💂 Tools to Transform and Query Data with 'Apache' 'Drill'
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💂 sergeant

Tools to Transform and Query Data with ‘Apache’ ‘Drill’

** IMPORTANT **

Version 0.7.0 splits off the JDBC interface into a separate package sergeant.caffeinated (sr.ht; (GitLab; GitHub).

If you want to try all the new features coming in 0.8.0 please install from the 0.8.0 branch via:

# sr.ht
devtools::install_git("https://git.sr.ht/~hrbrmstr/sergeant", ref="0.8.0")

# GitLab
devtools::install_git("https://gitlab.com/hrbrmstr/sergeant", ref="0.8.0")

# GitHub
devtools::install_git("https://github.com/hrbrmstr/sergeant", ref="0.8.0")

Description

Drill + sergeant is (IMO) a streamlined alternative to Spark + sparklyr if you don’t need the ML components of Spark (i.e. just need to query “big data” sources, need to interface with parquet, need to combine disparate data source types — json, csv, parquet, rdbms - for aggregation, etc). Drill also has support for spatial queries.

Using Drill SQL queries that reference parquet files on a local linux or macOS workstation can often be more performant than doing the same data ingestion & wrangling work with R (especially for large or disperate data sets). Drill can often help further streaming workflows that infolve wrangling many tiny JSON files on a daily basis.

Drill can be obtained from https://drill.apache.org/download/ (use “Direct File Download”). Drill can also be installed via Docker. For local installs on Unix-like systems, a common/suggestion location for the Drill directory is /usr/local/drill as the install directory.

Drill embedded (started using the $DRILL_BASE_DIR/bin/drill-embedded script) is a super-easy way to get started playing with Drill on a single workstation and most of many workflows can “get by” using Drill this way.

There are a few convenience wrappers for various informational SQL queries (like drill_version()). Please file an PR if you add more.

Some of the more “controlling vs data ops” REST API functions aren’t implemented. Please file a PR if you need those.

The following functions are implemented:

DBI (REST)

  • A “just enough” feature complete R DBI driver has been implemented using the Drill REST API, mostly to facilitate the dplyr interface. Use the RJDBC driver interface if you need more DBI functionality.
  • This also means that SQL functions unique to Drill have also been “implemented” (i.e. made accessible to the dplyr interface). If you have custom Drill SQL functions that need to be implemented please file an issue on GitHub. Many should work without it, but some may require a custom interface.

dplyr: (REST)

  • src_drill: Connect to Drill (using dplyr) + supporting functions

Note that a number of Drill SQL functions have been mapped to R functions (e.g. grepl) to make it easier to transition from non-database-backed SQL ops to Drill. See the help on drill_custom_functions for more info on these helper Drill custom function mappings.

Drill APIs:

  • drill_connection: Setup parameters for a Drill server/cluster connection
  • drill_active: Test whether Drill HTTP REST API server is up
  • drill_cancel: Cancel the query that has the given queryid
  • drill_jdbc: Connect to Drill using JDBC
  • drill_metrics: Get the current memory metrics
  • drill_options: List the name, default, and data type of the system and session options
  • drill_profile: Get the profile of the query that has the given query id
  • drill_profiles: Get the profiles of running and completed queries
  • drill_query: Submit a query and return results
  • drill_set: Set Drill SYSTEM or SESSION options
  • drill_settings_reset: Changes (optionally, all) session settings back to system defaults
  • drill_show_files: Show files in a file system schema.
  • drill_show_schemas: Returns a list of available schemas.
  • drill_stats: Get Drillbit information, such as ports numbers
  • drill_status: Get the status of Drill
  • drill_storage: Get the list of storage plugin names and configurations
  • drill_system_reset: Changes (optionally, all) system settings back to system defaults
  • drill_threads: Get information about threads
  • drill_uplift: Turn a columnar query results into a type-converted tbl
  • drill_use: Change to a particular schema.
  • drill_version: Identify the version of Drill running

