mirror of
https://codeberg.org/scip/esctl.git
synced 2026-08-24 01:34:17 +02:00
add feature esql search (#90)
This commit is contained in:
@@ -576,6 +576,7 @@ version - show esctl version information
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debug - developer only
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help-jsonpath - show jsonpath help
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help-usage - show overview of all available commands
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help-esql - show esql help
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```
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# Development
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@@ -24,10 +24,11 @@ import (
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"github.com/go-openapi/swag/loading"
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)
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//go:embed *.json
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//go:embed *.json *.md
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var AssetFS embed.FS
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var OpenAPI *loads.Document
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var EsQlCheatSheet string
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func LoadAssetOpenApi() {
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doc, err := loads.Spec(
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@@ -41,3 +42,12 @@ func LoadAssetOpenApi() {
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OpenAPI = doc
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}
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func LoadEsql() {
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md, err := AssetFS.ReadFile("esql.md")
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if err != nil {
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panic(err)
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}
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EsQlCheatSheet = string(md)
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}
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951
assets/esql.md
Normal file
951
assets/esql.md
Normal file
@@ -0,0 +1,951 @@
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<!-- courtesy https://github.com/linkan-per/ES-QL-Cheat-Sheet by |linkan-per -->
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# ES|QL (Elasticsearch Query Language) Cheat Sheet
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## Table of Contents
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1. [Introduction](#introduction)
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2. [Basic Query Structure](#basic-query-structure)
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3. [Source Commands](#source-commands)
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4. [Processing Commands](#processing-commands)
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5. [Data Selection & Filtering](#data-selection--filtering)
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6. [Aggregations & Statistics](#aggregations--statistics)
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7. [String Functions](#string-functions)
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8. [Mathematical Functions](#mathematical-functions)
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9. [Date/Time Functions](#datetime-functions)
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10. [Type Conversion Functions](#type-conversion-functions)
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11. [Conditional Functions](#conditional-functions)
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12. [Array Functions](#array-functions)
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13. [Join Operations (LOOKUP)](#join-operations-lookup)
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14. [Sorting & Limiting](#sorting--limiting)
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15. [Grouping & Aggregating](#grouping--aggregating)
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16. [Advanced Patterns](#advanced-patterns)
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---
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## Introduction
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ES|QL is Elasticsearch's new query language designed for data exploration, analysis, and transformation. It uses a pipe (`|`) syntax to chain commands together.
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**Basic Syntax:**
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```
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FROM <data-source>
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| <processing-command>
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| <processing-command>
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| ...
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```
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---
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## Basic Query Structure
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### Simple Query
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```esql
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FROM logs-*
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| LIMIT 10
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```
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### Query with Multiple Commands
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```esql
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FROM employees
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| WHERE department == "Engineering"
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| KEEP name, salary, hire_date
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| SORT salary DESC
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| LIMIT 5
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```
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---
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## Source Commands
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### FROM - Specify Data Source
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```esql
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// From a single index
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FROM logs-2024
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// From multiple indices with wildcard
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FROM logs-*, metrics-*
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// From specific indices
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FROM index1, index2, index3
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// With metadata
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FROM logs-* METADATA _id, _index
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```
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### ROW - Generate Inline Data
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```esql
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// Create a single row
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ROW name = "John", age = 30, city = "NYC"
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// Multiple rows
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ROW a = 1, b = "x"
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| EVAL c = a * 10
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```
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---
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## Processing Commands
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### KEEP - Select Specific Fields
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```esql
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FROM employees
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| KEEP name, department, salary
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// Keep with pattern
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FROM logs-*
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| KEEP @timestamp, message, host.*
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```
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### DROP - Remove Specific Fields
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```esql
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FROM employees
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| DROP password, ssn, internal_notes
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// Drop with pattern
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FROM logs-*
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| DROP *.keyword
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```
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### RENAME - Rename Fields
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```esql
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FROM employees
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| RENAME emp_name AS name, emp_dept AS department
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// Multiple renames
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FROM logs-*
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| RENAME source.ip AS src_ip, destination.ip AS dst_ip
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```
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---
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## Data Selection & Filtering
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### WHERE - Filter Rows
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```esql
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// Equality
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FROM employees
