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default Commands PPL SQL and PPL 2
/search-plugins/ppl/commands/

Commands

PPL supports all SQL common functions, including relevance search, but also introduces few more functions (called commands) which are available in PPL only.

dedup

The dedup (data deduplication) command removes duplicate documents defined by a field from the search result.

Syntax

dedup [int] <field-list> [keepempty=<bool>] [consecutive=<bool>]
Field Description Type Required Default
int Retain the specified number of duplicate events for each combination. The number must be greater than 0. If you do not specify a number, only the first occurring event is kept and all other duplicates are removed from the results. string No 1
keepempty If true, keep the document if any field in the field list has a null value or a field missing. nested list of objects No False
consecutive If true, remove only consecutive events with duplicate combinations of values. Boolean No False
field-list Specify a comma-delimited field list. At least one field is required. String or comma-separated list of strings Yes -

Example 1: Dedup by one field

To remove duplicate documents with the same gender:

search source=accounts | dedup gender | fields account_number, gender;
account_number gender
1 M
13 F

Example 2: Keep two duplicate documents

To keep two duplicate documents with the same gender:

search source=accounts | dedup 2 gender | fields account_number, gender;
account_number gender
1 M
6 M
13 F

Example 3: Keep or ignore an empty field by default

To keep two duplicate documents with a null field value:

search source=accounts | dedup email keepempty=true | fields account_number, email;
account_number email
1 amberduke@pyrami.com
6 hattiebond@netagy.com
13 null
18 daleadams@boink.com

To remove duplicate documents with the null field value:

search source=accounts | dedup email | fields account_number, email;
account_number email
1 amberduke@pyrami.com
6 hattiebond@netagy.com
18 daleadams@boink.com

Example 4: Dedup of consecutive documents

To remove duplicates of consecutive documents:

search source=accounts | dedup gender consecutive=true | fields account_number, gender;
account_number gender
1 M
13 F
18 M

Limitations

The dedup command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.

eval

The eval command evaluates an expression and appends its result to the search result.

Syntax

eval <field>=<expression> ["," <field>=<expression> ]...
Field Description Required
field If a field name does not exist, a new field is added. If the field name already exists, it's overwritten. Yes
expression Specify any supported expression. Yes

Example 1: Create a new field

To create a new doubleAge field for each document. doubleAge is the result of age multiplied by 2:

search source=accounts | eval doubleAge = age * 2 | fields age, doubleAge;
age doubleAge
32 64
36 72
28 56
33 66

Example 2: Overwrite the existing field

To overwrite the age field with age plus 1:

search source=accounts | eval age = age + 1 | fields age;
age
33
37
29
34

Example 3: Create a new field with a field defined with the eval command

To create a new field ddAge. ddAge is the result of doubleAge multiplied by 2, where doubleAge is defined in the eval command:

search source=accounts | eval doubleAge = age * 2, ddAge = doubleAge * 2 | fields age, doubleAge, ddAge;

| age | doubleAge | ddAge :--- | :--- | | 32 | 64 | 128 | 36 | 72 | 144 | 28 | 56 | 112 | 33 | 66 | 132

Limitation

The eval command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.

fields

Use the fields command to keep or remove fields from a search result.

Syntax

fields [+|-] <field-list>
Field Description Required Default
index Plus (+) keeps only fields specified in the field list. Minus (-) removes all fields specified in the field list. No +
field list Specify a comma-delimited list of fields. Yes No default

Example 1: Select specified fields from result

To get account_number, firstname, and lastname fields from a search result:

search source=accounts | fields account_number, firstname, lastname;

| account_number | firstname | lastname :--- | :--- | | 1 | Amber | Duke | 6 | Hattie | Bond | 13 | Nanette | Bates | 18 | Dale | Adams

Example 2: Remove specified fields from a search result

To remove the account_number field from the search results:

search source=accounts | fields account_number, firstname, lastname | fields - account_number;
firstname lastname
Amber Duke
Hattie Bond
Nanette Bates
Dale Adams

parse

Use the parse command to parse a text field using regular expression and append the result to the search result.

Syntax

parse <field> <regular-expression>
Field Description Required
field A text field. Yes
regular-expression The regular expression used to extract new fields from the given test field. If a new field name exists, it will replace the original field. Yes

The regular expression is used to match the whole text field of each document with Java regex engine. Each named capture group in the expression will become a new STRING field.

