8 ms·

Apache Drill's Future

132 points by bsg75 6y ago

srl 6y ago
For those interested, the relevant rules seem to be here: https://www.apache.org/foundation/voting.html https://www.apache.org/foundation/voting.html As far as I can tell, the implication is that there are now fewer than three people interested enough to participate in code reviews, and ASF rules require at least three +1 votes for basically anything to happen.
- rectang 6y ago
  That's basically the idea though the details are subtly different. What the ASF won't let you do if you can't muster the votes is actually make a release — that takes 3 votes from people on the Drill PMC (Project Management Committee). If you can't get 3 PMC votes, the project cannot even make security releases and must be retired. As to who can commit code, from the ASF's standpoint any person with commit rights can do so at any time. However, the project may impose additional constraints, such as requiring a code review.
  - gopalv 6y ago
    > As to who can commit code, from the ASF's standpoint any person with commit rights can do so at any time. However, the project may impose additional constraints, such as requiring a code review. Projects can amend their bylaws around this, but that also goes to the PMC - lazy consensus can apply, but yeah you can't go through the source release process without 3 binding votes. Eventually, you realize that this sort of software is not anybody's hobby project and takes real dollars to pay for development. Doesn't help that Dremio would profit from Drill collapsing and leaving that space open.
PaulHoule 6y ago
How many Apache projects are there in the "Big Data" space? It seems every time I look around I see a new one.
- chrisjc 6y ago
  49 according to the project list page. Some of which are in attic, some in incubation. https://projects.apache.org/projects.html?category#big-data https://projects.apache.org/projects.html?category#big-data Were you looking for a single project for all your big-data needs?
  - catawbasam 6y ago
    Looking for some continuity after those splashy Strata presentations.
    - TallGuyShort 6y ago
      Strata is very corporate. If you want what you see in Strata presentations, buy it from the vendors (Cloudera, Microsoft, etc.) What you see on apache.org is what gets put in presentations at say, the Hadoop Summit. edit: On a more helpful note, Apache Spark is probably as close as you can get to a single project for all your big data needs if that is what one wants out-of-the-box from an open-source project. It includes a SQL framework, streaming framework, either bundles or improves upon more general work done in Hadoop, etc. It can be pretty vendor-controlled at times, but it's birth was in academia, making it pretty different from the other projects that were mostly born as components in already established commercial platforms. There are pros and cons to that, of course.
  - _ZeD_ 6y ago
    > Were you looking for a single project for all your big-data needs? Isn't awk enough? :)
- moandcompany 6y ago
  It's why you need a Zookeeper ;)
dmix 6y ago
Some context Drill: https://en.wikipedia.org/wiki/Apache_Drill https://en.wikipedia.org/wiki/Apache_Drill MapR sold to Hewlett-Packard Enterprise (HPE): https://en.wikipedia.org/wiki/MapR https://en.wikipedia.org/wiki/MapR
timClicks 6y ago
I'm really impressed with the misson of Drill - write SQL for disparate data sources - but I've actually never installed it. When I have a bunch of parquet/csv/... files sitting around, I can normally slurp them in with pandas.
- cgivre 6y ago
  Try it out! I'd agree that if you have 1 CSV you don't need Drill. If you have more than one, is where it starts to get interesting. Also there is PyDrill which enables you to execute a Drill query and put the results directly into a pandas data frame. If you're an R person, there's Sergeant that does the same.
  - timClicks 6y ago
    Are you Charles Givre? I have your book!
    - cgivre 6y ago
      I am!! Glad to hear you liked the book!
chrisjc 6y ago
Sad to hear this since I've been following Drill for a while. From what I understand Drill was based on the google Dremel paper, hence the name. https://research.google/pubs/pub36632/ https://research.google/pubs/pub36632/ Wondering if maybe Spark REPL or Apache Zeppelin might be a decent replacement for Drill.
- rhacker 6y ago
  One thing I like about Spark is the number of data sources it supports, including its ability to write out to a table or whatever. If you want to set up a JDBC or ODBC server you can also access spark SQL : https://spark.apache.org/docs/latest/sql-distributed-sql-engine.html https://spark.apache.org/docs/latest/sql-distributed-sql-eng... From an analytics perspective, a lot of people like the ability to connect to a JDBC or ODBC source.
agacera 6y ago