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| WHERE department == "Sales"
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// Comparison operators
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FROM products
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| WHERE price > 100 AND stock < 50
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// IS NULL / IS NOT NULL
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FROM logs-*
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| WHERE error_code IS NOT NULL
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// IN operator
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FROM employees
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| WHERE department IN ("Sales", "Marketing", "HR")
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// LIKE operator (wildcards)
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FROM logs-*
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| WHERE message LIKE "*error*"
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// RLIKE operator (regex)
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FROM logs-*
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| WHERE message RLIKE "error|exception|failure"
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// NOT operator
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FROM employees
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| WHERE NOT department == "IT"
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// Multiple conditions
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FROM orders
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| WHERE status == "completed"
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AND total_amount > 1000
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AND order_date >= "2024-01-01"
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```
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---
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## Aggregations & Statistics
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### STATS - Aggregate Functions
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#### COUNT
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```esql
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// Count all rows
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FROM logs-*
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| STATS count = COUNT()
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// Count distinct
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FROM employees
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| STATS unique_departments = COUNT_DISTINCT(department)
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// Count by group
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FROM logs-*
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| STATS event_count = COUNT() BY log_level
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```
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#### SUM, AVG, MIN, MAX
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```esql
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FROM sales
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| STATS
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total_revenue = SUM(amount),
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avg_sale = AVG(amount),
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min_sale = MIN(amount),
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max_sale = MAX(amount)
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// With grouping
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FROM sales
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| STATS
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total = SUM(amount),
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average = AVG(amount)
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BY product_category
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```
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#### MEDIAN, PERCENTILE
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```esql
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FROM response_times
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| STATS
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median_time = MEDIAN(duration),
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p95 = PERCENTILE(duration, 95),
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p99 = PERCENTILE(duration, 99)
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```
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#### Multiple Aggregations
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```esql
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FROM orders
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| STATS
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order_count = COUNT(),
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total_revenue = SUM(amount),
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avg_order_value = AVG(amount),
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unique_customers = COUNT_DISTINCT(customer_id)
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BY region, product_category
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```
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---
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## String Functions
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### CONCAT - Concatenate Strings
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```esql
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FROM employees
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| EVAL full_name = CONCAT(first_name, " ", last_name)
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// With separator
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FROM logs-*
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| EVAL log_info = CONCAT(level, ": ", message)
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```
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### SUBSTRING - Extract Substring
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```esql
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FROM employees
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| EVAL first_initial = SUBSTRING(first_name, 0, 1)
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// Extract with length
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FROM products
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| EVAL short_code = SUBSTRING(product_id, 0, 5)
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```
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### LENGTH - String Length
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```esql
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FROM messages
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| EVAL message_length = LENGTH(message)
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| WHERE message_length > 100
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```
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### TRIM, LTRIM, RTRIM - Remove Whitespace
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```esql
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FROM user_input
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| EVAL cleaned = TRIM(input_field)
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| EVAL left_trimmed = LTRIM(input_field)
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| EVAL right_trimmed = RTRIM(input_field)
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```
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### UPPER, LOWER - Case Conversion
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```esql
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FROM employees
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| EVAL name_upper = UPPER(name)
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| EVAL email_lower = LOWER(email)
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```
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### REPLACE - Replace String
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```esql
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FROM logs-*
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| EVAL cleaned_message = REPLACE(message, "ERROR", "Warning")
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```
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### SPLIT - Split String into Array
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```esql
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FROM logs-*
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| EVAL tags_array = SPLIT(tags, ",")
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```
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### STARTS_WITH, ENDS_WITH
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```esql
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FROM files
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| WHERE STARTS_WITH(filename, "log_")
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| WHERE ENDS_WITH(filename, ".txt")
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```
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---
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## Mathematical Functions
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### Basic Operations
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```esql
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FROM sales
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| EVAL
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total = price * quantity,
