361 lines
7.9 KiB
Markdown
361 lines
7.9 KiB
Markdown
---
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layout: default
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title: Basic Queries
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parent: SQL
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nav_order: 5
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redirect_from: /docs/sql/basic/
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---
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# Basic queries
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Use the `SELECT` clause, along with `FROM`, `WHERE`, `GROUP BY`, `HAVING`, `ORDER BY`, and `LIMIT` to search and aggregate data.
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Among these clauses, `SELECT` and `FROM` are required, as they specify which fields to retrieve and which indices to retrieve them from. All other clauses are optional. Use them according to your needs.
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### Syntax
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The complete syntax for searching and aggregating data is as follows:
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```sql
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SELECT [DISTINCT] (* | expression) [[AS] alias] [, ...]
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FROM index_name
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[WHERE predicates]
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[GROUP BY expression [, ...]
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[HAVING predicates]]
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[ORDER BY expression [IS [NOT] NULL] [ASC | DESC] [, ...]]
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[LIMIT [offset, ] size]
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```
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### Fundamentals
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Apart from the predefined keywords of SQL, the most basic elements are literal and identifiers.
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A literal is a numeric, string, date or boolean constant. An identifier is an OpenSearch index or field name.
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With arithmetic operators and SQL functions, use literals and identifiers to build complex expressions.
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Rule `expressionAtom`:
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![expressionAtom](../../images/expressionAtom.png)
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The expression in turn can be combined into a predicate with logical operator. Use a predicate in the `WHERE` and `HAVING` clause to filter out data by specific conditions.
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Rule `expression`:
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![expression](../../images/expression.png)
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Rule `predicate`:
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![expression](../../images/predicate.png)
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### Execution Order
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These SQL clauses execute in an order different from how they appear:
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```sql
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FROM index
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WHERE predicates
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GROUP BY expressions
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HAVING predicates
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SELECT expressions
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ORDER BY expressions
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LIMIT size
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```
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## Select
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Specify the fields to be retrieved.
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### Syntax
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Rule `selectElements`:
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![selectElements](../../images/selectElements.png)
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Rule `selectElement`:
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![selectElements](../../images/selectElement.png)
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*Example 1*: Use `*` to retrieve all fields in an index:
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```sql
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SELECT *
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FROM accounts
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```
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| id | account_number | firstname | gender | city | balance | employer | state | email | address | lastname | age
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:--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :---
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0 | 1 | Amber | M | Brogan | 39225 | Pyrami | IL | amberduke@pyrami.com | 880 Holmes Lane | Duke | 32
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1 | 16 | Hattie | M | Dante | 5686 | Netagy | TN | hattiebond@netagy.com | 671 Bristol Street | Bond | 36
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2 | 13 | Nanette | F | Nogal | 32838 | Quility | VA | nanettebates@quility.com | 789 Madison Street | Bates | 28
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3 | 18 | Dale | M | Orick | 4180 | | MD | daleadams@boink.com | 467 Hutchinson Court | Adams | 33
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*Example 2*: Use field name(s) to retrieve only specific fields:
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```sql
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SELECT firstname, lastname
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FROM accounts
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```
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| id | firstname | lastname
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:--- | :--- | :---
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0 | Amber | Duke
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1 | Hattie | Bond
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2 | Nanette | Bates
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3 | Dale | Adams
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*Example 3*: Use field aliases instead of field names. Field aliases are used to make field names more readable:
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```sql
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SELECT account_number AS num
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FROM accounts
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```
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| id | num
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:--- | :---
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0 | 1
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1 | 6
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2 | 13
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3 | 18
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*Example 4*: Use the `DISTINCT` clause to get back only unique field values. You can specify one or more field names:
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```sql
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SELECT DISTINCT age
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FROM accounts
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```
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| id | age
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:--- | :---
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0 | 28
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1 | 32
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2 | 33
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3 | 36
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## From
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Specify the index that you want search.
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You can specify subqueries within the `FROM` clause.
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### Syntax
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Rule `tableName`:
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![tableName](../../images/tableName.png)
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*Example 1*: Use index aliases to query across indexes. To learn about index aliases, see [Index Alias](../opensearch/index-alias/).
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In this sample query, `acc` is an alias for the `accounts` index:
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```sql
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SELECT account_number, accounts.age
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FROM accounts
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```
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or
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```sql
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SELECT account_number, acc.age
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FROM accounts acc
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```
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| id | account_number | age
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:--- | :--- | :---
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0 | 1 | 32
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1 | 6 | 36
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2 | 13 | 28
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3 | 18 | 33
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*Example 2*: Use index patterns to query indices that match a specific pattern:
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```sql
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SELECT account_number
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FROM account*
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```
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| id | account_number
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:--- | :---
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0 | 1
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1 | 6
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2 | 13
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3 | 18
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## Where
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Specify a condition to filter the results.
