Window

LAG

Snowflake

Mengakses nilai dari baris sebelumnya dalam result set berdasarkan offset tertentu. Sangat berguna untuk perbandingan dengan periode sebelumnya.

Tipe hasil: Same as expressionDiperbarui: 6 Jan 2026

Syntax

SQL

LAG(expression [, offset [, default]]) OVER ([PARTITION BY partition_expr] ORDER BY order_expr)

Parameter

expressionanywajib

Kolom atau ekspresi yang nilainya akan diambil

ORDER BYclausewajib

Menentukan urutan baris untuk perhitungan LAG

offsetINTEGERopsional

Berapa baris ke belakang (default: 1)

Default: 1

defaultanyopsional

Nilai default jika tidak ada baris sebelumnya

PARTITION BYclauseopsional

Opsional. Membagi hasil ke dalam partition terpisah

Contoh Penggunaan

Perbandingan dengan Bulan Sebelumnya

SQL

1 SELECT
2   month,
3   revenue,
4   LAG(revenue) OVER (ORDER BY month) as prev_month_revenue,
5   revenue - LAG(revenue) OVER (ORDER BY month) as revenue_change
6 FROM monthly_sales;

Menampilkan revenue bulan ini vs bulan sebelumnya dan selisihnya.

Hasil

MONTH	REVENUE	PREV_MONTH_REVENUE	REVENUE_CHANGE
2024-01	100000	NULL	NULL
2024-02	120000	100000	20000
2024-03	115000	120000	-5000

Persentase Perubahan (MoM)

SQL

1 SELECT
2   month,
3   revenue,
4   LAG(revenue, 1, revenue) OVER (ORDER BY month) as prev_revenue,
5   ROUND((revenue - LAG(revenue, 1, revenue) OVER (ORDER BY month)) /
6         NULLIF(LAG(revenue, 1, revenue) OVER (ORDER BY month), 0) * 100, 2) as pct_change
7 FROM monthly_sales;

Menghitung persentase perubahan month-over-month.

Hasil

MONTH	REVENUE	PREV_REVENUE	PCT_CHANGE
2024-01	100000	100000	0.00
2024-02	120000	100000	20.00
2024-03	115000	120000	-4.17

LAG per Customer

SQL

1 SELECT
2   customer_id,
3   order_date,
4   order_total,
5   LAG(order_date) OVER (
6     PARTITION BY customer_id
7     ORDER BY order_date
8   ) as prev_order_date,
9   DATEDIFF('DAY',
10     LAG(order_date) OVER (PARTITION BY customer_id ORDER BY order_date),
11     order_date
12   ) as days_between_orders
13 FROM orders;

Menghitung jarak hari antar order untuk setiap customer.

Fungsi Terkait

LEADFIRST_VALUELAST_VALUENTH_VALUE

Kembali ke Snowflake Functions

1	SELECT
2	month,
3	revenue,
4	LAG(revenue) OVER (ORDER BY month) as prev_month_revenue,
5	revenue - LAG(revenue) OVER (ORDER BY month) as revenue_change
6	FROM monthly_sales;

1	SELECT
2	customer_id,
3	order_date,
4	order_total,
5	LAG(order_date) OVER (
6	PARTITION BY customer_id
7	ORDER BY order_date
8	) as prev_order_date,
9	DATEDIFF('DAY',
10	LAG(order_date) OVER (PARTITION BY customer_id ORDER BY order_date),
11	order_date
12	) as days_between_orders
13	FROM orders;