PartiQL CLI
Command line interface for executing PartiQL queries. Can be run in an interactive (REPL) mode or non-interactive.
Examples:
To run in REPL mode simply execute the executable without any arguments:
partiql
In non-interactive mode we use Ion as the format for input data which is bound to a global variable
named "input_data", in the example below /logs/log.ion is bound to "input_data":
partiql --query="SELECT * FROM input_data" --input=/logs/log.ion
The cli can output using PartiQL syntax or Ion using the --output-format option, e.g. to output binary ion:
partiql --query="SELECT * FROM input_data" --output-format=ION_BINARY --input=/logs/log.ion
To pipe input data in via stdin:
cat /logs/log.ion | partiql --query="SELECT * FROM input_data" --format=ION_BINARY > output.10n
Option Description
------ -----------
-e, --environment <File> initial global environment (optional)
-h, --help prints this help
-i, --input <File> input file, requires the query option (optional)
-o, --output <File> output file, requires the query option (default: stdout)
--of, --output-format <OutputFormat: output format, requires the query option (default: PARTIQL)
(ION_TEXT|ION_BINARY|PARTIQL|PARTIQL_PRETTY)>
-p, --permissive run the PartiQL query in PERMISSIVE typing mode
-q, --query <String> PartiQL query, triggers non interactive mode
The CLI is built during the main Gradle build. To build it separately execute:
./gradlew :cli:build
After building, distributable jars are located in the cli/build/distributions
directory (relative to the
project root).
Be sure to include the correct relative path to gradlew
if you are not in the project root.
The following command will build any dependencies before starting the CLI.
./gradlew :cli:run -q --args="<command line arguments>"
To start an interactive read, eval, print loop (REPL) execute:
rlwrap ./gradlew :cli:run --console=plain
rlwrap provides command history support. It allows
the use of the up and down arrow keys to cycle through recently executed commands and remembers commands entered into
previous sessions. rlwrap
is available as an optional package in all major Linux distributions and in
Homebrew on MacOS. rlwrap
is not required but is highly recommended.
You will see a prompt that looks as follows:
Welcome to the PartiQL REPL!
PartiQL>
At this point you can type in SQL and press enter twice to execute it:
PartiQL> SELECT id FROM `[{id: 5, name:"bill"}, {id: 6, name:"bob"}]` WHERE name = 'bob'
|
==='
<<
{
'id': 6
}
>>
---
OK!
The result of previous expression is stored in the variable named _
, so you can then run subsequent
expressions based on the last one.
PartiQL> SELECT id + 4 AS name FROM _
|
==='
<<
{
'name': 10
}
>>
---
OK!
Press control-D to exit the REPL.
To view the AST of an SQL statement, type one and press enter only once, then type !!
and press enter:
PartiQL> 1 + 1
| !!
==='
(
ast
(
version
1
)
(
root
(
+
(
lit
1
)
(
lit
1
)
)
)
)
---
OK!
The initial environment for the REPL can be setup with a configuration file, which should be an PartiQL file with a
single struct
containing the initial global environment.
For example a file named config.sql
, containing the following:
{
'animals':[
{'name': 'Kumo', 'type': 'dog'},
{'name': 'Mochi', 'type': 'dog'},
{'name': 'Lilikoi', 'type': 'unicorn'}
],
'types':[
{'id': 'dog', 'is_magic': false},
{'id': 'cat', 'is_magic': false},
{'id': 'unicorn', 'is_magic': true}
]
}
Could be loaded into the REPL with animals
and types
bound list of struct
values.
The REPL could be started up with:
$ ./gradlew :cli:run -q --console=plain --args='-e config.sql'
(Note that shell expansions such as ~
do not work within the value of the args
argument.)
Or if you have extracted one of the compressed archives:
$ ./bin/partiql -e config.sql
Expressions can then use the environment defined by config.sql
:
PartiQL> SELECT name, type, is_magic FROM animals, types WHERE type = id
|
==='
<<
{
'name': 'Kumo',
'type': 'dog',
'is_magic': false
},
{
'name': 'Mochi',
'type': 'dog',
'is_magic': false
},
{
'name': 'Lilikoi',
'type': 'unicorn',
'is_magic': true
}
>>
---
OK!
To see the current REPL environment you can use !global_env
, for example for the file above:
PartiQL> !global_env
|
==='
{
'types': [
{
'id': 'dog',
'is_magic': false
},
{
'id': 'cat',
'is_magic': false
},
{
'id': 'unicorn',
'is_magic': true
}
],
'animals': [
{
'name': 'Kumo',
'type': 'dog'
},
{
'name': 'Mochi',
'type': 'dog'
},
{
'name': 'Lilikoi',
'type': 'unicorn'
}
]
}
---
OK!