Example 1: Create new field

The example shows how to create new field host for each document. host will be the hostname after @ in email field. Parsing a null field will return an empty string.

os> source=accounts | parse email '.+@(?<host>.+)' | fields email, host ;
fetched rows / total rows = 4/4
email host
amberduke@pyrami.com pyrami.com
hattiebond@netagy.com netagy.com
null null
daleadams@boink.com boink.com

Example 2: Override the existing field

The example shows how to override the existing address field with street number removed.

os> source=accounts | parse address '\d+ (?<address>.+)' | fields address ;
fetched rows / total rows = 4/4
address
Holmes Lane
Bristol Street
Madison Street
Hutchinson Court

Example 3: Filter and sort be casted parsed field

The example shows how to sort street numbers that are higher than 500 in address field.

os> source=accounts | parse address '(?<streetNumber>\d+) (?<street>.+)' | where cast(streetNumber as int) > 500 | sort num(streetNumber) | fields streetNumber, street ;
fetched rows / total rows = 3/3
streetNumber street
671 Bristol Street
789 Madison Street
880 Holmes Lane

Limitations

A few limitations exist when using the parse command:

  • Fields defined by parse cannot be parsed again. For example, source=accounts | parse address '\d+ (?<street>.+)' | parse street '\w+ (?<road>\w+)' ; will fail to return any expressions.
  • Fields defined by parse cannot be overridden with other commands. For example, when entering source=accounts | parse address '\d+ (?<street>.+)' | eval street='1' | where street='1' ; where will not match any documents since street cannot be overridden.
  • The text field used by parse cannot be overridden. For example, when entering source=accounts | parse address '\d+ (?<street>.+)' | eval address='1' ; street will not be parse since address is overridden.
  • Fields defined by parse cannot be filtered/sorted after using them in the stats command. For example, source=accounts | parse email '.+@(?<host>.+)' | stats avg(age) by host | where host=pyrami.com ; where will not parse the domain listed.

rename

Use the rename command to rename one or more fields in the search result.

Syntax

rename <source-field> AS <target-field>["," <source-field> AS <target-field>]...
Field Description Required
source-field The name of the field that you want to rename. Yes
target-field The name you want to rename to. Yes

Example 1: Rename one field

Rename the account_number field as an:

search source=accounts | rename account_number as an | fields an;
an
1
6
13
18

Example 2: Rename multiple fields

Rename the account_number field as an and employer as emp:

search source=accounts | rename account_number as an, employer as emp | fields an, emp;
an emp
1 Pyrami
6 Netagy
13 Quility
18 null

Limitations

The rename command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.

sort

Use the sort command to sort search results by a specified field.

Syntax

sort [count] <[+|-] sort-field>...

Field | Description | Required | Default :--- | :--- |:--- count | The maximum number results to return from the sorted result. If count=0, all results are returned. | No | 1000 [+|-] | Use plus [+] to sort by ascending order and minus [-] to sort by descending order. | No | Ascending order sort-field | Specify the field that you want to sort by. | Yes | -

Example 1: Sort by one field

To sort all documents by the age field in ascending order:

search source=accounts | sort age | fields account_number, age;
account_number age
13 28
1 32
18 33
6 36

Example 2: Sort by one field and return all results

To sort all documents by the age field in ascending order and specify count as 0 to get back all results:

search source=accounts | sort 0 age | fields account_number, age;
account_number age
13 28
1 32
18 33
6 36

Example 3: Sort by one field in descending order

To sort all documents by the age field in descending order:

search source=accounts | sort - age | fields account_number, age;
account_number age
6 36
18 33
1 32
13 28

Example 4: Specify the number of sorted documents to return

To sort all documents by the age field in ascending order and specify count as 2 to get back two results:

search source=accounts | sort 2 age | fields account_number, age;
account_number age
13 28
1 32

Example 5: Sort by multiple fields

To sort all documents by the gender field in ascending order and age field in descending order:

search source=accounts | sort + gender, - age | fields account_number, gender, age;
account_number gender age
13 F 28
6 M 36
18 M 33
1 M 32

stats

Use the stats command to aggregate from search results.

The following table lists the aggregation functions and also indicates how each one handles null or missing values:

Function NULL MISSING
COUNT Not counted Not counted
SUM Ignore Ignore
AVG Ignore Ignore
MAX Ignore Ignore
MIN Ignore Ignore

Syntax

stats <aggregation>... [by-clause]...

Field | Description | Required | Default :--- | :--- |:--- aggregation | Specify a statistical aggregation function. The argument of this function must be a field. | Yes | 1000 by-clause | Specify one or more fields to group the results by. If not specified, the stats command returns only one row, which is the aggregation over the entire result set. | No | -

Example 1: Calculate the average value of a field

To calculate the average age of all documents:

search source=accounts | stats avg(age);
avg(age)
32.25

Example 2: Calculate the average value of a field by group

To calculate the average age grouped by gender:

search source=accounts | stats avg(age) by gender;
gender avg(age)
F 28.0
M 33.666666666666664

Example 3: Calculate the average and sum of a field by group

To calculate the average and sum of age grouped by gender:

search source=accounts | stats avg(age), sum(age) by gender;

| gender | avg(age) | sum(age) :--- | :--- | | F | 28 | 28 | M | 33.666666666666664 | 101

Example 4: Calculate the maximum value of a field

To calculate the maximum age:

search source=accounts | stats max(age);
max(age)
36

Example 5: Calculate the maximum and minimum value of a field by group

To calculate the maximum and minimum age values grouped by gender:

search source=accounts | stats max(age), min(age) by gender;
gender min(age) max(age)
F 28 28
M 32 36

where

Use the where command with a bool expression to filter the search result. The where command only returns the result when the bool expression evaluates to true.