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discount_price = price * 0.9,
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tax = price * 0.08
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// Multiple operations
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FROM metrics
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| EVAL
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sum_val = field1 + field2,
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diff_val = field1 - field2,
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product = field1 * field2,
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ratio = field1 / field2,
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remainder = field1 % field2
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```
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### ABS - Absolute Value
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```esql
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FROM transactions
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| EVAL abs_amount = ABS(transaction_amount)
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```
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### ROUND, FLOOR, CEIL
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```esql
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FROM measurements
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| EVAL
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rounded = ROUND(value, 2),
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floored = FLOOR(value),
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ceiled = CEIL(value)
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```
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### POW - Power
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```esql
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FROM data
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| EVAL squared = POW(value, 2)
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| EVAL cubed = POW(value, 3)
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```
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### SQRT - Square Root
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```esql
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FROM measurements
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| EVAL sqrt_value = SQRT(value)
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```
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### LOG, LOG10
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```esql
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FROM data
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| EVAL
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natural_log = LOG(value),
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log_base_10 = LOG10(value)
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```
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### GREATEST, LEAST
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```esql
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FROM comparisons
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| EVAL
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max_val = GREATEST(val1, val2, val3),
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min_val = LEAST(val1, val2, val3)
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```
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---
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## Date/Time Functions
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||||
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### NOW - Current Timestamp
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||||
```esql
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FROM logs-*
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| EVAL current_time = NOW()
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```
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||||
### DATE_EXTRACT - Extract Date Parts
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```esql
|
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FROM events
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| EVAL
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||||
year = DATE_EXTRACT("year", @timestamp),
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||||
month = DATE_EXTRACT("month", @timestamp),
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day = DATE_EXTRACT("day", @timestamp),
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hour = DATE_EXTRACT("hour", @timestamp),
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minute = DATE_EXTRACT("minute", @timestamp),
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day_of_week = DATE_EXTRACT("day_of_week", @timestamp)
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```
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### DATE_FORMAT - Format Date
|
||||
```esql
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FROM events
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||||
| EVAL formatted_date = DATE_FORMAT("yyyy-MM-dd", @timestamp)
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||||
| EVAL custom_format = DATE_FORMAT("MMM dd, yyyy HH:mm", @timestamp)
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||||
```
|
||||
|
||||
### DATE_TRUNC - Truncate Date
|
||||
```esql
|
||||
FROM logs-*
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| EVAL
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||||
hour_bucket = DATE_TRUNC("hour", @timestamp),
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||||
day_bucket = DATE_TRUNC("day", @timestamp),
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||||
month_bucket = DATE_TRUNC("month", @timestamp)
|
||||
```
|
||||
|
||||
### DATE_DIFF - Date Difference
|
||||
```esql
|
||||
FROM orders
|
||||
| EVAL days_since_order = DATE_DIFF("days", order_date, NOW())
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||||
| EVAL hours_to_delivery = DATE_DIFF("hours", order_date, delivery_date)
|
||||
```
|
||||
|
||||
### DATE_PARSE - Parse String to Date
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL parsed_date = DATE_PARSE("yyyy-MM-dd", date_string)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Type Conversion Functions
|
||||
|
||||
### TO_STRING - Convert to String
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL id_string = TO_STRING(id)
|
||||
| EVAL amount_string = TO_STRING(amount)
|
||||
```
|
||||
|
||||
### TO_INTEGER, TO_LONG - Convert to Integer
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL age_int = TO_INTEGER(age_string)
|
||||
| EVAL id_long = TO_LONG(id_string)
|
||||
```
|
||||
|
||||
### TO_DOUBLE - Convert to Double
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL price_double = TO_DOUBLE(price_string)
|
||||
```
|
||||
|
||||
### TO_BOOLEAN - Convert to Boolean
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL is_active = TO_BOOLEAN(active_string)
|
||||
```
|
||||
|
||||
### TO_DATETIME - Convert to DateTime
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL timestamp = TO_DATETIME(date_string)
|
||||
```
|
||||
|
||||
### TO_IP - Convert to IP Address
|
||||
```esql
|
||||
FROM logs-*
|
||||
| EVAL ip_address = TO_IP(ip_string)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Conditional Functions
|
||||
|
||||
### CASE - Conditional Logic
|
||||
```esql
|
||||
FROM employees
|
||||
| EVAL salary_grade = CASE(
|
||||
salary < 50000, "Entry",
|
||||
salary < 80000, "Mid",
|
||||
salary < 120000, "Senior",
|
||||
"Executive"
|
||||
)
|
||||
|
||||
// With multiple conditions
|
||||
FROM orders
|
||||
| EVAL order_status = CASE(
|
||||
status == "pending" AND days_old > 7, "Overdue",
|
||||
status == "pending", "Processing",
|
||||
status == "shipped", "In Transit",
|
||||
status == "delivered", "Completed",
|
||||
"Unknown"
|
||||
)
|
||||
```
|
||||
|
||||
### COALESCE - Return First Non-Null Value
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL display_name = COALESCE(nickname, first_name, username, "Unknown")
|
||||
```
|
||||
|
||||
### IF - Simple Conditional
|
||||
```esql
|
||||
FROM products
|
||||
| EVAL stock_status =
|
||||
CASE(stock > 0, "Available", "Out of Stock")
|
||||
|
||||
// Nested conditions
|
||||
FROM employees
|
||||
| EVAL bonus = CASE(
|
||||
performance_rating >= 4.5, salary * 0.15,
|
||||
performance_rating >= 3.5, salary * 0.10,
|
||||
performance_rating >= 2.5, salary * 0.05,
|
||||
0
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Array Functions
|
||||
|
||||
### MV_COUNT - Count Array Elements
|
||||
```esql
|
||||
FROM logs-*
|
||||
| EVAL tag_count = MV_COUNT(tags)
|
||||
| WHERE tag_count > 3
|
||||
```
|
||||
|
||||
### MV_AVG, MV_SUM, MV_MIN, MV_MAX - Array Aggregations
|
||||
```esql
|
||||
FROM metrics
|
||||
| EVAL
|
||||
avg_value = MV_AVG(values),
|
||||
total = MV_SUM(values),
|
||||
min_value = MV_MIN(values),
|
||||
max_value = MV_MAX(values)
|
||||
```
|
||||
|
||||
### MV_CONCAT - Concatenate Array Elements
|
||||
```esql
|
||||
FROM logs-*
|
||||
| EVAL all_tags = MV_CONCAT(tags, ", ")
|
||||
```
|
||||
|
||||
### MV_DEDUPE - Remove Duplicates from Array
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL unique_values = MV_DEDUPE(values)
|
||||
```
|
||||
|
||||
### MV_FIRST, MV_LAST - Get First/Last Element
|
||||
```esql
|
||||
FROM logs-*
|
||||
| EVAL first_tag = MV_FIRST(tags)
|
||||
| EVAL last_tag = MV_LAST(tags)
|
||||
```
|
||||
|
||||
### MV_SLICE - Extract Array Slice
|
||||
```esql
|
||||
FROM data
|
||||
| EVAL first_three = MV_SLICE(values, 0, 3)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Join Operations (LOOKUP)
|
||||
|
||||
ES|QL uses ENRICH (similar to LOOKUP/JOIN) to join data from enrich policies.