Apache Drill is an interesting project, from all the MPP engines that appeared a few years ago, it was the most similar one to BigQuery (the first public version) and the most flexible. However, the competion was fierce and each Big Data vendor (MapR, Cloudera and HortonWorks) was pushing its own solution: Drill, Impala and Hive on Tez. Competion is always a good thing, but it fragmented the user base too much so no clear winner emerged. At the same time, Spark SQL got sufficiently better to replace these tools in most use cases and Presto (from Facebook) got the traction and the user base that none of these projects had by being vendor agnostic (and its adoption by AWS in Athena and EMR also helped boost its popularity).
- qeternity 6y ago
  I've not spent much time, but I've never exactly understood what Presto is. Is it just map reduce across databases?
  - WookieRushing 6y ago
    Its basically a compute engine that maintains all state in memory and does distributed computations similarly to Spark. The big thing it adds is that it isn't stuck to any storage format. It has a connector that lets you load data into it from basically anything, from mysql dbs to hdfs files to whatever. So you can do cross database joins and just not care about where the data lives. You can also output to almost any database too.
    - qeternity 6y ago
      Not being snarky, but is that basically a sql interface for map reduce across databases?
      - Boxxed 6y ago
        It's basically federated SQL. Nothing to do with map/reduce, really.
cube2222 6y ago
Sad to see this happen as I really like the idea! If you're interested in Drill, check out OctoSQL[0]. It shares the same vision of querying multiple datasources using pure SQL, and pushing down as much operations as possible to the underlying datasource. Moreover, there's been a huge rewrite under way this past year, ready to use on the master branch, yet unreleased however (will be available soon). It adds Kafka and Parquet support and most importantly first-class unbounded stream support. Including temporal SQL extensions for working with event time metadata (instead of system time) so you can use stuff like live updated time window aggregations on incoming kafka streams. It also now uses on-disk badger storage as the primary way to store its state, so you can do Group Bys / Joins with lots of keys, and restarts of OctoSQL won't alter the final result (exactly-once semantics). Make sure to check it out, it's also very simple to get going locally! Disclosure: I'm one of the main contributors. [0]:https://github.com/cube2222/octosql https://github.com/cube2222/octosql
- bsg75 6y ago
  Does OctoSQL support reading columnar compressed formats (ex. Parquet) from distributed storage (ex. S3) ?
  - cube2222 6y ago
    No, we don't support Excel, JSON, CSV and Parquet datasources other than local files yet, though that's definitely planned and would be very easy to add.
    - cgivre 6y ago
      Drill does ;-) Drill also has a streaming Excel reader that works very well with large Excel files...
- willvarfar 6y ago
  How does it compare to prestosql?
  - 6y ago
kkwteh 6y ago
I was thinking of using Apache Drill for converting CSVs to Parquet. What else do people use for that?
- mochomocha 6y ago
  pyarrow
- bsg75 6y ago
  Spark
  - falaki 6y ago
    Spark community put a lot of effort into a feature-rich CSV data source. Often times the most challenging part of ingesting CSV is parsing it. There are many flavors each with different corner cases for NULLs, comments, headers, etc.
- lurker458 6y ago
  I've also been looking for that. In an ideal world there would be a small, fast, standalone cli tool that can convert csv to parquet. There is a (sadly, unfinished) parquet writer Rust library in the Arrow repository that looks promising. All approaches I've tried so far (spark, pyarrow, drill, ...) require everything and the kitchen sink. So far I've settled on a java cli tool that uses jackson + org.apache.parquet internally, but it's cpu bound and has a huge amount of maven dependencies.
  - meritt 6y ago
    pandas + fastparquet fairly lightweight. but yes I would love to see a simple c++/golang binary that's just a simple csv2parq call.
    - MrPowers 6y ago
      Newer versions of Pandas don't even need fastparquet anymore. This code works: import pandas as pd df = pd.read_csv('data/us_presidents.csv') df.to_parquet('tmp/us_presidents.parquet')
vhold 6y ago