You can also add new values to the global environment or replace existing values using !add_to_global_env
. The
example below replaces the value bound to types
PartiQL> !add_to_global_env {'types': []}
|
==='
{
'types': []
}
---
OK!
PartiQL> !global_env
|
==='
{
'types': [],
'animals': [
{
'name': 'Kumo',
'type': 'dog'
},
{
'name': 'Mochi',
'type': 'dog'
},
{
'name': 'Lilikoi',
'type': 'unicorn'
}
]
}
---
OK!
Let's consider the following initial environment:
{
'stores':[
{
'id': 5,
'books': [
{'title':'A', 'price': 5.0, 'categories':['sci-fi', 'action']},
{'title':'B', 'price': 2.0, 'categories':['sci-fi', 'comedy']},
{'title':'C', 'price': 7.0, 'categories':['action', 'suspense']},
{'title':'D', 'price': 9.0, 'categories':['suspense']}
]
},
{
'id': 6,
'books': [
{'title':'A', 'price': 5.0, 'categories':['sci-fi', 'action']},
{'title':'E', 'price': 9.5, 'categories':['fantasy', 'comedy']},
{'title':'F', 'price': 10.0, 'categories':['history']}
]
}
]
}
Set the environment as below
PartiQL> !add_to_global_env { 'stores':[ { 'id': 5, 'books': [ {'title':'A', 'price': 5.0, 'categories':['sci-fi', 'action']}, {'title':'B', 'price': 2.0, 'categories':['sci-fi', 'comedy']}, {'title':'C', 'price': 7.0, 'categories':['action', 'suspense']}, {'title':'D', 'price': 9.0, 'categories':['suspense']} ] }, { 'id': 6, 'books': [ {'title':'A', 'price': 5.0, 'categories':['sci-fi', 'action']}, {'title':'E', 'price': 9.5, 'categories':['fantasy', 'comedy']}, {'title':'F', 'price': 10.0, 'categories':['history']} ] } ] }
If we wanted to find all books as their own rows with a price greater than 7
we can use paths on the FROM
for this:
PartiQL> SELECT * FROM stores[*].books[*] AS b WHERE b.price > 7
|
==='
<<
{
'title': 'D',
'price': 9.0,
'categories': [
'suspense'
]
},
{
'title': 'E',
'price': 9.5,
'categories': [
'fantasy',
'comedy'
]
},
{
'title': 'F',
'price': 10.0,
'categories': [
'history'
]
}
>>
---
OK!
If you wanted to also de-normalize the store ID and title into the above rows:
PartiQL> SELECT s.id AS store, b.title AS title FROM stores AS s, @s.books AS b WHERE b.price > 7
|
==='
<<
{
'store': 5,
'title': 'D'
},
{
'store': 6,
'title': 'E'
},
{
'store': 6,
'title': 'F'
}
>>
---
OK!
We can also use sub-queries with paths to predicate on sub-structure without changing the
cardinality. So if we wanted to find all stores with books having prices greater than
9.5
PartiQL> SELECT * FROM stores AS s
| WHERE EXISTS(
| SELECT * FROM @s.books AS b WHERE b.price > 9.5
| )
|
==='
<<
{
'id': 6,
'books': [
{
'title': 'A',
'price': 5.0,
'categories': [
'sci-fi',
'action'
]
},
{
'title': 'E',
'price': 9.5,
'categories': [
'fantasy',
'comedy'
]
},
{
'title': 'F',
'price': 10.0,
'categories': [
'history'
]
}
]
}
>>
---
OK!
The REPL provides the read_file
function to stream data from a file. The files needs to be placed in the folder cli
.
For example:
Create a file called data.ion
in the cli
folder with the following contents
{ 'city': 'Seattle', 'state': 'WA' }
{ 'city': 'Bellevue', 'state': 'WA' }
{ 'city': 'Honolulu', 'state': 'HI' }
{ 'city': 'Rochester', 'state': 'NY' }
Select the cities that are in HI
and NY
states
PartiQL> SELECT city FROM read_file('data.ion') AS c, `["HI", "NY"]` AS s WHERE c.state = s
|
==='
<<
{
'city': 'Honolulu'
},
{
'city': 'Rochester'
}
>>
------
OK!
The REPL also has the capability to write files with the write_file
function:
PartiQL> write_file('out.ion', SELECT * FROM _)
|
==='
true
------
OK!