|
||||
|
||||
### Prerequisites: Create Enrich Policy
|
||||
First, create an enrich policy in Kibana Dev Tools:
|
||||
|
||||
```json
|
||||
PUT /_enrich/policy/user_lookup
|
||||
{
|
||||
"match": {
|
||||
"indices": "users",
|
||||
"match_field": "user_id",
|
||||
"enrich_fields": ["username", "email", "department"]
|
||||
}
|
||||
}
|
||||
|
||||
POST /_enrich/policy/user_lookup/_execute
|
||||
```
|
||||
|
||||
### ENRICH - Join/Lookup Data
|
||||
```esql
|
||||
FROM logs-*
|
||||
| ENRICH user_lookup ON user_id
|
||||
| KEEP @timestamp, user_id, username, email, message
|
||||
|
||||
// With field renaming
|
||||
FROM transactions
|
||||
| ENRICH product_lookup ON product_id WITH product_name, category, price
|
||||
| KEEP transaction_id, product_name, category, quantity, price
|
||||
|
||||
// Multiple enrichments
|
||||
FROM orders
|
||||
| ENRICH customer_lookup ON customer_id WITH customer_name, customer_tier
|
||||
| ENRICH product_lookup ON product_id WITH product_name, product_category
|
||||
| KEEP order_id, customer_name, product_name, order_amount
|
||||
```
|
||||
|
||||
### Complex Join Example
|
||||
```esql
|
||||
FROM orders
|
||||
| ENRICH customer_lookup ON customer_id
|
||||
WITH customer_name, customer_email, customer_segment
|
||||
| ENRICH product_lookup ON product_id
|
||||
WITH product_name, product_category, product_price
|
||||
| EVAL total_price = quantity * product_price
|
||||
| WHERE customer_segment == "Premium"
|
||||
| STATS
|
||||
total_orders = COUNT(),
|
||||
total_revenue = SUM(total_price)
|
||||
BY customer_name, product_category
|
||||
| SORT total_revenue DESC
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Sorting & Limiting
|
||||
|
||||
### SORT - Order Results
|
||||
```esql
|
||||
// Ascending order (default)
|
||||
FROM employees
|
||||
| SORT salary
|
||||
|
||||
// Descending order
|
||||
FROM employees
|
||||
| SORT salary DESC
|
||||
|
||||
// Multiple fields
|
||||
FROM employees
|
||||
| SORT department ASC, salary DESC
|
||||
|
||||
// With nulls first/last
|
||||
FROM data
|
||||
| SORT value DESC NULLS FIRST
|
||||
```
|
||||
|
||||
### LIMIT - Limit Results
|
||||
```esql
|
||||
// Get first 10 rows
|
||||
FROM logs-*
|
||||
| LIMIT 10
|
||||
|
||||
// Top 5 highest salaries
|
||||
FROM employees
|
||||
| SORT salary DESC
|
||||
| LIMIT 5
|
||||
|
||||
// Pagination (skip and limit)
|
||||
FROM products
|
||||
| SORT price
|
||||
| LIMIT 20 // Results 0-19
|
||||
```
|
||||
|
||||
### HEAD - Get First N Rows (Alias for LIMIT)
|
||||
```esql
|
||||
FROM logs-*
|
||||
| HEAD 100
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Grouping & Aggregating
|
||||
|
||||
### GROUP BY with STATS
|
||||
```esql
|
||||
// Single field grouping
|
||||
FROM sales
|
||||
| STATS total_sales = SUM(amount) BY region
|
||||
|
||||
// Multiple field grouping
|
||||
FROM orders
|
||||
| STATS
|
||||
order_count = COUNT(),
|
||||
total_revenue = SUM(amount)
|
||||
BY region, product_category, sales_rep
|
||||
|
||||
// Time-based grouping
|
||||
FROM logs-*
|
||||
| EVAL hour = DATE_TRUNC("hour", @timestamp)
|
||||
| STATS event_count = COUNT() BY hour, log_level
|
||||
| SORT hour DESC
|
||||
```
|
||||
|
||||
### Complex Aggregation Example
|
||||
```esql
|
||||
FROM sales_data
|
||||
| WHERE order_date >= "2024-01-01"
|
||||
| EVAL month = DATE_TRUNC("month", order_date)
|
||||
| STATS
|
||||
total_orders = COUNT(),
|
||||
total_revenue = SUM(amount),
|
||||
avg_order_value = AVG(amount),
|
||||
unique_customers = COUNT_DISTINCT(customer_id),
|
||||
max_order = MAX(amount),
|
||||
min_order = MIN(amount)
|
||||
BY month, region, product_category
|
||||
| EVAL revenue_per_customer = total_revenue / unique_customers
|
||||
| WHERE total_orders > 100
|
||||
| SORT month DESC, total_revenue DESC
|
||||
| LIMIT 50
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Advanced Patterns
|
||||
|
||||
### Window Functions Pattern
|
||||
```esql
|
||||
// Running total by group
|
||||
FROM sales
|
||||
| SORT date
|
||||
| STATS
|
||||
daily_sales = SUM(amount),
|
||||
order_count = COUNT()
|
||||
BY date, region
|
||||
| SORT region, date
|
||||
```
|
||||
|
||||
### Pivoting Data
|
||||
```esql
|
||||
// Count by status and priority
|
||||
FROM tickets
|
||||
| STATS ticket_count = COUNT() BY status, priority
