There will be some support for Hive tables in 1.9. It will use the dfs plugin but not the Hive plugin. Support for the Hive plugin is planned for the future, but it is not committed at this time. There will be a ticket soon.
Thanks. --Robert On Thu, Nov 17, 2016 at 1:31 PM, Sonny Heer <[email protected]> wrote: > Ok thanks Rahul. Yeah we have to use the hive plugin I believe since we > don't control the sql generated. > > The reason I ask if its tracked is because you mentioned it was going to be > part of 1.9 ...? > > On Wed, Nov 16, 2016 at 11:26 AM, rahul challapalli < > [email protected]> wrote: > > > Assume you have a hive table "revenue" partitioned by year. Then the > folder > > structure for the table on maprfs/hdfs looks something like below > > > > > > *revenue* > > *|----year=2015* > > *|----year=2016* > > *|----year=2107* > > > > Now if you want to leverage partition pruning, you can use something like > > below > > Hive plugin : select count(*) from hive.revenue where `year` = 2015 > > DFS plugin : select count(*) from dfs.`/user/hive/warehouse/revenue` > where > > dir0='year=2015' > > > > I am not sure if we have a jira for tracking parquet filter pushdown when > > using hive + native parquet reader > > > > - Rahul > > > > On Wed, Nov 16, 2016 at 7:24 AM, Sonny Heer <[email protected]> wrote: > > > > > thats a lot of good information Rahul!! - thanks. > > > > > > "modify the query to take advantage of drill's directory based > > > partitioning" > > > > > > What does this entail? Do you have to tell it on which column the > > > directories are partitioned by? > > > > > > I think option 3 is probably the way to go. Is there a ticket tracking > > > work on this? > > > > > > Thanks again > > > > > > On Tue, Nov 15, 2016 at 10:25 AM, rahul challapalli < > > > [email protected]> wrote: > > > > > > > Robert's suggestion is with using the DFS plugin. If you directly use > > DFS > > > > instead of hive plugin then > > > > > > > > 1. DFS plugin has to determine the underlying data format on the fly. > > > > 2. DFS plugin does not know the schema in advance. But in the case > > > parquet > > > > drill would get this information from the parquet metadata. However > if > > > the > > > > hive table is backed by a csv file, then you cast the columns > > > appropriately > > > > in the query or create a view. > > > > 3. If the underlying hive table is partitioned, then drill does not > > know > > > > anything about partitions. However since hive partitions are just > > > > sub-directories, you can still modify the query to take advantage of > > > > drill's directory based partitioning > > > > 4. In terms of performance, I am not aware of any published > benchmarks > > > > comparing hive plugin and dfs plugin for parquet format. But from my > > > > general experience it appears as though DFS plugin is faster. > > > > > > > > Also do not forget the 3rd option in my first response (Hive Plugin + > > > Drill > > > > native parquet reader). We do have plans to support filter pushdown > for > > > > this scenario in the future. > > > > > > > > - Rahul > > > > > > > > On Tue, Nov 15, 2016 at 8:01 AM, Sonny Heer <[email protected]> > > wrote: > > > > > > > > > Thanks Robert. > > > > > > > > > > "You can then use Drill to query the Hive table and get predicate > > > > pushdown" > > > > > > > > > > This is using the DFS plugin and going directly to the hive table > > > folder? > > > > > > > > > > Can someone speak to what advantages there are to use the hive > plugin > > > vs > > > > > going directly to dfs > > > > > > > > > > On Tue, Nov 15, 2016 at 12:32 AM, Robert Hou <[email protected]> > > > wrote: > > > > > > > > > > > I have used Hive 1.2 and I have found that the stats in parquet > > files > > > > are > > > > > > populated for some data types. Integer, bigint, float, double, > > date > > > > > work. > > > > > > String does not seem to work. > > > > > > > > > > > > You can then use Drill to query the Hive table and get predicate > > > > pushdown > > > > > > for simple compare filters. This has the form "where col = > value". > > > > > Other > > > > > > standard operators are !=, <, <=, >, >=. Compound filters can > use > > > > > "and/or" > > > > > > logic. This will be supported in Drill 1.9. > > > > > > > > > > > > In the future, we will add expressions and functions. > > > > > > > > > > > > Thanks. > > > > > > > > > > > > --Robert > > > > > > > > > > > > > > > > > > On Mon, Nov 14, 2016 at 3:53 PM, Sonny Heer <[email protected] > > > > > > wrote: > > > > > > > > > > > > > Is there a way to do that during the creation of the parquet > > table? > > > > > > Might > > > > > > > be a hive question but all we do is 'STORED AS parquet' and > then > > > > during > > > > > > > insert set the parquet.