773 lines
19 KiB
Markdown
773 lines
19 KiB
Markdown
---
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layout: default
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title: Commands
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parent: PPL – Piped Processing Language
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grand_parent: SQL and PPL
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nav_order: 2
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redirect_from:
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- /search-plugins/ppl/commands/
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---
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# Commands
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`PPL` supports all [`SQL` common]({{site.url}}{{site.baseurl}}/search-plugins/sql/functions/) functions, including [relevance search]({{site.url}}{{site.baseurl}}/search-plugins/sql/full-text/), but also introduces few more functions (called `commands`) which are available in `PPL` only.
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## dedup
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The `dedup` (data deduplication) command removes duplicate documents defined by a field from the search result.
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### Syntax
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```sql
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dedup [int] <field-list> [keepempty=<bool>] [consecutive=<bool>]
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```
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Field | Description | Type | Required | Default
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:--- | :--- |:--- |:--- |:---
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`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
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`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
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`consecutive` | If true, remove only consecutive events with duplicate combinations of values. | `Boolean` | No | False
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`field-list` | Specify a comma-delimited field list. At least one field is required. | `String` or comma-separated list of strings | Yes | -
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**Example 1: Dedup by one field**
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To remove duplicate documents with the same gender:
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```sql
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search source=accounts | dedup gender | fields account_number, gender;
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```
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| account_number | gender
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:--- | :--- |
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1 | M
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13 | F
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**Example 2: Keep two duplicate documents**
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To keep two duplicate documents with the same gender:
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```sql
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search source=accounts | dedup 2 gender | fields account_number, gender;
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```
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| account_number | gender
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:--- | :--- |
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1 | M
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6 | M
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13 | F
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**Example 3: Keep or ignore an empty field by default**
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To keep two duplicate documents with a `null` field value:
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```sql
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search source=accounts | dedup email keepempty=true | fields account_number, email;
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```
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| account_number | email
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:--- | :--- |
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1 | amberduke@pyrami.com
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6 | hattiebond@netagy.com
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13 | null
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18 | daleadams@boink.com
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To remove duplicate documents with the `null` field value:
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```sql
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search source=accounts | dedup email | fields account_number, email;
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```
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| account_number | email
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:--- | :--- |
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1 | amberduke@pyrami.com
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6 | hattiebond@netagy.com
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18 | daleadams@boink.com
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**Example 4: Dedup of consecutive documents**
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To remove duplicates of consecutive documents:
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```sql
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search source=accounts | dedup gender consecutive=true | fields account_number, gender;
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```
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| account_number | gender
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:--- | :--- |
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1 | M
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13 | F
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18 | M
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### Limitations
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The `dedup` command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.
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## eval
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The `eval` command evaluates an expression and appends its result to the search result.
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### Syntax
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```sql
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eval <field>=<expression> ["," <field>=<expression> ]...
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```
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Field | Description | Required
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:--- | :--- |:---
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`field` | If a field name does not exist, a new field is added. If the field name already exists, it's overwritten. | Yes
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`expression` | Specify any supported expression. | Yes
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**Example 1: Create a new field**
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To create a new `doubleAge` field for each document. `doubleAge` is the result of `age` multiplied by 2:
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```sql
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search source=accounts | eval doubleAge = age * 2 | fields age, doubleAge;
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```
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| age | doubleAge
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:--- | :--- |
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32 | 64
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36 | 72
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28 | 56
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33 | 66
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*Example 2*: Overwrite the existing field
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To overwrite the `age` field with `age` plus 1:
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```sql
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search source=accounts | eval age = age + 1 | fields age;
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```
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| age
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:--- |
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| 33
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| 37
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| 29
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| 34
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**Example 3: Create a new field with a field defined with the `eval` command**
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To create a new field `ddAge`. `ddAge` is the result of `doubleAge` multiplied by 2, where `doubleAge` is defined in the `eval` command:
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```sql
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search source=accounts | eval doubleAge = age * 2, ddAge = doubleAge * 2 | fields age, doubleAge, ddAge;
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```
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| age | doubleAge | ddAge
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:--- | :--- |
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| 32 | 64 | 128
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| 36 | 72 | 144
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| 28 | 56 | 112
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| 33 | 66 | 132
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### Limitation
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The ``eval`` command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.
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## fields
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Use the `fields` command to keep or remove fields from a search result.
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### Syntax
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```sql
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fields [+|-] <field-list>
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```
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Field | Description | Required | Default
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:--- | :--- |:---|:---
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`index` | Plus (+) keeps only fields specified in the field list. Minus (-) removes all fields specified in the field list. | No | +
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`field list` | Specify a comma-delimited list of fields. | Yes | No default
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**Example 1: Select specified fields from result**
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To get `account_number`, `firstname`, and `lastname` fields from a search result:
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```sql
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search source=accounts | fields account_number, firstname, lastname;
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```
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| account_number | firstname | lastname
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:--- | :--- |
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| 1 | Amber | Duke
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| 6 | Hattie | Bond
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| 13 | Nanette | Bates
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| 18 | Dale | Adams
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**Example 2: Remove specified fields from a search result**
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To remove the `account_number` field from the search results:
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```sql
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search source=accounts | fields account_number, firstname, lastname | fields - account_number;
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```
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| firstname | lastname
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:--- | :--- |
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| Amber | Duke
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| Hattie | Bond
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| Nanette | Bates
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| Dale | Adams
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## parse
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Use the `parse` command to parse a text field using regular expression and append the result to the search result.
