Join algorithms (nested loop, sort-merge, hash join) in DBMS Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to describe the basic operation of a nested loop join.

DBMS Theory

For each row in the outer table, the algorithm scans [1] rows in the inner table to find matching join keys.

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Ano

Ball

Cone

Dsome

Attempts:

3 left

💡 Hint

Common Mistakes

Assuming only one or some rows are checked instead of all.

Confusing nested loop join with more efficient join types.

Nested loop join compares each row of the outer table with all rows of the inner table to find matches.

2fill in blank

medium

Complete the code to describe the first step of a sort-merge join.

DBMS Theory

The first step in a sort-merge join is to [1] both input tables on the join key.

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Asort

Bhash

Cscan

Dfilter

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing sorting with hashing or scanning.

Skipping the sorting step before merging.

Sort-merge join requires both tables to be sorted on the join key before merging.

3fill in blank

hard

Fix the error in the description of a hash join.

DBMS Theory

In a hash join, the algorithm builds a hash table on the [1] table and probes it with rows from the [2] table.

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Aouter

Blarger

Csmaller

Dinner

Attempts:

3 left

💡 Hint

Common Mistakes

Building the hash table on the larger table, which is inefficient.

Confusing which table is hashed and which is probed.

Hash join builds a hash table on the smaller table to optimize memory usage and probes it with rows from the other table.

4fill in blank

hard

Fill both blanks to complete the description of sort-merge join conditions.

DBMS Theory

Sort-merge join requires both tables to be [1] on the join key and then [2] through them to find matching rows.

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Asorted

Bhashed

Cmerged

Dscanned

Attempts:

3 left

💡 Hint

Common Mistakes

Using hashing instead of sorting.

Confusing scanning with merging.

Sort-merge join first sorts both tables and then scans through them to find matching rows.

5fill in blank

hard

Fill all three blanks to complete the hash join process description.

DBMS Theory

The hash join algorithm first [1] the smaller table into a hash table, then [2] the larger table, and finally [3] matching rows using the hash table.

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Abuilds

Bscans

Cprobes

Dsorts

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up scanning and building steps.

Using sorting instead of hashing in hash join.

Hash join builds a hash table from the smaller table, scans the larger table, and probes the hash table to find matching rows.

Practice

1. Which join algorithm compares each row of one table with every row of another table to find matching pairs?

easy

A. Index join

B. Sort-merge join

C. Hash join

D. Nested loop join

Solution

1. Step 1: Understand the nested loop join process

   Nested loop join works by taking each row from the first table and comparing it with every row in the second table to find matches.

2. Step 2: Compare with other join types

   Sort-merge join sorts and merges, hash join uses hashing, and index join uses indexes, so they do not compare every pair.

3. Final Answer:

   Nested loop join -> Option D

4. Quick Check:

   Every row compared = Nested loop join [OK]

Hint: Nested loop = check all pairs one by one [OK]

Common Mistakes:

• Confusing nested loop with hash join
• Thinking sort-merge compares all pairs
• Assuming index join is same as nested loop

2. Which of the following is the correct description of a hash join algorithm?

easy

A. Sort both tables and merge matching rows

B. Use a hash table to find matching rows quickly

C. Compare each row of one table with every row of another

D. Use indexes to speed up join operations

Solution

1. Step 1: Recall hash join working

   Hash join builds a hash table on one table's join key to quickly find matching rows from the other table.

2. Step 2: Eliminate other options

   Sorting and merging is sort-merge join, comparing all pairs is nested loop, and using indexes is index join, not hash join.

3. Final Answer:

   Use a hash table to find matching rows quickly -> Option B

4. Quick Check:

   Hash table = fast matching [OK]

Hint: Hash join uses hash table for fast lookup [OK]

Common Mistakes:

• Mixing hash join with sort-merge join
• Thinking hash join compares all pairs
• Confusing index usage with hash join

3. Consider two tables A and B, each with 1000 rows. Which join algorithm is likely to perform best if both tables are already sorted on the join key?

medium

A. Nested loop join

B. Hash join

C. Sort-merge join

D. Cartesian join

Solution

1. Step 1: Analyze the condition of sorted tables

   Since both tables are sorted on the join key, sort-merge join can efficiently merge them by scanning once through both tables.

2. Step 2: Compare with other algorithms

   Nested loop join checks all pairs (slow), hash join builds hash table (extra work), Cartesian join is unrelated and very expensive.

3. Final Answer:

   Sort-merge join -> Option C

4. Quick Check:

   Sorted tables = sort-merge join best [OK]

Hint: Sorted tables? Use sort-merge join [OK]

Common Mistakes:

• Choosing nested loop for sorted tables
• Assuming hash join is always fastest
• Confusing Cartesian join with normal join

4. A database query uses a hash join but runs very slowly. Which of the following is a likely cause?

medium

A. The hash table does not fit in memory causing disk spills

B. The join keys are unique in both tables

C. Both tables are already sorted

D. The nested loop join was used instead

Solution

1. Step 1: Understand hash join memory use

   Hash join builds a hash table in memory. If it is too large, it spills to disk, slowing performance.

2. Step 2: Evaluate other options

   Sorted tables do not slow hash join, unique keys help performance, and nested loop join is a different algorithm.

3. Final Answer:

   The hash table does not fit in memory causing disk spills -> Option A

4. Quick Check:

   Memory overflow = slow hash join [OK]

Hint: Hash join slow? Check memory size for hash table [OK]

Common Mistakes:

• Blaming sorted tables for hash join slowness
• Ignoring memory limits in hash join
• Confusing nested loop join with hash join

5. You have two large tables to join on a key. Table A fits in memory but Table B is very large and unsorted. Which join algorithm is best to minimize disk I/O and why?

hard

A. Hash join, because building a hash on smaller Table A allows fast matching

B. Sort-merge join, because sorting both tables reduces I/O

C. Cartesian join, because it joins all rows regardless of keys

D. Nested loop join, because it checks all pairs without sorting

Solution

1. Step 1: Consider table sizes and memory

   Table A fits in memory, so building a hash table on it is efficient. Table B is large and unsorted, so sorting it would be expensive.

2. Step 2: Choose join algorithm minimizing disk I/O

   Hash join uses the smaller table in memory to quickly find matches in the larger table, reducing disk reads compared to sorting or nested loops.

3. Final Answer:

   Hash join, because building a hash on smaller Table A allows fast matching -> Option A

4. Quick Check:

   Small table in memory = hash join best [OK]

Hint: Small table fits memory? Use hash join [OK]

Common Mistakes:

• Choosing nested loop for large tables
• Preferring sort-merge without considering sorting cost
• Confusing Cartesian join with normal join