Installation

devtools::install_github("hrbrmstr/sergeant")

Usage

dplyr interface

library(sergeant)
library(tidyverse)

# use localhost if running standalone on same system otherwise the host or IP of your Drill server
ds <- src_drill("localhost")  #ds
db <- tbl(ds, "cp.`employee.json`") 

# without `collect()`:
count(db, gender, marital_status)
## # Source:   lazy query [?? x 3]
## # Database: DrillConnection
## # Groups:   gender
##   marital_status gender     n
##   <chr>          <chr>  <int>
## 1 S              F        297
## 2 M              M        278
## 3 S              M        276
## 4 M              F        304

count(db, gender, marital_status) %>% collect()
## # A tibble: 4 x 3
## # Groups:   gender [2]
##   marital_status gender     n
## * <chr>          <chr>  <int>
## 1 S              F        297
## 2 M              M        278
## 3 S              M        276
## 4 M              F        304

group_by(db, position_title) %>% 
  count(gender) -> tmp2

group_by(db, position_title) %>% 
  count(gender) %>% 
  ungroup() %>% 
  mutate(full_desc=ifelse(gender=="F", "Female", "Male")) %>% 
  collect() %>% 
  select(Title=position_title, Gender=full_desc, Count=n)
## # A tibble: 30 x 3
##    Title                  Gender Count
##  * <chr>                  <chr>  <int>
##  1 President              Female     1
##  2 VP Country Manager     Male       3
##  3 VP Country Manager     Female     3
##  4 VP Information Systems Female     1
##  5 VP Human Resources     Female     1
##  6 Store Manager          Female    13
##  7 VP Finance             Male       1
##  8 Store Manager          Male      11
##  9 HQ Marketing           Female     2
## 10 HQ Information Systems Female     4
## # ... with 20 more rows

arrange(db, desc(employee_id)) %>% print(n=20)
## # Source:     table<cp.`employee.json`> [?? x 20]
## # Database:   DrillConnection
## # Ordered by: desc(employee_id)
##    store_id gender department_id birth_date supervisor_id last_name  position_title hire_date           management_role
##       <int> <chr>          <int> <date>             <int> <chr>      <chr>          <dttm>              <chr>          
##  1       18 F                 18 1914-02-02          1140 Stand      Store Tempora… 1998-01-01 00:00:00 Store Temp Sta…
##  2       18 M                 18 1914-02-02          1140 Burnham    Store Tempora… 1998-01-01 00:00:00 Store Temp Sta…
##  3       18 F                 18 1914-02-02          1139 Doolittle  Store Tempora… 1998-01-01 00:00:00 Store Temp Sta…
##  4       18 M                 18 1914-02-02          1139 Pirnie     Store Tempora… 1998-01-01 00:00:00 Store Temp Sta…
##  5       18 M                 17 1914-02-02          1140 Younce     Store Permane… 1998-01-01 00:00:00 Store Full Tim…
##  6       18 F                 17 1914-02-02          1140 Biltoft    Store Permane… 1998-01-01 00:00:00 Store Full Tim…
##  7       18 M                 17 1914-02-02          1139 Detwiler   Store Permane… 1998-01-01 00:00:00 Store Full Tim…
##  8       18 F                 17 1914-02-02          1139 Ciruli     Store Permane… 1998-01-01 00:00:00 Store Full Tim…
##  9       18 F                 16 1914-02-02          1140 Bishop     Store Tempora… 1998-01-01 00:00:00 Store Full Tim…
## 10       18 F                 16 1914-02-02          1140 Cutwright  Store Tempora… 1998-01-01 00:00:00 Store Full Tim…
## 11       18 F                 16 1914-02-02          1139 Anderson   Store Tempora… 1998-01-01 00:00:00 Store Full Tim…
## 12       18 F                 16 1914-02-02          1139 Swartwood  Store Tempora… 1998-01-01 00:00:00 Store Full Tim…
## 13       18 M                 15 1914-02-02          1140 Curtsinger Store Permane… 1998-01-01 00:00:00 Store Full Tim…
## 14       18 F                 15 1914-02-02          1140 Quick      Store Permane… 1998-01-01 00:00:00 Store Full Tim…
## 15       18 M                 15 1914-02-02          1139 Souza      Store Permane… 1998-01-01 00:00:00 Store Full Tim…
## 16       18 M                 15 1914-02-02          1139 Compagno   Store Permane… 1998-01-01 00:00:00 Store Full Tim…
## 17       18 M                 11 1961-09-24          1139 Jaramillo  Store Shift S… 1998-01-01 00:00:00 Store Manageme…
## 18       18 M                 11 1972-05-12            17 Belsey     Store Assista… 1998-01-01 00:00:00 Store Manageme…
## 19       12 M                 18 1914-02-02          1069 Eichorn    Store Tempora… 1998-01-01 00:00:00 Store Temp Sta…
## 20       12 F                 18 1914-02-02          1069 Geiermann  Store Tempora… 1998-01-01 00:00:00 Store Temp Sta…
## # ... with more rows, and 7 more variables: salary <dbl>, marital_status <chr>, full_name <chr>, employee_id <int>,
## #   education_level <chr>, first_name <chr>, position_id <int>