|
||||
| SORT status, priority
|
||||
```
|
||||
|
||||
### Finding Duplicates
|
||||
```esql
|
||||
FROM users
|
||||
| STATS count = COUNT() BY email
|
||||
| WHERE count > 1
|
||||
| SORT count DESC
|
||||
```
|
||||
|
||||
### Time Series Analysis
|
||||
```esql
|
||||
FROM metrics-*
|
||||
| EVAL
|
||||
hour = DATE_TRUNC("hour", @timestamp),
|
||||
day = DATE_EXTRACT("day", @timestamp)
|
||||
| STATS
|
||||
avg_cpu = AVG(cpu_percent),
|
||||
max_cpu = MAX(cpu_percent),
|
||||
avg_memory = AVG(memory_percent)
|
||||
BY hour, host
|
||||
| WHERE avg_cpu > 80
|
||||
| SORT hour DESC
|
||||
```
|
||||
|
||||
### Percentage Calculations
|
||||
```esql
|
||||
FROM sales
|
||||
| STATS
|
||||
total_sales = SUM(amount),
|
||||
count = COUNT()
|
||||
BY product_category
|
||||
| EVAL percentage = ROUND(total_sales / SUM(total_sales) * 100, 2)
|
||||
| SORT percentage DESC
|
||||
```
|
||||
|
||||
### Top N per Group
|
||||
```esql
|
||||
// Top 3 products per category by sales
|
||||
FROM sales
|
||||
| STATS total_sales = SUM(amount) BY product_category, product_name
|
||||
| SORT product_category, total_sales DESC
|
||||
// Note: ES|QL doesn't have native PARTITION BY,
|
||||
// so you may need to process this in multiple queries or use aggregations
|
||||
```
|
||||
|
||||
### Data Cleaning
|
||||
```esql
|
||||
FROM raw_data
|
||||
| EVAL
|
||||
// Clean whitespace
|
||||
cleaned_name = TRIM(name),
|
||||
// Standardize case
|
||||
email_lower = LOWER(email),
|
||||
// Replace values
|
||||
status = REPLACE(status, "N/A", "Unknown"),
|
||||
// Handle nulls
|
||||
age = COALESCE(age, 0),
|
||||
// Validate ranges
|
||||
valid_age = CASE(age < 0 OR age > 150, NULL, age)
|
||||
| WHERE cleaned_name IS NOT NULL
|
||||
| DROP name, email
|
||||
| RENAME cleaned_name AS name, email_lower AS email
|
||||
```
|
||||
|
||||
### Cohort Analysis
|
||||
```esql
|
||||
FROM user_events
|
||||
| EVAL
|
||||
signup_month = DATE_TRUNC("month", signup_date),
|
||||
event_month = DATE_TRUNC("month", event_date)
|
||||
| STATS
|
||||
active_users = COUNT_DISTINCT(user_id)
|
||||
BY signup_month, event_month
|
||||
| SORT signup_month, event_month
|
||||
```
|
||||
|
||||
### Anomaly Detection Pattern
|
||||
```esql
|
||||
FROM metrics-*
|
||||
| EVAL hour = DATE_TRUNC("hour", @timestamp)
|
||||
| STATS
|
||||
avg_value = AVG(value),
|
||||
stddev = SQRT(AVG(POW(value - AVG(value), 2)))
|
||||
BY hour
|
||||
| EVAL
|
||||
upper_bound = avg_value + (2 * stddev),
|
||||
lower_bound = avg_value - (2 * stddev)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Complete Real-World Examples
|
||||
|
||||
### Example 1: User Activity Dashboard
|
||||
```esql
|
||||
FROM user_logs-*
|
||||
| WHERE @timestamp >= NOW() - 7 days
|
||||
| ENRICH user_lookup ON user_id WITH username, user_tier
|
||||
| EVAL day = DATE_TRUNC("day", @timestamp)
|
||||
| STATS
|
||||
daily_active_users = COUNT_DISTINCT(user_id),
|
||||
total_sessions = COUNT(),
|
||||
avg_session_duration = AVG(session_duration)
|
||||
BY day, user_tier
|
||||
| EVAL avg_duration_minutes = ROUND(avg_session_duration / 60, 2)
|
||||
| SORT day DESC, user_tier
|
||||
```
|
||||
|
||||
### Example 2: E-commerce Sales Report
|
||||
```esql
|
||||
FROM orders
|
||||
| WHERE order_date >= "2024-01-01"
|
||||
| ENRICH customer_lookup ON customer_id
|
||||
WITH customer_name, customer_segment
|
||||
| ENRICH product_lookup ON product_id
|
||||
WITH product_name, product_category, cost_price
|
||||
| EVAL
|
||||
profit = (price - cost_price) * quantity,
|
||||
month = DATE_TRUNC("month", order_date)
|
||||
| STATS
|
||||
total_orders = COUNT(),
|
||||
total_revenue = SUM(price * quantity),
|
||||
total_profit = SUM(profit),
|
||||
avg_order_value = AVG(price * quantity),
|
||||
unique_customers = COUNT_DISTINCT(customer_id)
|
||||
BY month, product_category, customer_segment
|
||||
| EVAL profit_margin = ROUND(total_profit / total_revenue * 100, 2)
|
||||
| WHERE total_revenue > 10000
|
||||
| SORT month DESC, total_revenue DESC
|
||||
| LIMIT 100
|
||||
```
|
||||
|
||||
### Example 3: Security Log Analysis
|
||||
```esql
|
||||
FROM security-logs-*
|
||||
| WHERE @timestamp >= NOW() - 24 hours
|
||||
| WHERE event_type IN ("login_failed", "suspicious_activity")
|
||||
| EVAL hour = DATE_TRUNC("hour", @timestamp)
