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Command Line Tutorial
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)
-if, --input-format <InputFormat> input format, requires the query option (default: ION) [ION, PARTIQL]
-w, --wrap-ion wraps Ion input file values in a bag, requires the input format to be ION, requires the query option
-m, --monochrome removes syntax highlighting for the REPL
-o, --output <File> output file, requires the query option (default: stdout)
-of, --output-format <OutputFormat> output format, requires the query option (default: PARTIQL) [PARTIQL, PARTIQL_PRETTY, ION_TEXT, ION_BINARY]
-p, --permissive run the PartiQL query in PERMISSIVE typing mode
-q, --query <String> PartiQL query, triggers non interactive mode
The root Gradle build also builds the CLI. To build the CLI separately, execute:
./gradlew :cli:buildAfter 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>"The CLI can be run in two manners, non-interactive and interactive (REPL).
To start an interactive read, eval, print loop (REPL) execute:
Note that running directly with Gradle will eat arrow keys and control sequences due to the Gradle daemon.
./partiql-app/partiql-cli/shell.shYou will see a prompt that looks as follows:
Welcome to the PartiQL REPL!
PartiQL> At this point, you can type in valid SQL/PartiQL and press enter twice to execute it:
PartiQL> SELECT id FROM `[{id: 5, name:"bill"}, {id: 6, name:"bob"}]` WHERE name = 'bob';<<
{
'id': 6
}
>>
Alternatively, you can denote the end of a query using a semi-colon:
PartiQL> SELECT id FROM `[{id: 5, name:"bill"}, {id: 6, name:"bob"}]` WHERE name = 'bob';<<
{
'id': 6
}
>>
The result of the 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
}
>>
Press control-D to exit the REPL.
To view the AST of a PartiQL statement, type the statement 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 a PartiQL file with a
single struct containing the initial global environment.
For example, a file named config.env contains 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}
]
}
The variables animals and types can both be bound to the execution environment for later access.
To bind the environment file to the execution environment, start the REPL with the following command:
$ ./gradlew :cli:run -q --console=plain --args='-e config.env'Note: 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.envExpressions can then use the environment defined by config.env:
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
}
>>
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'
}
]
}
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': []
}
Let's look at what has changed:
PartiQL> !global_env{
'types': [],
'animals': [
{
'name': 'Kumo',
'type': 'dog'
},
{
'name': 'Mochi',
'type': 'dog'
},
{
'name': 'Lilikoi',
'type': 'unicorn'
}
]
}
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'
]
}
>>
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'
}
>>
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'
]
}
]
}
>>
The REPL provides the read_file function to stream data from a file. The files need to be placed in the folder cli,
and, if using the default file type (Ion), they must contain only a single Ion value (typically a list).
Note: Later on, we will introduce reading different file types, but we will first focus on the default (Ion).
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' }
]
To 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'
}
>>
The REPL also has the capability to write files with the write_file function:
PartiQL> write_file('out.ion', SELECT * FROM _);A file called out.ion will be created in the cli directory with the following contents:
$bag::[
{
city: Honolulu
},
{
city: Rochester
}
]
Notice that PartiQL added the annotation of $bag to the Ion list. When outputting to Ion, we use type
annotations to represent some PartiQL values/types not in Ion.
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'
}
>>
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.
Note: One might ask how this differs from reading in Ion files. With Ion files, PartiQL expects a single value -- typically a bag/list, but it can also be literals such as strings or integers. CSV & TSV rows, on the other hand, are always interpreted as being contained within a bag.
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
You can read the file with the following CLI command:
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'
}
>>
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'
}
>>
Auto-conversion for numeric and timestamp values can also be specified as follows:
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
}
>>
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'});This would produce the following file:
$ cat out.tsv
Kumo dog
Mochi dog
Lilikoi unicornThe 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});Which would produce the following file:
$ cat out.tsv
name type
Kumo dog
Mochi dog
Lilikoi unicornThe 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:
PartiQL> 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:
PartiQL> read_file('customized.csv', {'type':'customized', 'delimiter':' ', 'header':true})All the available options for customized CSV files are as follows:
- 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': ','
We also provide a CLI function, query_ddb, that allows you to query AWS DynamoDB tables and perform additional computations on
the response.
Note: This implementation uses the Default Credentials Provider. Please see the link to determine how you can specify which account/profile to use.
For example, let's say you have a DDB table called users with primary-key of id. If your AWS credentials and
configurations are set correctly, you can perform the following:
PartiQL> query_ddb('SELECT * FROM users WHERE id = 0');Which, depending on the content of your table, will return something like:
[
{
'id': 0,
'name': 'John Doe',
'age': 22
}
]Now, while we don't recommend performing scans on your DDB tables (due to the cost), you can execute queries similar to:
PartiQL> !add_to_global_env {
'fullNames': <<
'John Doe',
'Sarah Jane',
'Boe Jackson'
>>
};
PartiQL> SELECT VALUE id
FROM query_ddb('SELECT id, name, age FROM users')
WHERE name IN fullNames;The above query will get the id's of all the users in your local environment, something like:
<<
0,
17,
1004
>>
Also, if you'd like to perform insertions into DDB tables, you can perform them as follows:
PartiQL> query_ddb('INSERT INTO users VALUE {''id'': 96, ''name'': ''Kim Lu'', ''age'': 26}');Note: You can escape the PartiQL single-quote by prepending another single-quote. See above.
For in-depth documentation on valid DDB PartiQL queries, please reference the official AWS DynamoDB PartiQL Docs.
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
---
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