Please correct me if I have this wrong, but my vague understanding is that the data representation heart of Apache Drill lives on in the rather active Apache Arrow project. https://stackoverflow.com/questions/53533506/what-is-the-difference-between-apache-drills-valuevectors-and-apache-arrow https://stackoverflow.com/questions/53533506/what-is-the-dif... https://github.com/apache/arrow/commit/e6905effbb9383afd2423a4f86cf9a33ca680b9d https://github.com/apache/arrow/commit/e6905effbb9383afd2423... And the platform/tools side of Drill now lives on as Dremio, which uses Apache Arrow. https://github.com/dremio/dremio-oss https://github.com/dremio/dremio-oss So the essence of Drill still lives, but it became half Apache project and half vendor controlled and supported, and the root of that split is now orphaned.
bradhe 6y ago
I wonder how many apache projects actually survive this sort of event?
SrslyJosh 6y ago
Still waiting for Apache dril.
- cgivre 6y ago
  For what?
moandcompany 6y ago
This is unfortunate. For anyone curious about Apache Drill, it was inspired by Dremel which was used internally at Google and once the engine beneath GCP's BigQuery. https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36632.pdf https://static.googleusercontent.com/media/research.google.c... In the era of Hadoop, it was most closely aligned with the MapR distribution, while Hortonworks aligned with Hive, and Cloudera offered Impala as their solution. History of Apache Drill: http://radar.oreilly.com/2015/09/apache-drill-tracking-its-history-as-an-open-source-community.html http://radar.oreilly.com/2015/09/apache-drill-tracking-its-h...
- pulisse 6y ago
  > Dremel which was [...] once the engine beneath GCP's BigQuery Is there a white paper describing what replaced Dremel in BigQuery's architecture?
  - moandcompany 6y ago
    Clarification -- There's the Dremel paper, the Google-internal implementation, and BigQuery, a public-facing implementation that evolved from Dremel :) Here's some interesting reads on BigQuery: https://cloud.google.com/files/BigQueryTechnicalWP.pdf https://cloud.google.com/files/BigQueryTechnicalWP.pdf Also, Happy 10th Birthday, BigQuery! https://cloud.google.com/blog/products/data-analytics/bigquery-turns-10 https://cloud.google.com/blog/products/data-analytics/bigque...
josep2 6y ago
I really like Apache Drill. I used it about 4 years ago as an MPP SQL on Anything Engine. Presto took a lot of that momentum away and MapR failed to adapt to the new age kind of meant EOL for the project. I hope someone else picks it up.
jerdavis 6y ago
Just use bigquery.
greendisc7 6y ago
Check out Dremio. The interface and speed were awesome when I tested on some pretty large datasets.
cgivre 6y ago
As the author of the above post, I thought I'd respond to the comments below. Firstly, I'm glad to see that people noticed... :-) Firstly, to paraphrase Monty Python, "Drill's not dead yet." There are some efforts to get corporate sponsorship, but it will take time. HPE's withdrawal was expected, but disappointing none the less. With that said, we are still gearing up to release Drill 1.18 which will have a considerable amount of enhancements, including new formats (SPSS, HDF5, possibly SAS) as well as new storage plugins to enable Drill to connect to Druid as well as REST APIs. Personally, I've always felt that Drill was marketed to the wrong audience. As everyone notes, there are many competitors in the big data analytics space: Spark, ES, Splunk, Presto, Impala to name a few. Where I see Drill as filling a rather unique niche in the market is the small-to medium size data analytics with complex data. For instance, if you have a CSV file, you use Excel. If you have 100 CSVs you have to code. Or what if you have an Excel spreadsheet and you want to pull data from your corporate reference API, which happens to return JSON and uses OAUTH authentication? Drill is the kind of tool that can bridge this gap and allow analysts to rapidly get value out of these situations. As an example, here's a demo of me building a COVID dashboard from a REST API and spreadsheet in about 15 min with zero data prep: https://youtu.be/oEOhFWm3D9A https://youtu.be/oEOhFWm3D9A Another example: incident response. Let's say you have a PCAP file, use Wireshark. What if you have 10GB of PCAP files? Most likely you'll have to code up some solution. With Drill however, you can query that w/o coding, which means that you can get the value out of this data faster. I know there are people using Drill. I know when I demo Drill to analysts, they love it. (Ok.. I'm biased here but I would say that's an accurate representation of the response to my presentations) What Drill lost was an active developer community. I hope over the next few months, that Drill's users will step up a bit and contribute to code reviews and/or actual code contributions. I've been thinking about creating a security focused fork of Drill as well so we'll see what happens. If you have ideas/comments/questions, you can email me at cgivre@apache.org.
- swuecho 6y ago
  Your introduction is exactly how I feel about drill. However, the official doc is not as good as the book (Learning Apache Drill)