|
||||
| STATS
|
||||
event_count = COUNT(),
|
||||
unique_ips = COUNT_DISTINCT(source_ip),
|
||||
unique_users = COUNT_DISTINCT(username)
|
||||
BY hour, event_type, country
|
||||
| WHERE event_count > 100
|
||||
| SORT hour DESC, event_count DESC
|
||||
```
|
||||
|
||||
### Example 4: Application Performance Monitoring
|
||||
```esql
|
||||
FROM apm-*
|
||||
| WHERE @timestamp >= NOW() - 1 hour
|
||||
| EVAL
|
||||
response_category = CASE(
|
||||
response_time < 100, "Fast",
|
||||
response_time < 500, "Medium",
|
||||
response_time < 1000, "Slow",
|
||||
"Very Slow"
|
||||
),
|
||||
minute = DATE_TRUNC("minute", @timestamp)
|
||||
| STATS
|
||||
request_count = COUNT(),
|
||||
avg_response = AVG(response_time),
|
||||
p95_response = PERCENTILE(response_time, 95),
|
||||
p99_response = PERCENTILE(response_time, 99),
|
||||
error_count = COUNT() WHERE status_code >= 400
|
||||
BY minute, endpoint, response_category
|
||||
| EVAL error_rate = ROUND(error_count / request_count * 100, 2)
|
||||
| WHERE request_count > 10
|
||||
| SORT minute DESC, avg_response DESC
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Tips & Best Practices
|
||||
|
||||
1. **Use KEEP instead of SELECT** - More explicit about which fields to retain
|
||||
2. **Filter early with WHERE** - Reduce data processing by filtering before aggregations
|
||||
3. **Use DATE_TRUNC for time bucketing** - Essential for time series analysis
|
||||
4. **Leverage ENRICH for joins** - Pre-create enrich policies for frequently joined data
|
||||
5. **Use EVAL for calculated fields** - Create derived fields before aggregation
|
||||
6. **Combine multiple conditions in WHERE** - More efficient than multiple WHERE clauses
|
||||
7. **Use STATS with BY for grouping** - Replaces traditional GROUP BY
|
||||
8. **Sort after aggregation** - More efficient than sorting before
|
||||
9. **Use LIMIT to control output size** - Especially important for large datasets
|
||||
10. **Use metadata fields when needed** - Access _id, _index with METADATA keyword
|
||||
|
||||
---
|
||||
|
||||
## Common Patterns Cheat Sheet
|
||||
|
||||
```esql
|
||||
// Count by field
|
||||
FROM index | STATS count = COUNT() BY field
|
||||
|
||||
// Top N
|
||||
FROM index | STATS value = SUM(amount) BY category | SORT value DESC | LIMIT 10
|
||||
|
||||
// Time series
|
||||
FROM index | EVAL bucket = DATE_TRUNC("hour", @timestamp) | STATS count = COUNT() BY bucket
|
||||
|
||||
// Percentage of total
|
||||
FROM index | STATS total = SUM(amount) BY category | EVAL pct = total / SUM(total) * 100
|
||||
|
||||
// Filter nulls
|
||||
FROM index | WHERE field IS NOT NULL
|
||||
|
||||
// String matching
|
||||
FROM index | WHERE field LIKE "*pattern*"
|
||||
|
||||
// Date range
|
||||
FROM index | WHERE @timestamp >= NOW() - 7 days
|
||||
|
||||
// Multiple aggregations
|
||||
FROM index | STATS count = COUNT(), sum = SUM(val), avg = AVG(val) BY group
|
||||
|
||||
// Conditional aggregation
|
||||
FROM index | STATS error_count = COUNT() WHERE status == "error" BY service
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Comparison with Traditional SQL
|
||||
|
||||
| SQL | ES|QL |
|
||||
|-----|-------|
|
||||
| SELECT * | FROM index |
|
||||
| SELECT field1, field2 | FROM index \| KEEP field1, field2 |
|
||||
| WHERE condition | WHERE condition (same) |
|
||||
| GROUP BY field | STATS ... BY field |
|
||||
| ORDER BY field | SORT field |
|
||||
| LIMIT 10 | LIMIT 10 (same) |
|
||||
| COUNT(*) | STATS count = COUNT() |
|
||||
| SUM(field) | STATS total = SUM(field) |
|
||||
| AVG(field) | STATS avg = AVG(field) |
|
||||
| JOIN | ENRICH (using enrich policies) |
|
||||
| CASE WHEN | CASE(...) |
|
||||
| CONCAT(a, b) | CONCAT(a, b) (same) |
|
||||
|
||||
---
|
||||
|
||||
## Resources
|
||||
|
||||
- Official ES|QL Documentation: https://www.elastic.co/guide/en/elasticsearch/reference/current/esql.html
|
||||
- ES|QL Functions Reference: https://www.elastic.co/guide/en/elasticsearch/reference/current/esql-functions.html
|
||||
- Enrich Processor: https://www.elastic.co/guide/en/elasticsearch/reference/current/enrich-processor.html
|
||||
|
||||
---
|
||||
|
||||
*Last Updated: 2024*
|
||||
*ES|QL is actively evolving - check official documentation for latest features*
|
||||
23
cmd/root.go
