FLATTEN for nested data in Snowflake - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the FLATTEN function do in Snowflake?

FLATTEN takes nested data like arrays or objects and turns them into a simple table format with one row per element.

beginner

Which data types can FLATTEN work on in Snowflake?

FLATTEN works on VARIANT, OBJECT, and ARRAY data types that contain nested structures.

intermediate

What is the purpose of the 'path' parameter in FLATTEN?

The 'path' parameter lets you specify which nested part of the data to flatten, like a specific array inside an object.

intermediate

How does FLATTEN handle nested arrays inside arrays?

FLATTEN can be applied multiple times or with the right path to break down nested arrays step by step into rows.

intermediate

What columns does FLATTEN output by default?

FLATTEN outputs columns like SEQ (sequence number), KEY (array index or object key), VALUE (element value), and PATH (location in the nested data).

What type of data does FLATTEN in Snowflake primarily work with?

A Binary files

B Nested data like arrays and objects

C Relational tables only

D Flat CSV files

FLATTEN is designed to convert nested data structures such as arrays and objects into a flat table format.

Which FLATTEN output column shows the position of the element in the array?

A VALUE

B PATH

C SEQ

D KEY

The KEY column shows the index or key of the element in the array or object.

How can you flatten a nested array inside another array in Snowflake?

A Use FLATTEN multiple times or specify the correct path

B Use FLATTEN once on the outer array only

C Use FLATTEN with no parameters

D You cannot flatten nested arrays

To flatten nested arrays, you apply FLATTEN multiple times or use the path parameter to target the inner array.

What does the 'path' parameter in FLATTEN do?

A Specifies which nested part to flatten

B Sorts the output rows

C Filters rows after flattening

D Changes data types

The path parameter tells FLATTEN which nested array or object to flatten inside the data.

Which Snowflake data type is NOT typically used with FLATTEN?

A OBJECT

B ARRAY

C INTEGER

D VARIANT

INTEGER is a simple data type and does not contain nested structures, so FLATTEN is not used on it.

Explain how the FLATTEN function helps when working with nested JSON data in Snowflake.

Think about turning a list inside a list into a simple table.

Describe the role of the 'path' parameter in the FLATTEN function and when you would use it.

Imagine pointing FLATTEN to a specific drawer inside a cabinet.

Practice

1. What does the FLATTEN function do in Snowflake when working with nested data?

easy

A. It encrypts nested data for security.

B. It compresses data to save storage space.

C. It converts nested arrays or objects into simple rows.

D. It creates a backup of nested data.

Solution

1. Step 1: Understand the purpose of FLATTEN

   FLATTEN is designed to take nested arrays or objects and turn them into individual rows so they are easier to query.

2. Step 2: Compare options to FLATTEN's function

   Options A, B, and D describe encryption, compression, and backup, which are unrelated to FLATTEN's role.

3. Final Answer:

   It converts nested arrays or objects into simple rows. -> Option C

4. Quick Check:

   FLATTEN = convert nested data to rows [OK]

Hint: FLATTEN breaks nested data into rows for easy reading [OK]

Common Mistakes:

• Thinking FLATTEN compresses or encrypts data
• Confusing FLATTEN with backup or storage functions
• Assuming FLATTEN changes data format instead of structure

2. Which of the following is the correct syntax to use FLATTEN on a JSON column named data in Snowflake?

easy

A. SELECT FLATTEN(data) FROM table;

B. SELECT * FROM FLATTEN(input => data);

C. SELECT FLATTEN(input = data) FROM table;

D. SELECT * FROM table, LATERAL FLATTEN(input => data);

Solution

1. Step 1: Recall FLATTEN usage in FROM clause

   FLATTEN is used as a table function in the FROM clause with LATERAL to expand nested data.

2. Step 2: Analyze each option's syntax

   SELECT * FROM table, LATERAL FLATTEN(input => data); correctly uses FROM table, LATERAL FLATTEN(input => data). Options A and C misuse FLATTEN as a scalar function. SELECT * FROM FLATTEN(input => data); misses the table reference.