132 points by bsg75 6y ago

srl 6y ago

For those interested, the relevant rules seem to be here: https://www.apache.org/foundation/voting.html https://www.apache.org/foundation/voting.html As far as I can tell, the implication is that there are now fewer than three people interested enough to participate in code reviews, and ASF rules require at least three +1 votes for basically anything to happen.

rectang 6y ago
That's basically the idea though the details are subtly different. What the ASF won't let you do if you can't muster the votes is actually make a release — that takes 3 votes from people on the Drill PMC (Project Management Committee). If you can't get 3 PMC votes, the project cannot even make security releases and must be retired. As to who can commit code, from the ASF's standpoint any person with commit rights can do so at any time. However, the project may impose additional constraints, such as requiring a code review.
- gopalv 6y ago
  > As to who can commit code, from the ASF's standpoint any person with commit rights can do so at any time. However, the project may impose additional constraints, such as requiring a code review. Projects can amend their bylaws around this, but that also goes to the PMC - lazy consensus can apply, but yeah you can't go through the source release process without 3 binding votes. Eventually, you realize that this sort of software is not anybody's hobby project and takes real dollars to pay for development. Doesn't help that Dremio would profit from Drill collapsing and leaving that space open.

PaulHoule 6y ago

How many Apache projects are there in the "Big Data" space? It seems every time I look around I see a new one.

chrisjc 6y ago
49 according to the project list page. Some of which are in attic, some in incubation. https://projects.apache.org/projects.html?category#big-data https://projects.apache.org/projects.html?category#big-data Were you looking for a single project for all your big-data needs?
- catawbasam 6y ago
  Looking for some continuity after those splashy Strata presentations.
  - TallGuyShort 6y ago
    Strata is very corporate. If you want what you see in Strata presentations, buy it from the vendors (Cloudera, Microsoft, etc.) What you see on apache.org is what gets put in presentations at say, the Hadoop Summit. edit: On a more helpful note, Apache Spark is probably as close as you can get to a single project for all your big data needs if that is what one wants out-of-the-box from an open-source project. It includes a SQL framework, streaming framework, either bundles or improves upon more general work done in Hadoop, etc. It can be pretty vendor-controlled at times, but it's birth was in academia, making it pretty different from the other projects that were mostly born as components in already established commercial platforms. There are pros and cons to that, of course.
- _ZeD_ 6y ago
  > Were you looking for a single project for all your big-data needs? Isn't awk enough? :)
moandcompany 6y ago
It's why you need a Zookeeper ;)

dmix 6y ago

Some context Drill: https://en.wikipedia.org/wiki/Apache_Drill https://en.wikipedia.org/wiki/Apache_Drill MapR sold to Hewlett-Packard Enterprise (HPE): https://en.wikipedia.org/wiki/MapR https://en.wikipedia.org/wiki/MapR

timClicks 6y ago

I'm really impressed with the misson of Drill - write SQL for disparate data sources - but I've actually never installed it. When I have a bunch of parquet/csv/... files sitting around, I can normally slurp them in with pandas.

cgivre 6y ago
Try it out! I'd agree that if you have 1 CSV you don't need Drill. If you have more than one, is where it starts to get interesting. Also there is PyDrill which enables you to execute a Drill query and put the results directly into a pandas data frame. If you're an R person, there's Sergeant that does the same.
- timClicks 6y ago
  Are you Charles Givre? I have your book!
  - cgivre 6y ago
    I am!! Glad to hear you liked the book!

chrisjc 6y ago

Sad to hear this since I've been following Drill for a while. From what I understand Drill was based on the google Dremel paper, hence the name. https://research.google/pubs/pub36632/ https://research.google/pubs/pub36632/ Wondering if maybe Spark REPL or Apache Zeppelin might be a decent replacement for Drill.

rhacker 6y ago
One thing I like about Spark is the number of data sources it supports, including its ability to write out to a table or whatever. If you want to set up a JDBC or ODBC server you can also access spark SQL : https://spark.apache.org/docs/latest/sql-distributed-sql-engine.html https://spark.apache.org/docs/latest/sql-distributed-sql-eng... From an analytics perspective, a lot of people like the ability to connect to a JDBC or ODBC source.

