> > > where adding an Avro partition in a mixed partition table resets the >> > table >> > > level schema. While I don't exactly remember why we chose this path, >> I do >> > > recall that we debated quite a bit about Avro schema evolution causing >> > > schema inconsistencies across partitions. AFAICT there is no specific >> > > reason Impala chose to different from Hive. Now that I see your email, >> > > Hive's behavior makes more sense to me, especially in the context of >> lazy >> > > loading of metadata. >> > > >> > > Also, agree with Edward that the whole mixed partitions + Avro schema >> > > evolution is a mess and I doubt if any serious user relies on a >> specific >> > > behavior. >> > > >> > > On Wed, Jul 11, 2018 at 7:48 PM Edward Capriolo < >> edlinuxg...@gmail.com> >> > > wrote: >> > > >> > > > I know that Hive can deal with schema being different per partition, >> > but >> > > I >> > > > really hesitate to understand why someone would want to do this. If >> > > someone >> > > > asked me to support a mixed avro/parquet table I would suggest they >> > > create >> > > > a view. If they kept insisting I would reply "Well it is your >> funeral." >> > > > >> > > > On Wed, Jul 11, 2018 at 7:51 PM, Todd Lipcon >> <t...@cloudera.com.invalid >> > > >> > > > wrote: >> > > > >> > > > > Hey folks, >> > > > > >> > > > > I'm trying to understand the current behavior of tables that >> contain >> > > > > partitions of mixed format, specifically when one or more >> partitions >> > is >> > > > > stored as Avro. Impala seems to be doing a number of things which >> I >> > > find >> > > > > surprising, and I'm not sure if they are intentional or should be >> > > > > considered bugs. >> > > > > >> > > > > *Surprise 1*: the _presence_ of an Avro-formatted partition can >> > change >> > > > the >> > > > > table schema >> > > > > https://gist.github.com/74bdef8a69b558763e4453ac21313649 >> > > > > >> > > > > - create a table that is Parquet-formatted, but with an >> > > 'avro.schema.url' >> > > > > property >> > > > > - the Avro schema is ignored, and we see whatever schema we >> specified >> > > > > (*makes >> > > > > sense, because the table is Parquet)* >> > > > > - add an partition >> > > > > - set the new partition's format to Avro >> > > > > - refresh the table >> > > > > - the schema for the table now reflects the Avro schema, because >> it >> > has >> > > > at >> > > > > least one Avro partition >> > > > > >> > > > > *Surprise 2*: the above is inconsistent with Hive and Spark >> > > > > >> > > > > Hive seems to still reflect the table-level defined schema, and >> > ignore >> > > > the >> > > > > avro.schema.url property in this mixed scenario. That is to say, >> with >> > > the >> > > > > state set up by the above, we have the following behavior: >> > > > > >> > > > > Impala: >> > > > > - uses the external avro schema for all table-level info, SELECT >> *, >> > > etc. >> > > > > - "compute stats" detects the inconsistency and tells the user to >> > > > recreate >> > > > > the table. >> > > > > - if some existing partitions (eg in Parquet) aren't compatible >> with >> > > that >> > > > > avro schema, errors result from the backend that there are missing >> > > > columns >> > > > > in the Parquet data files >> > > > > >> > > > > Hive: >> > > > > - uses the table-level schema defined in the HMS for describe, etc >> > > > > - queries like 'select *' again use the table-level HMS schema. >> The >> > > > > underlying reader that reads the Avro partition seems to use the >> > > defined >> > > > > external Avro schema, resulting in nulls for missing columns. >> > > > > - computing stats (analyze table mixedtable partition (y=1) >> compute >> > > stats >> > > > > for columns) seems to end up only recording stats against the >> column >> > > > > defined in the table-level Schema. >> > > > > >> > > > > Spark: >> > > > > - DESCRIBE TABLE shows the table-level info >> > > > > - select * fails, because apparently Spark doesn't support >> > multi-format >> > > > > tables at all (it tries to read the avro files as a parquet file) >> > > > > >> > > > > >> > > > > It seems to me that Hive's behavior is a bit better.* I'd like to >> > > propose >> > > > > we treat this as a bug and move to the following behavior:* >> > > > > >> > > > > - if a table's properties indicate it's an avro table, parse and >> > adopt >> > > > the >> > > > > external avro schema as the table schema >> > > > > - if a table's properties indicate it's _not_ an avro table, but >> > there >> > > is >> > > > > an external avro schema defined in the table properties, then >> parse >> > the >> > > > > avro schema and include it in the TableDescriptor (for use by avro >> > > > > partitions) but do not adopt it as the table schema. >> > > > > >> > > > > The added benefit of the above proposal (and the reason why I >> started >> > > > > looking into this in the first place) is that, in order to >> service a >> > > > simple >> > > > > query like DESCRIBE, our current behavior requires all partition >> > > metadata >> > > > > to be loaded to know whether there is any avro-formatted >> partition. >> > > With >> > > > > the proposed new behavior, we can avoid looking at all partitions. >> > This >> > > > is >> > > > > important for any metadata design which supports fine-grained >> loading >> > > of >> > > > > metadata to the coordinator. >> > > > > >> > > > > -Todd >> > > > > -- >> > > > > Todd Lipcon >> > > > > Software Engineer, Cloudera >> > > > > >> > > > >> > > >> > >> > >> > >> > -- >> > Todd Lipcon >> > Software Engineer, Cloudera >> > >> > > > > -- > Todd Lipcon > Software Engineer, Cloudera > -- Todd Lipcon Software Engineer, Cloudera