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### Syntax
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```sql
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parse <field> <regular-expression>
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```
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Field | Description | Required
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:--- | :--- |:---
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field | A text field. | Yes
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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
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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.
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**Example 1: Create new field**
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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.
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```sql
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os> source=accounts | parse email '.+@(?<host>.+)' | fields email, host ;
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fetched rows / total rows = 4/4
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```
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| email | host
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:--- | :--- |
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| amberduke@pyrami.com | pyrami.com
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| hattiebond@netagy.com | netagy.com
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| null | null
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| daleadams@boink.com | boink.com
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*Example 2*: Override the existing field
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The example shows how to override the existing address field with street number removed.
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```sql
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os> source=accounts | parse address '\d+ (?<address>.+)' | fields address ;
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fetched rows / total rows = 4/4
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```
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| address
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:--- |
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| Holmes Lane
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| Bristol Street
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| Madison Street
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| Hutchinson Court
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**Example 3: Filter and sort be casted parsed field**
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The example shows how to sort street numbers that are higher than 500 in address field.
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```sql
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os> source=accounts | parse address '(?<streetNumber>\d+) (?<street>.+)' | where cast(streetNumber as int) > 500 | sort num(streetNumber) | fields streetNumber, street ;
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fetched rows / total rows = 3/3
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```
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| streetNumber | street
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:--- | :--- |
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| 671 | Bristol Street
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| 789 | Madison Street
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| 880 | Holmes Lane
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### Limitations
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A few limitations exist when using the parse command:
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- 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.
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- 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.
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- 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.
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- 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.
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## rename
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Use the `rename` command to rename one or more fields in the search result.
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### Syntax
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```sql
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rename <source-field> AS <target-field>["," <source-field> AS <target-field>]...
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```
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Field | Description | Required
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:--- | :--- |:---
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`source-field` | The name of the field that you want to rename. | Yes
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`target-field` | The name you want to rename to. | Yes
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**Example 1: Rename one field**
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Rename the `account_number` field as `an`:
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```sql
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search source=accounts | rename account_number as an | fields an;
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```
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| an
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:--- |
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| 1
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**Example 2: Rename multiple fields**
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Rename the `account_number` field as `an` and `employer` as `emp`:
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```sql
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search source=accounts | rename account_number as an, employer as emp | fields an, emp;
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```
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| an | emp
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:--- | :--- |
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| 1 | Pyrami
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| 6 | Netagy
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| 13 | Quility
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| 18 | null
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### Limitations
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The `rename` command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.
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## sort
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Use the `sort` command to sort search results by a specified field.
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### Syntax
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```sql
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sort [count] <[+|-] sort-field>...
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```
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Field | Description | Required | Default
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:--- | :--- |:---
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`count` | The maximum number results to return from the sorted result. If count=0, all results are returned. | No | 1000
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`[+|-]` | Use plus [+] to sort by ascending order and minus [-] to sort by descending order. | No | Ascending order
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`sort-field` | Specify the field that you want to sort by. | Yes | -
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**Example 1: Sort by one field**
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To sort all documents by the `age` field in ascending order:
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```sql
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search source=accounts | sort age | fields account_number, age;
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```
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| account_number | age |
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:--- | :--- |
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| 13 | 28
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| 1 | 32
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| 18 | 33
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| 6 | 36
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**Example 2: Sort by one field and return all results**
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To sort all documents by the `age` field in ascending order and specify count as 0 to get back all results:
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```sql
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search source=accounts | sort 0 age | fields account_number, age;
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```
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| account_number | age |
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:--- | :--- |
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| 13 | 28
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| 1 | 32
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| 18 | 33
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| 6 | 36
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**Example 3: Sort by one field in descending order**
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To sort all documents by the `age` field in descending order:
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```sql
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search source=accounts | sort - age | fields account_number, age;
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```
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| account_number | age |
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:--- | :--- |
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| 6 | 36
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| 18 | 33
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| 1 | 32
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| 13 | 28
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**Example 4: Specify the number of sorted documents to return**
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To sort all documents by the `age` field in ascending order and specify count as 2 to get back two results:
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```sql
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search source=accounts | sort 2 age | fields account_number, age;
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```
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| account_number | age |
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:--- | :--- |
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| 13 | 28
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| 1 | 32
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**Example 5: Sort by multiple fields**
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To sort all documents by the `gender` field in ascending order and `age` field in descending order:
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```sql
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search source=accounts | sort + gender, - age | fields account_number, gender, age;
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```
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| account_number | gender | age |
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:--- | :--- | :--- |
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| 13 | F | 28
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| 6 | M | 36
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| 18 | M | 33
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| 1 | M | 32
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## stats
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Use the `stats` command to aggregate from search results.