* properties. I'm just trying to see if > > #2 > > > is > > > > > an > > > > > > > option for us to utilize filter pushdown via dfs > > > > > > > > > > > > > > On Mon, Nov 14, 2016 at 3:43 PM, rahul challapalli < > > > > > > > [email protected]> wrote: > > > > > > > > > > > > > > > I do not know of any plans to support filter pushdown when > > using > > > > the > > > > > > hive > > > > > > > > plugin. > > > > > > > > If you run analyze stats then hive computes the table stats > and > > > > > stores > > > > > > > them > > > > > > > > in the hive metastore for the relevant table. I believe drill > > > uses > > > > > some > > > > > > > of > > > > > > > > these stats. However running analyze stats command does not > > > > alter(or > > > > > > add) > > > > > > > > the metadata in the parquet files themselves. The parquet > level > > > > > > metadata > > > > > > > > should be written when the parquet file itself is created in > > the > > > > > first > > > > > > > > place. > > > > > > > > > > > > > > > > - Rahul > > > > > > > > > > > > > > > > On Mon, Nov 14, 2016 at 3:32 PM, Sonny Heer < > > [email protected] > > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > Rahul, > > > > > > > > > > > > > > > > > > Thanks for the details. Is there any plans to support > filter > > > > > > pushdown > > > > > > > > for > > > > > > > > > #1? Do you know if we run analyze stats through hive on a > > > > parquet > > > > > > file > > > > > > > > if > > > > > > > > > that will have enough info to do the pushdown? > > > > > > > > > > > > > > > > > > Thanks again. > > > > > > > > > > > > > > > > > > On Mon, Nov 14, 2016 at 9:50 AM, rahul challapalli < > > > > > > > > > [email protected]> wrote: > > > > > > > > > > > > > > > > > > > Sonny, > > > > > > > > > > > > > > > > > > > > If the underlying data in the hive table is in parquet > > > format, > > > > > > there > > > > > > > > are > > > > > > > > > 3 > > > > > > > > > > ways to query from drill : > > > > > > > > > > > > > > > > > > > > 1. Using the hive plugin : This does not support filter > > > > pushdown > > > > > > for > > > > > > > > any > > > > > > > > > > formats (ORC, Parquet, Text...etc) > > > > > > > > > > 2. Directly Querying the folder in maprfs/hdfs which > > contains > > > > the > > > > > > > > parquet > > > > > > > > > > files using DFS plugin: With DRILL-1950, we can now do a > > > filter > > > > > > > > pushdown > > > > > > > > > > into the parquet files. In order to take advantage of > this > > > > > feature, > > > > > > > the > > > > > > > > > > underlying parquet files should have the relevant stats. > > This > > > > > > feature > > > > > > > > > will > > > > > > > > > > only be available with the 1.9.0 release > > > > > > > > > > 3. Using the drill's native parquet reader in conjunction > > > with > > > > > the > > > > > > > hive > > > > > > > > > > plugin (See store.hive.optimize_scan_with_ > native_readers) > > : > > > > This > > > > > > > > allows > > > > > > > > > > drill to fetch all the metadata about the hive table from > > the > > > > > > > metastore > > > > > > > > > and > > > > > > > > > > then drill uses its own parquet reader for actually > reading > > > the > > > > > > > files. > > > > > > > > > This > > > > > > > > > > approach currently does not support parquet filter > pushdown > > > but > > > > > > this > > > > > > > > > might > > > > > > > > > > be added in the next release after 1.9.0. > > > > > > > > > > > > > > > > > > > > - Rahul > > > > > > > > > > > > > > > > > > > > On Sun, Nov 13, 2016 at 11:06 AM, Sonny Heer < > > > > > [email protected]> > > > > > > > > > wrote: > > > > > > > > > > > > > > > > > > > > > I'm running a drill query with a where clause on a > > > > > > non-partitioned > > > > > > > > > column > > > > > > > > > > > via hive storage plugin. This query inspects all > > > partitions > > > > > > (kind > > > > > > > of > > > > > > > > > > > expected), but when i run the same query in Hive I can > > see > > > a > > > > > > > > predicate > > > > > > > > > > > passed down to the query plan. This particular query > is > > > much > > > > > > > faster > > > > > > > > in > > > > > > > > > > > Hive vs Drill. BTW these are parquet files. > > > > > > > > > > > > > > > > > > > > > > Hive: > > > > > > > > > > > > > > > > > > > > > > Stage-0 > > > > > > > > > > > > > > > > > > > > > > Fetch Operator > > > > > > > > > > > > > > > > > > > > > > limit:-1 > > > > > > > > > > > > > > > > > > > > > > Select Operator [SEL_2] > > > > > > > > > > > > > > > > > > > > > > outputColumnNames:["_col0"] > > > > > > > > > > > > > > > > > > > > > > Filter Operator [FIL_4] > > > > > > > > > > > > > > > > > > > > > > predicate:(my_column = 123) (type: boolean) > > > > > > > > > > > > > > > > > > > > > > TableScan [TS_0] > > > > > > > > > > > > > > > > > > > > > > alias:my_table > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Any idea on why this is? My guess is Hive is storing > > hive > > > > > > specific > > > > > > > > > info > > > > > > > > > > in > > > > > > > > > > > the parquet file since it was created through Hive. > > > Although > > > > > it > > > > > > > > seems > > > > > > > > > > > drill-hive plugin should honor this to. Not sure, but > > > > willing > > > > > to > > > > > > > > look > > > > > > > > > > > through code if someone can point me in the right > > > direction. > > > > > > > Thanks! > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > > > > > > > > > > > > > > > > > > > Pushpinder S. Heer > > > > > > > > > Senior Software Engineer > > > > > > > > > m: 360-434-4354 h: 509-884-2574 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > > > > > > > > > > > > > Pushpinder S. Heer > > > > > > > Senior Software Engineer > > > > > > > m: 360-434-4354 h: 509-884-2574 > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > > > > > > > Pushpinder S. Heer > > > > > Senior Software Engineer > > > > > m: 360-434-4354 h: 509-884-2574 > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > > Pushpinder S. Heer > > > Senior Software Engineer > > > m: 360-434-4354 h: 509-884-2574 > > > > > > > > > -- > > > Pushpinder S. Heer > Senior Software Engineer > m: 360-434-4354 h: 509-884-2574 >
