Combining two or more tables using values from a related column is one of the most common tasks when analyzing data. This is typically done by matching the values in the related column(s).

But this runs into problems because real world data often does NOT yield perfect matches.

This is particularly true when dealing with streaming data. For instance, imagine that you have two tables. A stock_portfolio table showing the time at which different trades for a particular stock were executed and another with the stock_prices. Both these tables are recorded with a timestamp with millisecond intervals.


TSLA 9.93 2024-02-02 14:29:10.753
TSLA 9.62 2024-02-02 14:29:52.806
TSLA 9.61 2024-02-02 14:30:43.379
TSLA 9.93 2024-02-02 14:32:35.397
TSLA 9.68 2024-02-02 14:41:38.263
TSLA 9.05 2024-02-02 14:45:00.480
TSLA 9.06 2024-02-02 14:45:32.556
TSLA 9.88 2024-02-02 15:04:29.979
TSLA 9.72 2024-02-02 15:06:40.404
TSLA 9.44 2024-02-02 15:23:07.893
TSLA 9.13 2024-02-02 15:23:21.083


TSLA 100.00 2024-02-02 14:29:20.264
TSLA 77.00 2024-02-02 14:30:51.040
TSLA 56.00 2024-02-02 14:45:41.192
TSLA 86.00 2024-02-02 15:06:48.475
TSLA 60.00 2024-02-02 15:23:12.587

For every trade in the stock_portfolio tables we would like to find a relevant stock price from the stock_prices table i.e. the nearest stock price. This requires us to combine the two tables on the timestamp column.

But we have a problem here. The time stamps for quotes and trades don’t always match.

Perform inexact joins using ASOF JOIN

We can solve this problem using an ASOF join. ASOF join in Snowflake joins two different time-series measures. For each row in the first time-series, the ASOF join takes from the second time-series a timestamp that meets both of the following criteria:

  1. The timestamp is the closest to the first timestamp.
  2. The timestamp is strictly prior or after or equal to the first timestamp.

ASOF join can take the timestamp of from Table A and find an entry in Table B where the timestamp is closest to the timestamp of the event from Table A corresponding to the closest match condition. Equal timestamp values are the closest if available.

SQL Query

An ASOF join query can look like the following:

  , price as stock_price
  , number_of_shares
  , transaction_timestamp
  , stock_price_asof  
  , price * number_of_shares as value
from stock_portfolio
asof join stock_prices
  match_condition (stock_portfolio.transaction_timestamp >= stock_prices.stock_price_asof)
  on stock_prices.symbol = stock_portfolio.symbol ;

This is the JOIN result:

TSLA 9.93 100.00 2024-02-02 14:29:20.264 2024-02-02 14:29:10.753 993.0000
TSLA 9.61 77.00 2024-02-02 14:30:51.040 2024-02-02 14:30:43.379 739.9700
TSLA 9.06 56.00 2024-02-02 14:45:41.192 2024-02-02 14:45:32.556 507.3600
TSLA 9.72 86.00 2024-02-02 15:06:48.475 2024-02-02 15:06:40.404 835.9200
TSLA 9.44 60.00 2024-02-02 15:23:12.587 2024-02-02 15:23:07.893 566.4000

The result has all rows from the stock_portfolio table joined with rows from the stock_prices table. For each timestamp from the stock_portfolio table, the query looks for a timestamp that is equal or prior to it from the stock_prices table. If no matching timestamp is found, NULL is inserted.

This query returns all rows from the bids table joined with records from the asks table that meet both the following criterion:

The stock column of the two tables has the same value The timestamp of the stock_prices record is prior to or equal to the timestamp of the stock_portfolio record.

See also: