Join Algorithms interview questions

1. A.an algorithm that scans the outer input and, for each row, probes the inner input, ideal when one side is small or indexed
2. B.a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
3. C.an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
4. D.the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible

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1. A.Hash join
2. B.Broadcast join
3. C.Nested loop join
4. D.Merge join

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1. A.Nested loop join — an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
2. B.Nested loop join — an algorithm that scans the outer input and, for each row, probes the inner input, ideal when one side is small or indexed
3. C.Nested loop join — a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together
4. D.Nested loop join — the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible

Answer + AI explanation with Pro

1. A.an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
2. B.the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible
3. C.an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
4. D.a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together

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1. A.Nested loop join
2. B.Partitioned join
3. C.Hash join
4. D.Merge join

Answer + AI explanation with Pro

1. A.Hash join — the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible
2. B.Hash join — an algorithm that scans the outer input and, for each row, probes the inner input, ideal when one side is small or indexed
3. C.Hash join — an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
4. D.Hash join — an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins

Answer + AI explanation with Pro

1. A.an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
2. B.a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
3. C.the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible
4. D.an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins

Answer + AI explanation with Pro

1. A.Merge join
2. B.Nested loop join
3. C.Partitioned join
4. D.Broadcast join

Answer + AI explanation with Pro

1. A.Merge join — an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
2. B.Merge join — an algorithm that scans the outer input and, for each row, probes the inner input, ideal when one side is small or indexed
3. C.Merge join — a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together
4. D.Merge join — an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows

Answer + AI explanation with Pro

1. A.an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
2. B.the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible
3. C.an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
4. D.a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling

Answer + AI explanation with Pro

1. A.Broadcast join
2. B.Join order
3. C.Nested loop join
4. D.Merge join

Answer + AI explanation with Pro

1. A.Join order — a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
2. B.Join order — an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
3. C.Join order — the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible
4. D.Join order — a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together

Answer + AI explanation with Pro

1. A.a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
2. B.a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together
3. C.an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
4. D.the sequence in which the optimizer combines tables, chosen to keep intermediate result sizes as small as possible

Answer + AI explanation with Pro

1. A.Merge join
2. B.Nested loop join
3. C.Broadcast join
4. D.Hash join

Answer + AI explanation with Pro

1. A.Broadcast join — an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
2. B.Broadcast join — an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
3. C.Broadcast join — a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
4. D.Broadcast join — a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together

Answer + AI explanation with Pro

1. A.an algorithm that scans the outer input and, for each row, probes the inner input, ideal when one side is small or indexed
2. B.an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
3. C.a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
4. D.a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together

Answer + AI explanation with Pro

1. A.Merge join
2. B.Broadcast join
3. C.Hash join
4. D.Partitioned join

Answer + AI explanation with Pro

1. A.Partitioned join — a distributed strategy that copies a small table to every node so each can join its local partition without reshuffling
2. B.Partitioned join — an algorithm that consumes two inputs already sorted on the key and advances through them in lockstep to match rows
3. C.Partitioned join — an algorithm that builds an in-memory hash table on one input and probes it with the other, favored for large unsorted equality joins
4. D.Partitioned join — a distributed strategy that repartitions both inputs on the join key across nodes so matching rows land together

Answer + AI explanation with Pro