Pipelined join technique, both left and right are evaluation techniques that can be used to organize data.

The iterator does not provide the wait() function but it provides open(), next() and close() operations.

If the system makes repeated requests for tuples from the operation at the top of the table, it is called as demand driven pipeline. Each time an operation receives a request for tuples, it computes the next tuple or tuples to be returned and then returns that tuple.

Sorting is an inherently blocking operation i.e. output is not given until all the tuples from their input are examined

The result of each intermediate operation are created and then are used foe valuation of the next level operations, this evaluation is called as Materialized evaluation. This is not space effective as we need to construct the temporary relations which must be written to a disk.

If the results of one operation are passed on to the other, it is called as Pipelined. This can be used to evaluate several expressions simultaneously.

If the operations do not wait to produce tuples, then it is called as producer driven pipeline. IT does not wait to produce tuples but it produces tuples eagerly.

Join is not an inherently blocking algorithm. This is because all the tuples need not be examined to execute the join operation.

The usage of two buffers, with one continuing execution of the algorithm while the other is written is called as Double buffering. This makes the algorithm quicker by performing CPU operations simultaneously with the I/O operations.

Hybrid hash join is partially pipelined on the probe relation since it can output tuples from the first partition as tuples are received for the probe relation.