jl v2.4.1

node-jl

(Russian translation)

Utility kit for working with JSON files/streams divided by \n symbol. JSON-representation of each record shouldn't contain line breaking symbol.

Install

npm install -g jl

Examples

We have a log file /tmp/test.json, that contains next records

{"ts": 1416595508, "type": "click"}
{"ts": 1416478467, "type": "buy", "price": 10}
{"ts": 1416466930, "type": "click"}
{"ts": 1416622653, "type": "buy", "price": 20}
{"ts": 1416699396, "type": "click"}
{"ts": 1416624334, "type": "click"}
{"ts": 1416518859, "type": "click"}
{"ts": 1416569870, "type": "click"}
{"ts": 1416573325, "type": "click"}
{"ts": 1416682270, "type": "click"}

SQL-interface

jl-sql utility supports query language very similar to SQL

cat /tmp/test.json \
    | jl-sql 'SELECT type, COUNT(*) AS c, SUM(price) AS sum GROUP BY type ORDER BY c NUMERIC DESC'

{"type":"click","c":8,"sum":0}
{"type":"buy","c":2,"sum":30}

As you can see we receive that we expect.

Please note non-standard keyword NUMERIC after ORDER BY: without this keyword, sorting will be by string representation, not by numerical value.

Constants

• NULL
• TRUE
• FALSE

Operators

Arithmetic

• +
• -
• *
• /
• %

Comparison

• =, ==
• !=
• === - Comparison with type check
• !== - Negative comparison with type check
• >
• <
• >=
• <=

Logical

• AND, &&
• OR, ||
• !

Functions

Functions for working with data

• FROM_UNIXTIME(unixTimestamp) - converts unix timestamp to Date
• UNIX_TIMESTAMP(date) - converts Date to unix timestamp, date should be string in 'YYYY-MM-DD hh:mm:ss' format
• DATE(date) - returns date in 'YYYY-MM-DD' format

Misc

• IF(expression, ifTrue, ifFalse)
• COALESCE(expression1[, expression2[, ...]])

Aggregating

Right now, only very basic aggregating functions supported:

• SUM(expression) - counts summary of field's values. Non-numerical values will be ignored
• MIN(expression) - returns minimal field's value. Non-numerical values will be ignored
• MAX(expression) - returns maximal field's value. Non-numerical values will be ignored
• COUNT(expression) - counts amount of elements for which comparison with expression will be !== null or !== undefined
• COUNT(*) - counts amount of elements
• HLL_COUNT_DISTINCT(arg1[, args2[, ...]]) - counts amount of unique argument combinations. Uses O(1) of memory and O(N) of CPU, but returns result with 0.1% error. For more information read HyperLogLog algorithm.

Restrictions

• JOIN is not supported(and probably never will be)
• Sorting by multiple fields is not supported
• LIMIT is not supported, but could be replaced with head and tail

Low-level interface

SQL-interface only wrapper for utility kit described down below. By combining those utilities you can do much more than with SQL.

Filtering and aggregation

Let's filter only events with type buy

cat /tmp/test.json \
    | jl-filter 'type == "buy"'

{"ts": 1416478467, "type": "buy", "price": 10}
{"ts": 1416622653, "type": "buy", "price": 20}

Add sum calculation for all price fields

cat /tmp/test.json \
    | jl-filter 'type == "buy"'
    | jl-sum price

{"value":30}

To get just 30 you can add jl-extract value at the end - this command extract value of the field.

Sorting

Let sort log file by ts field

cat /tmp/test.json \
    | jl-sort ts

{"ts": 1416466930, "type": "click"}
{"ts": 1416478467, "type": "buy", "price": 10}
{"ts": 1416518859, "type": "click"}
{"ts": 1416569870, "type": "click"}
{"ts": 1416573325, "type": "click"}
{"ts": 1416595508, "type": "click"}
{"ts": 1416622653, "type": "buy", "price": 20}
{"ts": 1416624334, "type": "click"}
{"ts": 1416682270, "type": "click"}
{"ts": 1416699396, "type": "click"}

The standard arguments of sort utility is also supported: -r, -n, -u, -m, -s, -T, -S

Modification

Let's add to each object field date, that contains event date in UTC format

cat /tmp/test.json \
    | jl-transform '{r.date = (new Date(r.ts * 1000)).toUTCString()}'

