Dealing with time series data is a common challenge for data engineers, especially when joining two tables where dates or timestamps do not align perfectly. For instance, Table 1 may have dates missing in Table 2 and vice versa.

Typically, this problem is addressed by generating a table that includes dates for every day and then joining this table with both Table 1 and Table 2 to obtain a daily view. Alternatively, one might perform a left join between Table 1 and Table 2 and then forward fill the null values with the last known value. Both methods can be cumbersome.

However, Snowflake has introduced a new feature to tackle this problem efficiently—the 'ASOF' join. This feature joins two time series tables and fills in null values with the last known value, streamlining the process significantly.

Enough of the theory, let's deep dive into a example:

Table 1: Contains exchange rates on specific dates.

Date | Exchange Rate |

2023-04-01 | 93 |

2023-04-03 | 94 |

2023-04-06 | 92 |

2023-04-08 | 91 |

2023-04-10 | 90 |

Table 2: Contains payment amounts on specific days.

The typical approach to calculate the exchanged amount, even for dates missing exchange rates (assuming the rate stays the same until updated), involves complex SQL queries:

```
WITH all_dates AS (
SELECT
p.date,
p.payment_amount,
e.exchange_rate
FROM payments p
LEFT JOIN exchange e ON p.date = e.date
),
filled_exchange_rates AS (
SELECT
date,
payment_amount,
-- Use LAST_VALUE to carry forward the non-null values and IGNORE NULLS
LAST_VALUE(exchange_rate) IGNORE NULLS OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS exchange_rate
FROM all_dates
)
SELECT
date,
payment_amount,
exchange_rate,
payment_amount * exchange_rate AS exchanged_amount
FROM filled_exchange_rates
ORDER BY date;
```

**Result:**

**Streamlining with Snowflake's ASOF Join**

Snowflake's ASOF join can simplify these calculations significantly:

```
select P.date, P.payment_amount,
P.payment_amount * E.exchange_rate as exchanged_amount
from PAYMENTS P
ASOF join exchange E
MATCH_CONDITION (P.date >= E.date);
```

Result:

**Explanation**

**ASOF Join Condition**: Instead of a simple LEFT JOIN, an ASOF JOIN is specified, allowing for a time-sensitive match.**MATCHING CONDITIONS Clause**: This clause is specific to Snowflake's ASOF join syntax. It specifies that each payment should be aligned with the last known exchange rate on or before the payment date, ensuring that the exchange rate applied is the latest available up to that day.**Column Selection and Calculation**: The query selects dates and amounts from both tables and calculates the exchanged amount by multiplying the payment amount by the applicable exchange rate.

For a more in-depth explanation and additional examples, you can refer to the following links: