SQL functions
Learn how to use SQL functions in APL
SQL functions
Function Name | Description |
---|---|
parse_sql() | Interprets and analyzes SQL queries, making it easier to extract and understand SQL statements within datasets. |
format_sql() | Converts the data model produced by parse_sql() back into a SQL statement for validation or formatting purposes. |
parse_sql()
Analyzes an SQL statement and constructs a data model, enabling insights into the SQL content within a dataset.
Limitations
- It is mainly used for simple SQL queries. SQL statements like stored procedures, Windows functions, common table expressions (CTEs), recursive queries, advanced statistical functions, and special joins are not supported.
Arguments
Name | Type | Required or Optional | Description |
---|---|---|---|
sql_statement | string | Required | The SQL statement to analyze. |
Returns
A dictionary representing the structured data model of the provided SQL statement. This model includes maps or slices that detail the various components of the SQL statement, such as tables, fields, conditions, etc.
Examples
Basic data retrieval
The SQL statement SELECT * FROM db
retrieves all columns and rows from the table named db
.
hn
| project parse_sql("select * from db")
WHERE Clause
This example parses a SELECT
statement with a WHERE
clause, filtering customers
by subscription_status
.
hn
| project parse_sql("SELECT id, email FROM customers WHERE subscription_status = 'active'")
JOIN operation
This example shows parsing an SQL statement that performs a JOIN
operation between orders
and customers
tables to match orders with customer names.
hn
| project parse_sql("SELECT orders.id, customers.name FROM orders JOIN customers ON orders.customer_id = customers.id")
GROUP BY Clause
In this example, the parse_sql()
function is used to parse an SQL statement that aggregates order counts by product_id
using the GROUP BY
clause.
hn
| project parse_sql("SELECT product_id, COUNT(*) as order_count FROM orders GROUP BY product_id")
Nested Queries
This example demonstrates parsing a nested SQL query, where the inner query selects user_id
from orders
based on purchase_date
, and the outer query selects names from users
based on those IDs.
hn
| project parse_sql("SELECT name FROM users WHERE id IN (SELECT user_id FROM orders WHERE purchase_date > '2022-01-01')")
ORDER BY Clause
Here, the example shows how to parse an SQL statement that orders users
by registration_date
in descending order.
hn
| project parse_sql("SELECT name, registration_date FROM users ORDER BY registration_date DESC")
Sorting users by registration data
This example demonstrates parsing an SQL statement that retrieves the name
and registration_date
of users from the users
table, and orders the results by registration_date
in descending order, showing how to sort data based on a specific column.
hn | extend parse_sql("SELECT name, registration_date FROM users ORDER BY registration_date DESC")
Querying with index hints to use a specific index
This query hints at MySQL to use a specific index named index_name
when executing the SELECT statement on the users
table.
hn
| project parse_sql("SELECT * FROM users USE INDEX (index_name) WHERE user_id = 101")
Inserting data with ON DUPLICATE KEY UPDATE
This example showcases MySQL’s ability to handle duplicate key entries elegantly by updating the existing record if the insert operation encounters a duplicate key.
hn
| project parse_sql("INSERT INTO settings (user_id, setting, value) VALUES (1, 'theme', 'dark') ON DUPLICATE KEY UPDATE value='dark'")
Using JSON functions
This query demonstrates MySQL’s support for JSON data types and functions, extracting the age from a JSON object stored in the user_info
column.
hn
| project parse_sql("SELECT JSON_EXTRACT(user_info, '$.age') AS age FROM users WHERE user_id = 101")
format_sql()
Transforms the data model output by parse_sql()
back into a SQL statement. Useful for testing and ensuring that the parsing accurately retains the original structure and intent of the SQL statement.
Arguments
Name | Type | Required or Optional | Description |
---|---|---|---|
parsed_sql_model | dictionary | Required | The structured data model output by parse_sql() . |
Returns
A string that represents the SQL statement reconstructed from the provided data model.
Examples
Reformatting a basic SELECT Query
After parsing a SQL statement, you can reformat it back to its original or a standard SQL format.
hn
| extend parsed = parse_sql("SELECT * FROM db")
| project formatted_sql = format_sql(parsed)
Formatting SQL Queries
This example first parses a SQL statement to analyze its structure and then formats the parsed structure back into a SQL string using format_sql
.
hn
| extend parsed = parse_sql("SELECT name, registration_date FROM users ORDER BY registration_date DESC")
| project format_sql(parsed)
Formatting a simple SELECT Statement
This example demonstrates parsing a straightforward SELECT
statement that retrieves user IDs and usernames from an user_accounts
table where the active
status is 1
. After parsing, it uses format_sql
to convert the parsed data back into a SQL string.
hn
| extend parsed = parse_sql("SELECT user_id, username FROM user_accounts WHERE active = 1")
| project formatted_sql = format_sql(parsed)
Reformatting a complex query with JOINS
In this example, a more complex SQL statement involving an INNER JOIN
between orders
and customers
tables is parsed. The query selects orders and customer names for orders placed after January 1, 2023. format_sql
is then used to reformat the parsed structure into a SQL string.
hn
| extend parsed = parse_sql("SELECT orders.order_id, customers.name FROM orders INNER JOIN customers ON orders.customer_id = customers.id WHERE orders.order_date > '2023-01-01'")
| project formatted_sql = format_sql(parsed)
Using format_sql with aggregation functions
This example focuses on parsing an SQL statement that performs aggregation. It selects product IDs and counts of total sales from a sales
table, grouping by product_id
and having a condition on the count. After parsing, format_sql
reformats the output into an SQL string.
hn
| extend parsed = parse_sql("SELECT product_id, COUNT(*) as total_sales FROM sales GROUP BY product_id HAVING COUNT(*) > 100")
| project formatted_sql = format_sql(parsed)
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