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| Operators | Behavior
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:--- | :---
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`=` | Equal to.
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`<>` | Not equal to.
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`>` | Greater than.
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`<` | Less than.
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`>=` | Greater than or equal to.
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`<=` | Less than or equal to.
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`IN` | Specify multiple `OR` operators.
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`BETWEEN` | Similar to a range query. For more information about range queries, see [Range query](../opensearch/term/#range).
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`LIKE` | Use for full text search. For more information about full-text queries, see [Full-text queries](../opensearch/full-text/).
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`IS NULL` | Check if the field value is `NULL`.
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`IS NOT NULL` | Check if the field value is `NOT NULL`.
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Combine comparison operators (`=`, `<>`, `>`, `>=`, `<`, `<=`) with boolean operators `NOT`, `AND`, or `OR` to build more complex expressions.
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*Example 1*: Use comparison operators for numbers, strings, or dates:
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```sql
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SELECT account_number
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FROM accounts
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WHERE account_number = 1
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```
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| id | account_number
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:--- | :---
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0 | 1
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*Example 2*: OpenSearch allows for flexible schema so documents in an index may have different fields. Use `IS NULL` or `IS NOT NULL` to retrieve only missing fields or existing fields. We do not differentiate between missing fields and fields explicitly set to `NULL`:
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```sql
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SELECT account_number, employer
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FROM accounts
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WHERE employer IS NULL
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```
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| id | account_number | employer
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:--- | :--- | :---
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0 | 18 |
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*Example 3*: Deletes a document that satisfies the predicates in the `WHERE` clause:
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```sql
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DELETE FROM accounts
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WHERE age > 30
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```
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## Group By
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Group documents with the same field value into buckets.
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*Example 1*: Group by fields:
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```sql
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SELECT age
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FROM accounts
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GROUP BY age
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```
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| id | age
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:--- | :---
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0 | 28
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1 | 32
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2 | 33
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3 | 36
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*Example 2*: Group by field alias:
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```sql
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SELECT account_number AS num
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FROM accounts
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GROUP BY num
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```
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| id | num
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:--- | :---
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0 | 1
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1 | 6
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2 | 13
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3 | 18
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*Example 4*: Use scalar functions in the `GROUP BY` clause:
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```sql
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SELECT ABS(age) AS a
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FROM accounts
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GROUP BY ABS(age)
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```
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| id | a
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:--- | :---
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0 | 28.0
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1 | 32.0
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2 | 33.0
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3 | 36.0
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## Having
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Use the `HAVING` clause to aggregate inside each bucket based on aggregation functions (`COUNT`, `AVG`, `SUM`, `MIN`, and `MAX`).
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The `HAVING` clause filters results from the `GROUP BY` clause:
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*Example 1*:
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```sql
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SELECT age, MAX(balance)
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FROM accounts
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GROUP BY age HAVING MIN(balance) > 10000
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```
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| id | age | MAX (balance)
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:--- | :---
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0 | 28 | 32838
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1 | 32 | 39225
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## Order By
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Use the `ORDER BY` clause to sort results into your desired order.
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*Example 1*: Use `ORDER BY` to sort by ascending or descending order. Besides regular field names, using `ordinal`, `alias`, or `scalar` functions are supported:
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```sql
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SELECT account_number
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FROM accounts
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ORDER BY account_number DESC
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```
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| id | account_number
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:--- | :---
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0 | 18
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1 | 13
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2 | 6
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3 | 1
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*Example 2*: Specify if documents with missing fields are to be put at the beginning or at the end of the results. The default behavior of OpenSearch is to return nulls or missing fields at the end. To push them before non-nulls, use the `IS NOT NULL` operator:
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```sql
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SELECT employer
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FROM accounts
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ORDER BY employer IS NOT NULL
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```
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| id | employer
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:--- | :---
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0 |
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1 | Netagy
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2 | Pyrami
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3 | Quility
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## Limit
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Specify the maximum number of documents that you want to retrieve. Used to prevent fetching large amounts of data into memory.
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*Example 1*: If you pass in a single argument, it's mapped to the `size` parameter in OpenSearch and the `from` parameter is set to 0.
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```sql
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SELECT account_number
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FROM accounts
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ORDER BY account_number LIMIT 1
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```
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| id | account_number
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:--- | :---
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0 | 1
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*Example 2*: If you pass in two arguments, the first is mapped to the `from` parameter and the second to the `size` parameter in OpenSearch. You can use this for simple pagination for small indices, as it's inefficient for large indices.
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Use `ORDER BY` to ensure the same order between pages:
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```sql
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SELECT account_number
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FROM accounts
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ORDER BY account_number LIMIT 1, 1
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```
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| id | account_number
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:--- | :---
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0 | 6
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