agacera 6y ago

Apache Drill is an interesting project, from all the MPP engines that appeared a few years ago, it was the most similar one to BigQuery (the first public version) and the most flexible. However, the competion was fierce and each Big Data vendor (MapR, Cloudera and HortonWorks) was pushing its own solution: Drill, Impala and Hive on Tez. Competion is always a good thing, but it fragmented the user base too much so no clear winner emerged. At the same time, Spark SQL got sufficiently better to replace these tools in most use cases and Presto (from Facebook) got the traction and the user base that none of these projects had by being vendor agnostic (and its adoption by AWS in Athena and EMR also helped boost its popularity).

qeternity 6y ago
I've not spent much time, but I've never exactly understood what Presto is. Is it just map reduce across databases?
- WookieRushing 6y ago
  Its basically a compute engine that maintains all state in memory and does distributed computations similarly to Spark. The big thing it adds is that it isn't stuck to any storage format. It has a connector that lets you load data into it from basically anything, from mysql dbs to hdfs files to whatever. So you can do cross database joins and just not care about where the data lives. You can also output to almost any database too.
  - qeternity 6y ago
    Not being snarky, but is that basically a sql interface for map reduce across databases?
    - Boxxed 6y ago
      It's basically federated SQL. Nothing to do with map/reduce, really.

cube2222 6y ago

Sad to see this happen as I really like the idea! If you're interested in Drill, check out OctoSQL[0]. It shares the same vision of querying multiple datasources using pure SQL, and pushing down as much operations as possible to the underlying datasource. Moreover, there's been a huge rewrite under way this past year, ready to use on the master branch, yet unreleased however (will be available soon). It adds Kafka and Parquet support and most importantly first-class unbounded stream support. Including temporal SQL extensions for working with event time metadata (instead of system time) so you can use stuff like live updated time window aggregations on incoming kafka streams. It also now uses on-disk badger storage as the primary way to store its state, so you can do Group Bys / Joins with lots of keys, and restarts of OctoSQL won't alter the final result (exactly-once semantics). Make sure to check it out, it's also very simple to get going locally! Disclosure: I'm one of the main contributors. [0]:https://github.com/cube2222/octosql https://github.com/cube2222/octosql

bsg75 6y ago
Does OctoSQL support reading columnar compressed formats (ex. Parquet) from distributed storage (ex. S3) ?
- cube2222 6y ago
  No, we don't support Excel, JSON, CSV and Parquet datasources other than local files yet, though that's definitely planned and would be very easy to add.
  - cgivre 6y ago
    Drill does ;-) Drill also has a streaming Excel reader that works very well with large Excel files...
willvarfar 6y ago
How does it compare to prestosql?
- 6y ago

kkwteh 6y ago

I was thinking of using Apache Drill for converting CSVs to Parquet. What else do people use for that?

mochomocha 6y ago
pyarrow
bsg75 6y ago
Spark
- falaki 6y ago
  Spark community put a lot of effort into a feature-rich CSV data source. Often times the most challenging part of ingesting CSV is parsing it. There are many flavors each with different corner cases for NULLs, comments, headers, etc.
lurker458 6y ago
I've also been looking for that. In an ideal world there would be a small, fast, standalone cli tool that can convert csv to parquet. There is a (sadly, unfinished) parquet writer Rust library in the Arrow repository that looks promising. All approaches I've tried so far (spark, pyarrow, drill, ...) require everything and the kitchen sink. So far I've settled on a java cli tool that uses jackson + org.apache.parquet internally, but it's cpu bound and has a huge amount of maven dependencies.
- meritt 6y ago
  pandas + fastparquet fairly lightweight. but yes I would love to see a simple c++/golang binary that's just a simple csv2parq call.
  - MrPowers 6y ago
    Newer versions of Pandas don't even need fastparquet anymore. This code works: import pandas as pd df = pd.read_csv('data/us_presidents.csv') df.to_parquet('tmp/us_presidents.parquet')

vhold 6y ago

Please correct me if I have this wrong, but my vague understanding is that the data representation heart of Apache Drill lives on in the rather active Apache Arrow project. https://stackoverflow.com/questions/53533506/what-is-the-difference-between-apache-drills-valuevectors-and-apache-arrow https://stackoverflow.com/questions/53533506/what-is-the-dif... https://github.com/apache/arrow/commit/e6905effbb9383afd2423a4f86cf9a33ca680b9d https://github.com/apache/arrow/commit/e6905effbb9383afd2423... And the platform/tools side of Drill now lives on as Dremio, which uses Apache Arrow. https://github.com/dremio/dremio-oss https://github.com/dremio/dremio-oss So the essence of Drill still lives, but it became half Apache project and half vendor controlled and supported, and the root of that split is now orphaned.

bradhe 6y ago

I wonder how many apache projects actually survive this sort of event?