{"ts":1416595508,"type":"click","date":"Fri, 21 Nov 2014 18:45:08 GMT"}
{"ts":1416478467,"type":"buy","price":10,"date":"Thu, 20 Nov 2014 10:14:27 GMT"}
{"ts":1416466930,"type":"click","date":"Thu, 20 Nov 2014 07:02:10 GMT"}
{"ts":1416622653,"type":"buy","price":20,"date":"Sat, 22 Nov 2014 02:17:33 GMT"}
{"ts":1416699396,"type":"click","date":"Sat, 22 Nov 2014 23:36:36 GMT"}
{"ts":1416624334,"type":"click","date":"Sat, 22 Nov 2014 02:45:34 GMT"}
{"ts":1416518859,"type":"click","date":"Thu, 20 Nov 2014 21:27:39 GMT"}
{"ts":1416569870,"type":"click","date":"Fri, 21 Nov 2014 11:37:50 GMT"}
{"ts":1416573325,"type":"click","date":"Fri, 21 Nov 2014 12:35:25 GMT"}
{"ts":1416682270,"type":"click","date":"Sat, 22 Nov 2014 18:51:10 GMT"}

Internal pipe

The system pipes are inefficient because of serialization/deserialization of JSON each time when working with multiple jl-utilities because each utility receives and returns JSON using stdin/stdout.

To solve this problem jl-utilities supports internal piping which allows to multiple utilities interact with each other in the context of a single process without spending resources for parsing. To use internal pipes replace | to \| between jl-commands in the command line. For example:

cat /tmp/test.json \
    | jl-filter 'type == "buy"'
    | jl-sum price

you can change to:

cat /tmp/test.json \
    | jl-filter 'type == "buy"'
    \| jl-sum price

Performance

CPU consumption of all utilities except for jl-sort is O(n), by memory is O(1).

The performance of jl-sort completely depends on system's sort realization, additional CPU consumptions also O(n), and by memory O(1).

By using internal pipes significantly increases performance because JSON parsing is very expensive operation. But in another hand, all operations in pipes is computing in a single thread, so with very long pipes you should keep the balance.

Utilities

jl-sql - SQL

Requires single argument - SQL and has few options:

• -T DIR - temporary directory which will be used for sorting if it didn't use RAM. $TMPDIR or /tmp by default. Pay attention when sorting big amount of data, by having /tmp on the RAM disk.
• -S BUF - size of sorting buffer in bytes. On buffer overflow, filesystem will be used(see -T option)

jl-sort - sorting

Wrapper for GNU Sort, allowing to sort JSON. Uses all advantages of sort, also, supports sorting in filesystem, merge-sort, stable sorting, limit buffer size.

jl-filter - filtering

Alternative to grep, but for JSON.

jl-reduce - aggregation and grouping by key

General utility that produces welding elements into a single value for each group. Expects 3 JS-functions arguments:

• -i FUNC - accumulator initialization: gets called for each group. The function executes in a group context.
• -u FUNC - accumulator update: the function that will be executed for each element of a group. The function executes in a group context and receives argument r, containing each element of a thread.
• -r FUNC - received accumulator's value: will be executed at the end of group with the passed result. The function executes in a group context.

and one required argument

• -k KEYDEF - key which will be used for grouping, could be a function. For correct execution thread's input should be sorted by this key in any direction.

Here is simple example of using jl-sum utility, which counts sum for amount field for each user that gets identified by uid field:

jl-reduce -k uid -i '{this.sum = 0}' -u '{this.sum += r.amount}' -r '{return this.sum}'

For thread's input containing:

{"uid": 1, "amount": 10}
{"uid": 1, "amount": 11}
{"uid": 2, "amount": 12}
{"uid": 3, "amount": 13}

Output will be:

{"key":1,"value":21}
{"key":2,"value":12}
{"key":3,"value":13}

If -k argument will be missing, convolution will go over whole thread and will return:

{"value":46}

jl-sum - summation

Predefined jl-reduce, which counts sum of parameter in group

jl-count - подсчёт количества

Predefined jl-reduce, which counts amount of elements in group

jl-transform - modification

jl-extract - field's value extraction

jl-from-csv - CSV to JSON conversation

jl-plainify - Flattens object to a single level deep k-v