mutate(db, position_title=tolower(position_title)) %>%
  mutate(salary=as.numeric(salary)) %>% 
  mutate(gender=ifelse(gender=="F", "Female", "Male")) %>%
  mutate(marital_status=ifelse(marital_status=="S", "Single", "Married")) %>% 
  group_by(supervisor_id) %>% 
  summarise(underlings_count=n()) %>% 
  collect()
## # A tibble: 112 x 2
##    supervisor_id underlings_count
##  *         <int>            <int>
##  1             0                1
##  2             1                7
##  3             5                9
##  4             4                2
##  5             2                3
##  6            20                2
##  7            21                4
##  8            22                7
##  9             6                4
## 10            36                2
## # ... with 102 more rows

REST API

dc <- drill_connection("localhost") 

drill_active(dc)
## [1] TRUE

drill_version(dc)
## [1] "1.13.0"

drill_storage(dc)$name
## [1] "cp"    "dfs"   "hbase" "hive"  "kudu"  "mongo" "s3"

drill_query(dc, "SELECT * FROM cp.`employee.json` limit 100")
## Parsed with column specification:
## cols(
##   store_id = col_integer(),
##   gender = col_character(),
##   department_id = col_integer(),
##   birth_date = col_date(format = ""),
##   supervisor_id = col_integer(),
##   last_name = col_character(),
##   position_title = col_character(),
##   hire_date = col_datetime(format = ""),
##   management_role = col_character(),
##   salary = col_double(),
##   marital_status = col_character(),
##   full_name = col_character(),
##   employee_id = col_integer(),
##   education_level = col_character(),
##   first_name = col_character(),
##   position_id = col_integer()
## )
## # A tibble: 100 x 16
##    store_id gender department_id birth_date supervisor_id last_name position_title  hire_date           management_role
##  *    <int> <chr>          <int> <date>             <int> <chr>     <chr>           <dttm>              <chr>          
##  1        0 F                  1 1961-08-26             0 Nowmer    President       1994-12-01 00:00:00 Senior Managem…
##  2        0 M                  1 1915-07-03             1 Whelply   VP Country Man… 1994-12-01 00:00:00 Senior Managem…
##  3        0 M                  1 1969-06-20             1 Spence    VP Country Man… 1998-01-01 00:00:00 Senior Managem…
##  4        0 F                  1 1951-05-10             1 Gutierrez VP Country Man… 1998-01-01 00:00:00 Senior Managem…
##  5        0 F                  2 1942-10-08             1 Damstra   VP Information… 1994-12-01 00:00:00 Senior Managem…
##  6        0 F                  3 1949-03-27             1 Kanagaki  VP Human Resou… 1994-12-01 00:00:00 Senior Managem…
##  7        9 F                 11 1922-08-10             5 Brunner   Store Manager   1998-01-01 00:00:00 Store Manageme…
##  8       21 F                 11 1979-06-23             5 Blumberg  Store Manager   1998-01-01 00:00:00 Store Manageme…
##  9        0 M                  5 1949-08-26             1 Stanz     VP Finance      1994-12-01 00:00:00 Senior Managem…
## 10        1 M                 11 1967-06-20             5 Murraiin  Store Manager   1998-01-01 00:00:00 Store Manageme…
## # ... with 90 more rows, and 7 more variables: salary <dbl>, marital_status <chr>, full_name <chr>, employee_id <int>,
## #   education_level <chr>, first_name <chr>, position_id <int>