SrslyJosh 6y ago

Still waiting for Apache dril.

cgivre 6y ago
For what?

moandcompany 6y ago

This is unfortunate. For anyone curious about Apache Drill, it was inspired by Dremel which was used internally at Google and once the engine beneath GCP's BigQuery. https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/36632.pdf https://static.googleusercontent.com/media/research.google.c... In the era of Hadoop, it was most closely aligned with the MapR distribution, while Hortonworks aligned with Hive, and Cloudera offered Impala as their solution. History of Apache Drill: http://radar.oreilly.com/2015/09/apache-drill-tracking-its-history-as-an-open-source-community.html http://radar.oreilly.com/2015/09/apache-drill-tracking-its-h...

pulisse 6y ago
> Dremel which was [...] once the engine beneath GCP's BigQuery Is there a white paper describing what replaced Dremel in BigQuery's architecture?
- moandcompany 6y ago
  Clarification -- There's the Dremel paper, the Google-internal implementation, and BigQuery, a public-facing implementation that evolved from Dremel :) Here's some interesting reads on BigQuery: https://cloud.google.com/files/BigQueryTechnicalWP.pdf https://cloud.google.com/files/BigQueryTechnicalWP.pdf Also, Happy 10th Birthday, BigQuery! https://cloud.google.com/blog/products/data-analytics/bigquery-turns-10 https://cloud.google.com/blog/products/data-analytics/bigque...

josep2 6y ago

I really like Apache Drill. I used it about 4 years ago as an MPP SQL on Anything Engine. Presto took a lot of that momentum away and MapR failed to adapt to the new age kind of meant EOL for the project. I hope someone else picks it up.

jerdavis 6y ago

Just use bigquery.

greendisc7 6y ago

Check out Dremio. The interface and speed were awesome when I tested on some pretty large datasets.

cgivre 6y ago

As the author of the above post, I thought I'd respond to the comments below. Firstly, I'm glad to see that people noticed... :-) Firstly, to paraphrase Monty Python, "Drill's not dead yet." There are some efforts to get corporate sponsorship, but it will take time. HPE's withdrawal was expected, but disappointing none the less. With that said, we are still gearing up to release Drill 1.18 which will have a considerable amount of enhancements, including new formats (SPSS, HDF5, possibly SAS) as well as new storage plugins to enable Drill to connect to Druid as well as REST APIs. Personally, I've always felt that Drill was marketed to the wrong audience. As everyone notes, there are many competitors in the big data analytics space: Spark, ES, Splunk, Presto, Impala to name a few. Where I see Drill as filling a rather unique niche in the market is the small-to medium size data analytics with complex data. For instance, if you have a CSV file, you use Excel. If you have 100 CSVs you have to code. Or what if you have an Excel spreadsheet and you want to pull data from your corporate reference API, which happens to return JSON and uses OAUTH authentication? Drill is the kind of tool that can bridge this gap and allow analysts to rapidly get value out of these situations. As an example, here's a demo of me building a COVID dashboard from a REST API and spreadsheet in about 15 min with zero data prep: https://youtu.be/oEOhFWm3D9A https://youtu.be/oEOhFWm3D9A Another example: incident response. Let's say you have a PCAP file, use Wireshark. What if you have 10GB of PCAP files? Most likely you'll have to code up some solution. With Drill however, you can query that w/o coding, which means that you can get the value out of this data faster. I know there are people using Drill. I know when I demo Drill to analysts, they love it. (Ok.. I'm biased here but I would say that's an accurate representation of the response to my presentations) What Drill lost was an active developer community. I hope over the next few months, that Drill's users will step up a bit and contribute to code reviews and/or actual code contributions. I've been thinking about creating a security focused fork of Drill as well so we'll see what happens. If you have ideas/comments/questions, you can email me at cgivre@apache.org.

swuecho 6y ago
Your introduction is exactly how I feel about drill. However, the official doc is not as good as the book (Learning Apache Drill)