3. Final Answer:

   SELECT * FROM table, LATERAL FLATTEN(input => data); -> Option D

4. Quick Check:

   FLATTEN used with LATERAL in FROM clause [OK]

Hint: Use FLATTEN with LATERAL in FROM clause for nested data [OK]

Common Mistakes:

• Using FLATTEN as a scalar function in SELECT
• Omitting LATERAL keyword
• Not specifying input parameter correctly

3. Given the JSON column data with value '{"items": ["apple", "banana", "cherry"]}', what will the query below return?

SELECT f.value FROM table, LATERAL FLATTEN(input => data:items) f;

medium

A. Rows with values: apple, banana, cherry

B. A single row with the entire array as a string

C. An error because data:items is invalid syntax

D. Rows with keys and values of the JSON object

Solution

1. Step 1: Understand FLATTEN on JSON array

   FLATTEN(input => data:items) expands the array under 'items' into multiple rows, each with one element.

2. Step 2: Analyze the query output

   The query selects f.value, which will be each element: 'apple', 'banana', 'cherry' as separate rows.

3. Final Answer:

   Rows with values: apple, banana, cherry -> Option A

4. Quick Check:

   FLATTEN on array returns each element as a row [OK]

Hint: FLATTEN on JSON array returns each element as a separate row [OK]

Common Mistakes:

• Expecting a single row with the whole array
• Confusing keys with values in FLATTEN output
• Misreading JSON path syntax

4. You wrote this query to flatten nested JSON data:

SELECT f.value FROM table, FLATTEN(input => data:items) f;

But it returns an error. What is the likely cause?

medium

A. Missing LATERAL keyword before FLATTEN

B. Incorrect JSON path syntax in input

C. FLATTEN cannot be used on JSON arrays

D. SELECT statement missing WHERE clause

Solution

1. Step 1: Identify FLATTEN usage requirements

   FLATTEN is a table function that requires LATERAL when used with another table to expand nested data.

2. Step 2: Check query syntax

   The query misses the LATERAL keyword before FLATTEN, causing a syntax error.

3. Final Answer:

   Missing LATERAL keyword before FLATTEN -> Option A

4. Quick Check:

   FLATTEN needs LATERAL in FROM clause [OK]

Hint: Always add LATERAL before FLATTEN in FROM clause [OK]

Common Mistakes:

• Forgetting LATERAL keyword
• Assuming FLATTEN works without LATERAL
• Blaming JSON path syntax instead of syntax structure

5. You have a table with a column orders storing nested JSON arrays of items per order. You want to list each item with its order ID. Which query correctly uses FLATTEN to achieve this?

hard

A. SELECT order_id, FLATTEN(orders) FROM orders_table;

B. SELECT order_id, f.value FROM orders_table, LATERAL FLATTEN(input => orders) f;

C. SELECT order_id, f.value FROM orders_table JOIN FLATTEN(input => orders) f ON TRUE;

D. SELECT order_id, f.value FROM orders_table, FLATTEN(orders) f;

Solution

1. Step 1: Understand how to join FLATTEN with table

   FLATTEN must be used with LATERAL in the FROM clause to expand nested arrays per row.

2. Step 2: Evaluate each option's correctness

   SELECT order_id, f.value FROM orders_table, LATERAL FLATTEN(input => orders) f; correctly uses FROM orders_table, LATERAL FLATTEN(input => orders) f, selecting order_id and each item value. Options A and D misuse FLATTEN syntax. SELECT order_id, f.value FROM orders_table JOIN FLATTEN(input => orders) f ON TRUE; uses JOIN incorrectly without LATERAL.

3. Final Answer:

   SELECT order_id, f.value FROM orders_table, LATERAL FLATTEN(input => orders) f; -> Option B

4. Quick Check:

   Use LATERAL FLATTEN with table to list nested items [OK]

Hint: Use LATERAL FLATTEN(input => column) to expand nested arrays per row [OK]

Common Mistakes:

• Using FLATTEN without LATERAL
• Trying to JOIN FLATTEN without LATERAL
• Incorrect FLATTEN syntax in SELECT clause