drill_query(dc, "SELECT COUNT(gender) AS gender FROM cp.`employee.json` GROUP BY gender")
## Parsed with column specification:
## cols(
##   gender = col_integer()
## )
## # A tibble: 2 x 1
##   gender
## *  <int>
## 1    601
## 2    554

drill_options(dc)
## # A tibble: 138 x 5
##    name                                              value    accessibleScopes kind    optionScope
##  * <chr>                                             <chr>    <chr>            <chr>   <chr>      
##  1 debug.validate_iterators                          FALSE    ALL              BOOLEAN BOOT       
##  2 debug.validate_vectors                            FALSE    ALL              BOOLEAN BOOT       
##  3 drill.exec.functions.cast_empty_string_to_null    FALSE    ALL              BOOLEAN BOOT       
##  4 drill.exec.hashagg.fallback.enabled               FALSE    ALL              BOOLEAN BOOT       
##  5 drill.exec.memory.operator.output_batch_size      16777216 SYSTEM           LONG    BOOT       
##  6 drill.exec.storage.file.partition.column.label    dir      ALL              STRING  BOOT       
##  7 drill.exec.storage.implicit.filename.column.label filename ALL              STRING  BOOT       
##  8 drill.exec.storage.implicit.filepath.column.label filepath ALL              STRING  BOOT       
##  9 drill.exec.storage.implicit.fqn.column.label      fqn      ALL              STRING  BOOT       
## 10 drill.exec.storage.implicit.suffix.column.label   suffix   ALL              STRING  BOOT       
## # ... with 128 more rows

drill_options(dc, "json")
## # A tibble: 9 x 5
##   name                                                  value accessibleScopes kind    optionScope
##   <chr>                                                 <chr> <chr>            <chr>   <chr>      
## 1 store.json.all_text_mode                              FALSE ALL              BOOLEAN BOOT       
## 2 store.json.extended_types                             FALSE ALL              BOOLEAN BOOT       
## 3 store.json.read_numbers_as_double                     FALSE ALL              BOOLEAN BOOT       
## 4 store.json.reader.allow_nan_inf                       TRUE  ALL              BOOLEAN BOOT       
## 5 store.json.reader.print_skipped_invalid_record_number FALSE ALL              BOOLEAN BOOT       
## 6 store.json.reader.skip_invalid_records                FALSE ALL              BOOLEAN BOOT       
## 7 store.json.writer.allow_nan_inf                       TRUE  ALL              BOOLEAN BOOT       
## 8 store.json.writer.skip_null_fields                    TRUE  ALL              BOOLEAN BOOT       
## 9 store.json.writer.uglify                              FALSE ALL              BOOLEAN BOOT

Working with parquet files

drill_query(dc, "SELECT * FROM dfs.`/usr/local/drill/sample-data/nation.parquet` LIMIT 5")
## Parsed with column specification:
## cols(
##   N_COMMENT = col_character(),
##   N_NAME = col_character(),
##   N_NATIONKEY = col_integer(),
##   N_REGIONKEY = col_integer()
## )
## # A tibble: 5 x 4
##   N_COMMENT            N_NAME    N_NATIONKEY N_REGIONKEY
## * <chr>                <chr>           <int>       <int>
## 1 haggle. carefully f  ALGERIA             0           0
## 2 al foxes promise sly ARGENTINA           1           1
## 3 y alongside of the p BRAZIL              2           1
## 4 eas hang ironic, sil CANADA              3           1
## 5 y above the carefull EGYPT               4           4