23
cmd/root.go
@@ -24,10 +24,13 @@ import (
|
||||
"runtime/pprof"
|
||||
"strings"
|
||||
|
||||
"codeberg.org/scip/esctl/assets"
|
||||
"codeberg.org/scip/esctl/pkg/cfg"
|
||||
"codeberg.org/scip/esctl/pkg/es"
|
||||
"codeberg.org/scip/esctl/pkg/log"
|
||||
"codeberg.org/scip/esctl/pkg/printer"
|
||||
|
||||
markdown "github.com/MichaelMure/go-term-markdown"
|
||||
"github.com/urfave/cli/v3"
|
||||
)
|
||||
|
||||
@@ -141,7 +144,7 @@ func Main() int {
|
||||
Name: "output",
|
||||
Aliases: []string{"o"},
|
||||
Value: "",
|
||||
Usage: "output mode (tsv, json, yaml) default: tsv",
|
||||
Usage: "output mode (tsv, csv, json, yaml) default: tsv",
|
||||
Destination: &conf.Output,
|
||||
},
|
||||
&cli.StringFlag{
|
||||
@@ -164,6 +167,7 @@ func Main() int {
|
||||
Node(conf),
|
||||
Roles(conf),
|
||||
Search(conf),
|
||||
SearchQL(conf),
|
||||
Shard(conf),
|
||||
Snapshot(conf),
|
||||
Task(conf),
|
||||
@@ -171,6 +175,7 @@ func Main() int {
|
||||
Debug(conf),
|
||||
HelpJsonPath(conf),
|
||||
HelpUsage(conf),
|
||||
HelpEsQl(conf),
|
||||
},
|
||||
|
||||
Before: func(ctx context.Context, cmd *cli.Command) (context.Context, error) {
|
||||
@@ -226,6 +231,22 @@ func HelpJsonPath(conf *cfg.Config) *cli.Command {
|
||||
}
|
||||
}
|
||||
|
||||
func HelpEsQl(conf *cfg.Config) *cli.Command {
|
||||
return &cli.Command{
|
||||
Name: "help-esql",
|
||||
Usage: "show esql help",
|
||||
|
||||
Action: func(ctx context.Context, cmd *cli.Command) error {
|
||||
assets.LoadEsql()
|
||||
|
||||
width := cfg.GetTermWidth()
|
||||
printer.Pager("esql cheat sheet", string(markdown.Render(assets.EsQlCheatSheet, width, cfg.DefaultMargin)))
|
||||
|
||||
return nil
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func Version(conf *cfg.Config) *cli.Command {
|
||||
return &cli.Command{
|
||||
Name: "version",
|
||||
|
||||
@@ -18,6 +18,7 @@ package cmd
|
||||
|
||||
import (
|
||||
"context"
|
||||
"strings"
|
||||
|
||||
"codeberg.org/scip/esctl/pkg/cfg"
|
||||
"codeberg.org/scip/esctl/pkg/es"
|
||||
@@ -45,6 +46,11 @@ https://www.elastic.co/docs/reference/elasticsearch/rest-apis/common-options#dat
|
||||
For timestamp formats refer to:
|
||||
https://www.elastic.co/docs/reference/elasticsearch/mapping-reference/mapping-date-format`
|
||||
|
||||
const QlUsage = `ES|QL documentation:
|
||||
https://www.elastic.co/docs/reference/query-languages/esql/esql-getting-started
|
||||
|
||||
See also: esctl help-esql`
|
||||
|
||||
func Search(conf *cfg.Config) *cli.Command {
|
||||
return &cli.Command{
|
||||
Name: "search",
|
||||
@@ -149,3 +155,19 @@ func Search(conf *cfg.Config) *cli.Command {
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
func SearchQL(conf *cfg.Config) *cli.Command {
|
||||
return &cli.Command{
|
||||
Name: "searchql",
|
||||
Aliases: []string{"/"},
|
||||
Usage: "search using ES/QL language",
|
||||
UsageText: "search <ES/QL term>",
|
||||
CustomHelpTemplate: addReference(QlUsage),
|
||||
|
||||
Action: func(ctx context.Context, cmd *cli.Command) error {
|
||||
args := cmd.Args()
|
||||
|
||||
return es.SearchQL(conf, strings.Join(args.Slice(), " "))
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
79
pkg/es/searchql.go
Normal file
79
pkg/es/searchql.go
Normal file
@@ -0,0 +1,79 @@
|
||||
/*
|
||||
Copyright © 2026 Thomas von Dein
|
||||
|
||||
This program is free software: you can redistribute it and/or modify
|
||||
it under the terms of the GNU General Public License as published by
|
||||
the Free Software Foundation, either version 3 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU General Public License
|
||||
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
||||
*/
|
||||
package es
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"log/slog"
|
||||
|
||||
"codeberg.org/scip/esctl/pkg/cfg"
|
||||
"codeberg.org/scip/esctl/pkg/printer"
|
||||
)
|
||||
|
||||
type searchQlColumn struct {
|
||||
Name string `json:"name"`
|
||||
Type string `json:"type"`
|
||||
}
|
||||
|
||||
type searchQlResult struct {
|
||||
Partial bool `json:"is_partial"`
|
||||
Docs int `json:"documents_found"`
|
||||
Columns []searchQlColumn `json:"columns"`
|
||||
Values [][]any `json:"values"`
|
||||
}
|
||||
|
||||
func SearchQL(conf *cfg.Config, querystring string) error {
|
||||
query := conf.DefaultCluster.ES().Esql.Query().
