Hash Joins

What is a Hash-Join

A hash join is one of the join methods used by the Oracle optimizer to combine rows from two tables based on a join condition. They are generally efficient, but their effectiveness depends on the specific use case and the nature of the data. For example, when no indexes can be used or the query involves large datasets. It is particularly effective when joining large tables because it minimizes disk I/O.

How Does a Hash-Join Work

The process involves two main steps

1. The Build Phase:

   • The optimizer the smaller dataset or table, referred to as the build table.

   • It scans the build table and creates a hash table in memory based on the join key 

   • A hash function is applied to the join key values to distribute rows into "buckets" in the hash table. 

   • If the hash table exceeds available memory, it is partitioned and is written to the temporary tablespace. 

2. Probe Phase:

   • The larger dataset or table, referred to as the probe table, is scanned and its rows are matched against the hash table to find matches

   • For each row in the probe table, the same hash function is applied to its join key 

   • Oracle uses the resulting hash value to look up the matching bucket in the hash table created from the build table. 

   • If a match is found, the rows are joined; if not, the row is discarded. 

When Does Oracle Choose a Hash-Join

Oracle chooses a hash-join in scenarios such as, although not limited to, the following

• Lack of Indexes: When neither of the tables in the join has a suitable index for other join methods.

• Large Data Sets: The optimizer will typically default to a hash join on large datasets.

• Efficiency: When the optimizer determines that a hash join will be faster than other join methods 

Advantages of a Hash-Join

The following are some of the advantages of hash-join

• Efficient for Large Datasets: It avoids the need for sorting (as in merge joins) or repeated table access (as in nested loop joins).

• Memory-Optimized: By creating a hash table in memory, hash joins reduce disk I/O compared to other methods.

Disadvantages of a Hash-Join

The following are some of the disadvantages of hash-join

• Memory Overhead: If the hash table exceeds the allocated PGA memory, temporary disk storage will be used, which in turn can degrade performance.

• Small Datasets: Hash joins may not be the best choice for small tables due to the overhead of building and probing the hash table.

• Data Skew: If the data distribution in the join key is highly skewed, the hash table may become unbalanced, leading to inefficient bucket usage.

Comparisons with Other Joins

Below is a handy guide with a extensive list of comparisons between join types, with additional strengths and weaknesses or each.

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Published 29th November 2024