Including multiple parquet files in different directories (note the wildcard support):

drill_query(dc, "SELECT * FROM dfs.`/usr/local/drill/sample-data/nations*/nations*.parquet` LIMIT 5")
## Parsed with column specification:
## cols(
##   N_COMMENT = col_character(),
##   N_NAME = col_character(),
##   N_NATIONKEY = col_integer(),
##   dir0 = col_character(),
##   N_REGIONKEY = col_integer()
## )
## # A tibble: 5 x 5
##   N_COMMENT            N_NAME    N_NATIONKEY dir0      N_REGIONKEY
## * <chr>                <chr>           <int> <chr>           <int>
## 1 haggle. carefully f  ALGERIA             0 nationsSF           0
## 2 al foxes promise sly ARGENTINA           1 nationsSF           1
## 3 y alongside of the p BRAZIL              2 nationsSF           1
## 4 eas hang ironic, sil CANADA              3 nationsSF           1
## 5 y above the carefull EGYPT               4 nationsSF           4

Drill has built-in support for spatial ops

Via: https://github.com/k255/drill-gis

A common use case is to select data within boundary of given polygon:

drill_query(dc, "
select columns[2] as city, columns[4] as lon, columns[3] as lat
    from cp.`sample-data/CA-cities.csv`
    where
        ST_Within(
            ST_Point(columns[4], columns[3]),
            ST_GeomFromText(
                'POLYGON((-121.95 37.28, -121.94 37.35, -121.84 37.35, -121.84 37.28, -121.95 37.28))'
                )
            )
")
## Parsed with column specification:
## cols(
##   city = col_character(),
##   lon = col_double(),
##   lat = col_double()
## )
## # A tibble: 7 x 3
##   city          lon   lat
## * <chr>       <dbl> <dbl>
## 1 Burbank     -122.  37.3
## 2 San Jose    -122.  37.3
## 3 Lick        -122.  37.3
## 4 Willow Glen -122.  37.3
## 5 Buena Vista -122.  37.3
## 6 Parkmoor    -122.  37.3
## 7 Fruitdale   -122.  37.3

Test Results

library(sergeant)
library(testthat)
## 
## Attaching package: 'testthat'
## The following object is masked from 'package:dplyr':
## 
##     matches
## The following object is masked from 'package:purrr':
## 
##     is_null

date()
## [1] "Sun Oct 14 08:27:29 2018"

devtools::test()
## Loading sergeant
## Testing sergeant
## ✔ | OK F W S | Context
## |  0       | dplyr API
⠋ |  1       | dplyr API
⠙ |  2       | dplyr API
⠹ |  3       | dplyr API
✔ |  3       | dplyr API [0.3 s]
## |  0       | REST API
⠋ |  1       | REST API
⠙ |  2       | REST API
⠹ |  3       | REST API
⠸ |  4       | REST API
⠼ |  5       | REST API
⠴ |  6       | REST API
⠦ |  7       | REST API
⠧ |  8       | REST API
⠇ |  9       | REST API
⠏ | 10       | REST API
⠋ | 11       | REST API
⠙ | 12       | REST API
⠹ | 13       | REST API
⠸ | 14       | REST API
⠼ | 15       | REST API
⠴ | 16       | REST API
✔ | 16       | REST API [2.2 s]
## 
## ══ Results ═══════════════════════════════════════════════════
## Duration: 2.5 s
## 
## OK:       19
## Failed:   0
## Warnings: 0
## Skipped:  0

sergeant Metrics

Lang # Files (%) LoC (%) Blank lines (%) # Lines (%)
R 12 0.92 625 0.92 173 0.75 562 0.87
Rmd 1 0.08 55 0.08 58 0.25 86 0.13

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.