|
||||
Query(querystring).
|
||||
DropNullColumns(true)
|
||||
|
||||
res, err := query.Do(context.Background())
|
||||
if err != nil {
|
||||
return fmt.Errorf("failed to run esql query: %w", esErrorString(err))
|
||||
}
|
||||
|
||||
if conf.Debug {
|
||||
fmt.Println(string(res))
|
||||
}
|
||||
|
||||
qlResult := searchQlResult{}
|
||||
|
||||
if err = json.Unmarshal(res, &qlResult); err != nil {
|
||||
return fmt.Errorf("failed to unmarshal esql result: %w", err)
|
||||
}
|
||||
|
||||
slog.Debug("searchql result", "qlres", qlResult)
|
||||
|
||||
if qlResult.Docs == 0 {
|
||||
return nil
|
||||
}
|
||||
|
||||
table := printer.NewTable(conf, len(qlResult.Columns), len(qlResult.Values))
|
||||
|
||||
headers := make([]string, len(qlResult.Columns))
|
||||
for idx, col := range qlResult.Columns {
|
||||
headers[idx] = col.Name
|
||||
}
|
||||
|
||||
table.Addheaders(headers...)
|
||||
|
||||
table.Entries = qlResult.Values
|
||||
|
||||
return table.Print()
|
||||
}
|
||||
@@ -30,9 +30,10 @@ import (
|
||||
)
|
||||
|
||||
type Table struct {
|
||||
Mode string // tsv, json, yaml
|
||||
Headers []string
|
||||
Entries [][]any
|
||||
Mode string // tsv, json, yaml
|
||||
Headers []string
|
||||
RawHeaders []string
|
||||
Entries [][]any
|
||||
|
||||
rows [][]string // representation used for printing
|
||||
processed bool
|
||||
@@ -45,6 +46,7 @@ func NewTable(conf *cfg.Config, columns, rows int) *Table {
|
||||
table := Table{Mode: conf.Output, maxwidth: cfg.GetTermWidth()}
|
||||
|
||||
table.Headers = make([]string, columns)
|
||||
table.RawHeaders = make([]string, columns)
|
||||
table.Entries = make([][]any, rows)
|
||||
table.lenHeaders = make([]int, columns)
|
||||
table.alignInts = conf.AlignInts
|
||||
@@ -65,6 +67,7 @@ func (table *Table) WithHeaders(headers ...string) *Table {
|
||||
table.Entries = [][]any{}
|
||||
table.lenHeaders = make([]int, count)
|
||||
table.Headers = make([]string, count)
|
||||
table.RawHeaders = make([]string, count)
|
||||
|
||||
table.Addheaders(headers...)
|
||||
|
||||
@@ -77,6 +80,8 @@ func (table *Table) Print() error {
|
||||
return table.PrintJSON()
|
||||
case "yaml":
|
||||
return table.PrintYAML()
|
||||
case "csv":
|
||||
return table.PrintCSV()
|
||||
default:
|
||||
return table.PrintTSV()
|
||||
}
|
||||
@@ -178,6 +183,28 @@ func (table *Table) PrintTSV() error {
|
||||
return nil
|
||||
}
|
||||
|
||||
func (table *Table) PrintCSV() error {
|
||||
table.preprocessRows()
|
||||
|
||||
fmt.Println(strings.Join(table.RawHeaders, ","))
|
||||
|
||||
for _, entries := range table.rows {
|
||||
row := make([]string, len(entries))
|
||||
|
||||
for idx, entry := range entries {
|
||||
if strings.Contains(entry, " ") || strings.Contains(entry, ",") {
|
||||
row[idx] = `"` + entry + `"`
|
||||
} else {
|
||||
row[idx] = entry
|
||||
}
|
||||
}
|
||||
|
||||
fmt.Println(strings.Join(row, ","))
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
|
||||
func (table *Table) Sort() {
|
||||
// sanity checks
|
||||
if len(table.Entries) == 0 {
|
||||
@@ -199,6 +226,8 @@ func (table *Table) Addheaders(headers ...string) {
|
||||
default:
|
||||
table.Headers[idx] = bold(strings.ReplaceAll(strings.ToUpper(header), " ", "-"))
|
||||
}
|
||||
|
||||
table.RawHeaders[idx] = header
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
Reference in New Issue
Block a user