Syntax

where <boolean-expression>
Field Description Required
bool-expression An expression that evaluates to a boolean value. No

Example: Filter result set with a condition

To get all documents from the accounts index where account_number is 1 or gender is F:

search source=accounts | where account_number=1 or gender=\"F\" | fields account_number, gender;
account_number gender
1 M
13 F

head

Use the head command to return the first N number of results in a specified search order.

Syntax

head [N]

Field | Description | Required | Default :--- | :--- |:--- N | Specify the number of results to return. | No | 10

Example 1: Get the first 10 results

To get the first 10 results:

search source=accounts | fields firstname, age | head;
firstname age
Amber 32
Hattie 36
Nanette 28

Example 2: Get the first N results

To get the first two results:

search source=accounts | fields firstname, age | head 2;
firstname age
Amber 32
Hattie 36

Limitations

The head command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.

rare

Use the rare command to find the least common values of all fields in a field list. A maximum of 10 results are returned for each distinct set of values of the group-by fields.

Syntax

rare <field-list> [by-clause]
Field Description Required
field-list Specify a comma-delimited list of field names. No
by-clause Specify one or more fields to group the results by. No

Example 1: Find the least common values in a field

To find the least common values of gender:

search source=accounts | rare gender;
gender
F
M

Example 2: Find the least common values grouped by gender

To find the least common age grouped by gender:

search source=accounts | rare age by gender;
gender age
F 28
M 32
M 33

Limitations

The rare command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.

top

Use the top command to find the most common values of all fields in the field list.

Syntax

top [N] <field-list> [by-clause]
Field Description Default
N Specify the number of results to return. 10
field-list Specify a comma-delimited list of field names. -
by-clause Specify one or more fields to group the results by. -

Example 1: Find the most common values in a field

To find the most common genders:

search source=accounts | top gender;
gender
M
F

Example 2: Find the most common value in a field

To find the most common gender:

search source=accounts | top 1 gender;
gender
M

Example 3: Find the most common values grouped by gender

To find the most common age grouped by gender:

search source=accounts | top 1 age by gender;
gender age
F 28
M 32

Limitations

The top command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.

ad

The ad command applies the Random Cut Forest (RCF) algorithm in the ML Commons plugin on the search result returned by a PPL command. Based on the input, the plugin uses two types of RCF algorithms: fixed in time RCF for processing time-series data and batch RCF for processing non-time-series data.

Syntax: Fixed In Time RCF For Time-series Data Command

ad <shingle_size> <time_decay> <time_field>
Field Description Required
shingle_size A consecutive sequence of the most recent records. The default value is 8. No
time_decay Specifies how much of the recent past to consider when computing an anomaly score. The default value is 0.001. No
time_field Specifies the time filed for RCF to use as time-series data. Must be either a long value, such as the timestamp in miliseconds, or a string value in "yyyy-MM-dd HH:mm:ss". Yes

Syntax: Batch RCF for Non-time-series Data Command

ad <shingle_size> <time_decay>
Field Description Required
shingle_size A consecutive sequence of the most recent records. The default value is 8. No
time_decay Specifies how much of the recent past to consider when computing an anomaly score. The default value is 0.001. No

Example 1: Detecting events in New York City from taxi ridership data with time-series data

The example trains a RCF model and use the model to detect anomalies in the time-series ridership data.

PPL query:

os> source=nyc_taxi | fields value, timestamp | AD time_field='timestamp' | where value=10844.0
value timestamp score anomaly_grade
10844.0 1404172800000 0.0 0.0

Example 2: Detecting events in New York City from taxi ridership data with non-time-series data

PPL query:

os> source=nyc_taxi | fields value | AD | where value=10844.0
value score anomalous
10844.0 0.0 false

kmeans

The kmeans command applies the ML Commons plugin's kmeans algorithm to the provided PPL command's search results.

Syntax

kmeans <cluster-number>

For cluster-number, enter the number of clusters you want to group your data points into.

Example: Group Iris data

The example shows how to classify three Iris species (Iris setosa, Iris virginica and Iris versicolor) based on the combination of four features measured from each sample: the length and the width of the sepals and petals.

PPL query:

os> source=iris_data | fields sepal_length_in_cm, sepal_width_in_cm, petal_length_in_cm, petal_width_in_cm | kmeans centroids=3
sepal_length_in_cm sepal_width_in_cm petal_length_in_cm petal_width_in_cm ClusterID
5.1 3.5 1.4 0.2 1
5.6 3.0 4.1 1.3 0
6.7 2.5 5.8 1.8 2