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The following table lists the aggregation functions and also indicates how each one handles null or missing values:
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Function | NULL | MISSING
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:--- | :--- |:---
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`COUNT` | Not counted | Not counted
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`SUM` | Ignore | Ignore
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`AVG` | Ignore | Ignore
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`MAX` | Ignore | Ignore
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`MIN` | Ignore | Ignore
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### Syntax
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```
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stats <aggregation>... [by-clause]...
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```
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Field | Description | Required | Default
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:--- | :--- |:---
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`aggregation` | Specify a statistical aggregation function. The argument of this function must be a field. | Yes | 1000
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`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 | -
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**Example 1: Calculate the average value of a field**
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To calculate the average `age` of all documents:
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```sql
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search source=accounts | stats avg(age);
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```
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| avg(age)
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:--- |
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| 32.25
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**Example 2: Calculate the average value of a field by group**
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To calculate the average age grouped by gender:
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```sql
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search source=accounts | stats avg(age) by gender;
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```
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| gender | avg(age)
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:--- | :--- |
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| F | 28.0
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| M | 33.666666666666664
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**Example 3: Calculate the average and sum of a field by group**
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To calculate the average and sum of age grouped by gender:
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```sql
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search source=accounts | stats avg(age), sum(age) by gender;
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```
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| gender | avg(age) | sum(age)
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:--- | :--- |
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| F | 28 | 28
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| M | 33.666666666666664 | 101
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**Example 4: Calculate the maximum value of a field**
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To calculate the maximum age:
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```sql
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search source=accounts | stats max(age);
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```
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| max(age)
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:--- |
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| 36
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**Example 5: Calculate the maximum and minimum value of a field by group**
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To calculate the maximum and minimum age values grouped by gender:
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```sql
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search source=accounts | stats max(age), min(age) by gender;
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```
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| gender | min(age) | max(age)
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:--- | :--- | :--- |
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| F | 28 | 28
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| M | 32 | 36
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## where
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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.
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### Syntax
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```sql
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where <boolean-expression>
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```
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Field | Description | Required
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:--- | :--- |:---
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`bool-expression` | An expression that evaluates to a boolean value. | No
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**Example: Filter result set with a condition**
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To get all documents from the `accounts` index where `account_number` is 1 or gender is `F`:
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```sql
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search source=accounts | where account_number=1 or gender=\"F\" | fields account_number, gender;
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```
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| account_number | gender
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:--- | :--- |
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| 1 | M
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| 13 | F
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## head
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Use the `head` command to return the first N number of results in a specified search order.
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### Syntax
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```sql
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head [N]
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```
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Field | Description | Required | Default
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:--- | :--- |:---
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`N` | Specify the number of results to return. | No | 10
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**Example 1: Get the first 10 results**
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To get the first 10 results:
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```sql
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search source=accounts | fields firstname, age | head;
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```
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| firstname | age
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:--- | :--- |
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| Amber | 32
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| Hattie | 36
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| Nanette | 28
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**Example 2: Get the first N results**
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To get the first two results:
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```sql
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search source=accounts | fields firstname, age | head 2;
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```
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| firstname | age
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:--- | :--- |
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| Amber | 32
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| Hattie | 36
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### Limitations
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|
|
|
The `head` command is not rewritten to OpenSearch DSL, it is only executed on the coordination node.
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## rare
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|
Use the `rare` command to find the least common values of all fields in a field list.
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|
A maximum of 10 results are returned for each distinct set of values of the group-by fields.
|
|
|
|
### Syntax
|
|
|
|
```sql
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|
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:
|
|
|
|
```sql
|
|
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:
|
|
|
|
```sql
|
|
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 {#top-command}
|
|
|
|
Use the `top` command to find the most common values of all fields in the field list.
|
|
|
|
### Syntax
|
|
|
|
```sql
|
|
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:
|
|
|
|
```sql
|
|
search source=accounts | top gender;
|
|
```
|
|
|
|
| gender
|
|
:--- |
|
|
| M
|
|
| F
|
|
|
|
**Example 2: Find the most common value in a field**
|
|
|
|
To find the most common gender:
|
|
|
|
```sql
|
|
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:
|
|
|
|
```sql
|
|
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]({{site.url}}{{site.baseurl}}/ml-commons-plugin/index/) 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
|
|
|
|
```sql
|
|
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
|
|
|
|
```sql
|
|
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:
|
|
|
|
```sql
|
|
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:
|
|
|
|
```sql
|
|
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
|
|
|
|
```sql
|
|
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:
|
|
|
|
```sql
|
|
os> source=iris_data | fields sepal_length_in_cm, sepal_width_in_cm, petal_length_in_cm, petal_width_in_cm | kmeans 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
|