A file called out.ion
will be created in the cli
directory with the following contents
{
city:Honolulu
}
{
city:Rochester
}
Functions and expressions can be used in the global configuration as well. Consider
the following config.ion
:
{
'data': read_file('data.ion')
}
The data
variable will now be bound to file containing Ion:
PartiQL> SELECT * FROM data
|
==='
<<
{
'city: ;Seattle;,
'state: 'WA;
},
{
'city: 'Bellevue',
'state: 'WA'
},
{
'city: 'Honolulu',
'state: 'HI'
},
{
'city: 'Rochester',
'state: 'NY'
}
>>
------
OK!
The read_file
function supports an optional struct argument to add additional parsing options.
Parsing delimited files can be specified with the type
field with a string tsv
or csv
to parse tab or comma separated values respectively.
Create a file called simple.csv
in the cli
directory with the following contents
title,category,price
harry potter,book,7.99
dot,electronics,49.99
echo,electronics,99.99
PartiQL> read_file('simple.csv', {'type':'csv'})
|
==='
<<
{
_0:'title',
_1:'category',
_2:'price'
},
{
_0:'harry potter',
_1:'book',
_2:'7.99'
},
{
_0:'dot',
_1:'electronics',
_2:'49.99'
},
{
_0:'echo',
_1:'electronics',
_2:'99.99'
}
>>
----
OK!
The options struct
can also define if the first row for delimited data should be the
column names with the header
field.
PartiQL> read_file('simple.csv', {'type': 'csv', 'header': true})
|
==='
<<
{
'title': 'harry potter',
'category': 'book',
'price': '7.99'
},
{
'title': 'dot',
'category': 'electronics',
'price': '49.99'
},
{
'title': 'echo',
'category': 'electronics',
'price': '99.99'
}
>>
----
OK!
Auto conversion can also be specified numeric and timestamps in delimited data.
PartiQL> read_file('simple.csv', {'type':'csv', 'header':true, 'conversion':'auto'})
|
==='
<<
{
'title':' harry potter',
'category': 'book',
'price': 7.99
},
{
'title: 'dot',
'category': 'electronics',
'price': 49.99
},
{
'title: 'echo',
'category': 'electronics',
'price': 99.99
}
>>
----
OK!
Writing TSV/CSV data can be done by specifying the optional struct
argument to specify output
format to the write_file
function. Similar to the read_file
function, the type
field
can be used to specify tsv
, csv
, or ion
output.
PartiQL> write_file('out.tsv', SELECT name, type FROM animals, {'type':'tsv'},)
|
==='
true
----
OK!
This would produce the following file:
$ cat out.tsv
Kumo dog
Mochi dog
Lilikoi unicorn
The options struct
can also specify a header
Boolean field to indicate whether the output
TSV/CSV should have a header row.
PartiQL> write_file('out.tsv', SELECT name, type FROM animals, {'type':'tsv', 'header':true})
|
==='
true
----
OK!
Which would produce the following file:
$ cat out.tsv
name type
Kumo dog
Mochi dog
Lilikoi unicorn
The read_file
function provides options to read other predefined CSV data formats.
For example, if a CSV file is exported from PostgreSQL, we can use the following command
to read the file:
read_file('simple_postgresql.csv', {'type':'postgresql_csv'})
Other available options for the argument type
besides postgresql_csv
are excel_csv
, mysql_csv
, and postgresql_text
.
The read_file
function also provides options to read customized CSV data formats.
For example, we have a data file where the whitespace is the separator as shown below:
title category price
harry_potter book 7.99
dot electronics 49.99
echo electronics 99.99
We can use the following command to read the file:
read_file('customized.csv', {'type':'customized', 'delimiter':' ', 'header':true})
All the available options for customized CSV files are shown as following:
- Ignore empty lines:
'ignore_empty_line':true
- Ignore spaces surrounding comma:
'ignore_surrounding_space':true
- Trim leading and trailing blanks:
'trim':true
- Set line breaker (only working with '\r', '\n' and '\r\n'):
'line_breaker: \n'
- Set escape sign (single character only):
'escape':'\'
- Set quote sign (single character only):
'quote':'"'
- Set delimiter sign (single character only):
'delimiter':','
By default, the CLI/REPL runs in LEGACY typing mode, which will give an evaluation time error in the case of data type mismatches.
(Running in the default LEGACY typing mode)
PartiQL> 1 + 'foo';
org.partiql.lang.eval.EvaluationException: ...
...
Specifying the -p
or -permissive
flag will allow you to run PartiQL queries in PERMISSIVE
typing mode, which will return MISSING
in the case of data type mismatches.
(Running in PERMISSIVE typing mode)
PartiQL> 1 + 'foo';
==='
MISSING
---
OK!