Why FLATTEN for nested data in Snowflake? - Purpose & Use Cases

The Big Idea

What if you could instantly see every hidden detail inside your messy data boxes without opening them one by one?

The Scenario

Imagine you have a big box filled with smaller boxes, and each smaller box has many items inside. You want to see every single item clearly, but you have to open each small box one by one and write down what's inside.

The Problem

Doing this by hand takes forever and you might miss some items or write things down wrong. It's slow, confusing, and easy to make mistakes when you try to look inside many nested boxes manually.

The Solution

The FLATTEN function in Snowflake acts like a magic tool that opens all the small boxes at once and lays out every item in a neat list. This way, you can see and work with all the nested data easily and quickly without missing anything.

Before vs After

✗ Before

SELECT nested_column FROM table;

✓ After

SELECT value FROM table, LATERAL FLATTEN(input => nested_column);

What It Enables

It lets you explore and analyze complex nested data as if it were simple and flat, unlocking insights hidden deep inside.

Real Life Example

Think of a customer order that includes multiple products, each with its own details. FLATTEN helps you list every product separately to understand sales better.

Key Takeaways

Manual inspection of nested data is slow and error-prone.

FLATTEN quickly expands nested data into simple rows.

This makes complex data easy to analyze and use.

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