Final answer:
Data streams can be joined using an Inner Join, combining matching rows from both streams, or a Left (or Right) Outer Join, including all rows from one stream and matched rows from the other with nulls for non-matching rows.
Step-by-step explanation:
Two common methods to join data streams with a Join tool include using an Inner Join or a Left (or Right) Outer Join. An Inner Join combines data from two streams based on matching values in specified key columns and includes only the rows that have matching values in both streams. On the other hand, a Left Outer Join will include all rows from the left stream and the matched rows from the right stream, providing nulls for non-matching rows from the right stream. The equivalent is true for a Right Outer Join but in the opposite direction.
Suppose you have two data streams, Stream A and B. For an Inner Join, if Stream A has a column ID with values 1, 2, and 3, and Stream B has column ID with values 2, 3, and 4, the resulting dataset after the join would only include rows with IDs 2 and 3. For a Left Outer Join, the resulting dataset would include IDs 1, 2, and 3, with ID 1 from Stream A having null values for the columns from Stream B.