John,

What happens when you partition the data using drill in the same pattern as
Hive uses?  Are the Drill produced parquet files still faster?



On Mon, Sep 7, 2015 at 1:02 PM, John Omernik <[email protected]> wrote:

> So interestingly enough, this particular table doesn't have 4k files in it,
> it's actually pretty small, in that there is only 1 file per partition.
>  (tiny?)  Thus there are only 162 files vs. the 30 that drill created when
> reprocessing the table. That probably doesn't help either given that this
> is such small data, the planning takes more time than query.  It's cool
> that the team is looking to improve this, I found the ability to just have
> my data in Parquet partitioned by drill to be a huge win as well.  The
> enhancements sound like they will enhance this even more, I would love to
> see as close to native drill loaded parquet performance as possible with
> Hive loaded tables, that would allow us to use drill to query, and hive to
> load. (Using complex transforms, longer running queries etc).
>
> I love drill :)
>
>
>
> On Mon, Sep 7, 2015 at 2:23 PM, Aman Sinha <[email protected]> wrote:
>
> > Hi John,
> > the partition pruning *planning* time is indeed a function of the number
> of
> > files in the table. The execution time is only dependent on the number of
> > files in the specified partition.   In the Drill loaded Parquet files you
> > had 30 files whereas in the Hive loaded parquet files you probably had
> 162
> > directories x 24 hours = about 4000 files  ? or somewhere in that
> range...
> >
> > During the query planning phase, Drill partition pruning will load the
> full
> > pathnames of the files in memory, including materializing the
> partitioning
> > columns such as 'day'  into memory and apply the `day` >= '2015-01-01`
> > filter.  It turns out this process is expensive when there are lots of
> > files even if they are spread out over multiple directories.   I believe
> > there's an enhancement JIRA to make this process efficient by loading
> only
> > directory names first and then the files...if not, I will create a JIRA.
> >
> > Note that partition pruning is still a huge win for more complex queries
> > when the total execution time is substantially longer than the planning
> > time.  It is only for shorter running queries against large number of
> files
> > where the planning times becomes more dominant.  There is ongoing effort
> to
> > improve that.
> >
> > Aman
> >
> >
> > On Mon, Sep 7, 2015 at 10:15 AM, John Omernik <[email protected]> wrote:
> >
> > > As a follow-up to Jacques email, I did some testing with Parquet files
> > > created and partitioned by Apache Hive. (Not using the metastore to
> read
> > > these files, just using the directories and reading the Parquet files
> > > directly).
> > >
> > > Consider that Hive's partition scheme makes directories that have
> > > partitionfield=partitionvalue as the directory name like this:
> > >
> > >
> > > table
> > > ---day=2015-09-06
> > > -------hour=00
> > > -------hour=01
> > > -------hour=02
> > > ---day=2015-09-07
> > > -------hour=00
> > > -------hour=01
> > > -------hour=02
> > >
> > >
> > > Basically in this case, to use hives partition directory scheme (with
> > > parquet and without the metastore)  you would have to write queries
> such
> > > as:
> > >
> > > select * from table where dir0 >= 'day=2015-09-06' and dir1 = 'hour=01'
> > >
> > > or
> > >
> > > select * from table where dir0 = 'day=2015-09-06' and dir1 < 'hour=03'
> > >
> > > These are "doable" but are prone to user errors (what happens they put
> a
> > > space between hour, =, and the hour) are non intuitive (likes become
> more
> > > complicated)  etc.
> > >
> > >
> > > So what I did was use the regexp_replace function in Drill to create a
> > view
> > > that instead of using dir0 or dir1 directly, I could just work with the
> > > "name" and the value... like this
> > >
> > > regexp_replace(dir0, 'day=', '') as `day`, regexp_replace(dir1,
> 'hour=',
> > > '') as `hour`
> > >
> > > That allowed me to use the Hive directories easily and intuitively,
> > without
> > > changing the directories.
> > >
> > > I will say that performance wasn't great compared to natively loaded
> > (drill
> > > loaded) parquet files.
> > >
> > > For example, where I did one query on the hive data that was:
> > >
> > > select count(1)  from table where day >= '2015-01-01' using the hive
> > loaded
> > > tables with drill and the drill view it took 26 seconds
> > >
> > > When I loaded the whole table into a new parquet (from the hive view)
> > table
> > > in drill, and specified partition by `day`, `hour` the same query ran
> in
> > > 1.08 seconds.  Not sure why this is, perhaps there is more work the
> drill
> > > engine has to do, perhaps Hive isn't writing parquet file stats well,
> > > perhaps just more IO in that with the drill created table, there was 30
> > > files created, in the hive table there was at least 162 unique
> partitions
> > > (not even counting files) given the directory structure.  Another
> example
> > > of performance difference:
> > >
> > > select `day`, `hour` from drill_parquet_table where `day` >=
> > '2015-01-01`:
> > > 162 rows in 1.6 seconds
> > >
> > > select `day`, `hour` from hive_parquet_table where `day` >=
> '2015-01-01`:
> > > 162 rows in 27.2 seconds
> > >
> > > Interesting stuff, but the regex_replace does give partition pruning
> > based
> > > on testing. I.e. on the hive table, select count(1) from hivetable
> where
> > > `day` >= '2015-01-01'  runs much faster than select count(1) from
> > hivetable
> > > where `day` >= '2014-01-01' indicating to me that is indeed not reading
> > the
> > > directories that were older than 2015-01-01 on the >= '2015-01-01'
> query.
> > >
> > > * Note my observations are that of a drill rookie, so if drill experts
> > have
> > > any thoughts on what I wrote about my observations, I'd happily
> defer.  I
> > > would be interested in a drill expert commenting on the speed of the
> > Drill
> > > loaded Parquet files vs Hive Loaded Parquet files, and if there is
> > > something I can do make Hive loaded parquet less  doggy comparatively,
> or
> > > if that is just a function of more files to read.
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > > On Fri, Sep 4, 2015 at 4:48 PM, Jacques Nadeau <[email protected]>
> > wrote:
> > >
> > > > You can create a view that renames the columns to whatever you like.
> > For
> > > > example:
> > > >
> > > > CREATE VIEW mydata AS SELECT dir0 as "year", dir1 as "month", dir2 as
> > > > "day", dir3 as "hour", a, b, ..., z FROM
> `/warehouse/database/table/`
> > > >
> > > > Then you can query: select * from mydata where year = 2012
> > > >
> > > > --
> > > > Jacques Nadeau
> > > > CTO and Co-Founder, Dremio
> > > >
> > > > On Fri, Sep 4, 2015 at 2:35 PM, Grant Overby (groverby) <
> > > > [email protected]>
> > > > wrote:
> > > >
> > > > > I’m using parquet files in hdfs. My files are stored thusly:
> > > > >
> > > > > /warehouse/database/table/field0/field1/field2/field3/fileX.parquet
> > > > >
> > > > > I’d like to give a name to field0..3 that could be used in queries
> in
> > > > > stead of dir0, dir1, dir2, dir3. Is this possible?
> > > > > [
> > > > >
> > > >
> > >
> >
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> > > > >
> > > > > Grant Overby
> > > > > Software Engineer
> > > > > Cisco.com<http://www.cisco.com/>
> > > > > [email protected]<mailto:[email protected]>
> > > > > Mobile: 865 724 4910
> > > > >
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