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apl/aggregation-function/statistical-functions.mdx

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title: 'Aggregation functions'
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description: 'This section explains how to use and combine different aggregation functions in APL.'
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sidebarTitle: Overview
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tags:
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['axiom documentation', 'documentation', 'axiom', 'avg', 'avgif', 'count', 'countif', 'dcount', 'max', 'maxif', 'min', 'minif', 'sum', 'sumif', 'histogram', 'topk', 'percentile', 'variance', 'stdev', 'make_list', 'rate']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'avg', 'avgif', 'count', 'countif', 'dcount', 'max', 'maxif', 'min', 'minif', 'sum', 'sumif', 'histogram', 'topk', 'percentile', 'variance', 'stdev', 'make_list', 'rate']
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The table summarizes the aggregation functions available in APL. Use all these aggregation functions in the context of the [summarize operator](/apl/tabular-operators/summarize-operator).

apl/data-types/map-fields.mdx

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---
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title: 'Map fields'
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description: 'This page explains what map fields are and how to query them.'
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tags: ['axiom documentation', 'documentation', 'axiom', 'map fields', 'object fields', 'data types']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'map fields', 'object fields', 'data types']
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import ReplaceDomain from "/snippets/replace-domain.mdx"

apl/data-types/null-values.mdx

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title: 'Null values'
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description: 'This page explains how APL represents missing values.'
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tags: ['axiom documentation', 'documentation', 'axiom', 'scalar', 'null', 'datetime', 'dynamic', 'guid', 'int']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'scalar', 'null', 'datetime', 'dynamic', 'guid', 'int']
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All scalar data types in APL have a special value that represents a missing value. This value is called the null value, or null.

apl/data-types/scalar-data-types.mdx

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title: 'Scalar data types'
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description: 'This page explains the data types in APL.'
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tags: ['axiom documentation', 'documentation', 'axiom', 'scalar', 'data types', 'bool', 'datetime', 'dynamic', 'int', 'long', 'string', 'timespan']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'scalar', 'data types', 'bool', 'datetime', 'dynamic', 'int', 'long', 'string', 'timespan']
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Axiom Processing Language supplies a set of system data types that define all the types of data that can be used with APL.

apl/entities/entity-names.mdx

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title: 'Entity names'
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description: 'This page explains how to use entity names in your APL query.'
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tags: ['axiom documentation', 'documentation', 'axiom', 'scalar', 'columns', 'identifier', 'entity names', 'identifier quoting']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'scalar', 'columns', 'identifier', 'entity names', 'identifier quoting']
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APL entities (datasets, tables, columns, and operators) are named. For example, two fields or columns in the same dataset can have the same name if the casing is different, and a table and a dataset may have the same name because they aren’t in the same scope.

apl/guides/migrating-from-sql-to-apl.mdx

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title: "Migrate from SQL to APL"
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description: "This guide will help you through migrating SQL to APL, helping you understand key differences and providing you with query examples."
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sidebarTitle: SQL
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tags: ['axiom documentation', 'documentation', 'axiom', 'apl', 'sql', 'guide', 'migration guide', 'sql query']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'apl', 'sql', 'guide', 'migration guide', 'sql query']
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## Introduction

apl/guides/migrating-from-sumologic-to-apl.mdx

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title: 'Migrate from Sumo Logic Query Language to APL'
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description: 'This guide dives into why APL could be a superior choice for your data needs, and the differences between Sumo Logic and APL.'
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sidebarTitle: Sumo Logic
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tags: ['axiom documentation', 'documentation', 'axiom', 'apl', 'sumo logic', 'scalability', 'performance', 'parse', 'extract']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'apl', 'sumo logic', 'scalability', 'performance', 'parse', 'extract']
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## Introduction

apl/guides/splunk-cheat-sheet.mdx

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title: 'Migrate from Splunk SPL to APL'
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description: 'This step-by-step guide provides a high-level mapping from Splunk SPL to APL.'
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sidebarTitle: Splunk SPL
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tags: ['axiom documentation', 'documentation', 'axiom', 'splunk', 'apl', 'searching', 'aggregation', 'time frames', 'sorting', 'functions']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'splunk', 'apl', 'searching', 'aggregation', 'time frames', 'sorting', 'functions']
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Splunk and Axiom are powerful tools for log analysis and data exploration. The data explorer interface uses Axiom Processing Language (APL). There are some differences between the query languages for Splunk and Axiom. When transitioning from Splunk to APL, you will need to understand how to convert your Splunk SPL queries into APL.

apl/introduction.mdx

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description: 'This section explains how to use the Axiom Processing Language to get deeper insights from your data.'
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sidebarTitle: Introduction
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icon: door-open
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tags: ['axiom documentation', 'documentation', 'axiom', 'APL', 'axiom processing language', 'data explorer', 'getiing started guide', 'summarize', 'filter']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'APL', 'axiom processing language', 'data explorer', 'getiing started guide', 'summarize', 'filter']
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import Prerequisites from "/snippets/minimal-prerequisites.mdx"

apl/query-statement/set-statement.mdx

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title: 'Set statement'
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description: 'The set statement is used to set a query option in your APL query.'
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tags: ['axiom documentation', 'documentation', 'axiom', 'set statement', 'strict types']
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keywords: ['axiom documentation', 'documentation', 'axiom', 'set statement', 'strict types']
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The `set` statement is used to set a query option. Options enabled with the `set` statement only have effect for the duration of the query.

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