Sequences and auto-increment in Snowflake - Time & Space Complexity

Time Complexity: Sequences and auto-increment

O(n)

Understanding Time Complexity

When using sequences or auto-increment in Snowflake, it's important to understand how the time to get the next number grows as you request more values.

We want to know how the number of calls to get new sequence values changes as we insert more rows.

Scenario Under Consideration

Analyze the time complexity of fetching sequence values during inserts.

CREATE SEQUENCE my_seq START = 1 INCREMENT = 1;

INSERT INTO my_table (id, data)
SELECT my_seq.nextval, data_col
FROM source_table;
    

This sequence generates unique IDs for each inserted row by calling my_seq.nextval once per row.

Identify Repeating Operations

• Primary operation: Calling my_seq.nextval to get the next sequence number.
• How many times: Once for each row inserted.

How Execution Grows With Input

Each new row requires one call to get the next sequence number.

Input Size (n)	Approx. API Calls/Operations
10	10 calls to nextval
100	100 calls to nextval
1000	1000 calls to nextval

Pattern observation: The number of sequence calls grows directly with the number of rows inserted.

Final Time Complexity

Time Complexity: O(n)

This means the time to get sequence values grows linearly with the number of rows inserted.

Common Mistake

[X] Wrong: "Getting the next sequence value is a single call no matter how many rows we insert."

[OK] Correct: Each row needs its own unique number, so the sequence is called once per row, making the calls grow with the number of rows.

Interview Connect

Understanding how sequence calls scale helps you design efficient data loading and avoid surprises in performance when inserting many rows.

Self-Check

What if we batch multiple rows in one insert but use a single sequence call for all? How would the time complexity change?