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The hash join is an example of a join algorithm and is used in the implementation of a relational database management system.All variants of hash join algorithms involve building hash tables from the tuples of one or both of the joined relations, and subsequently probing those tables so that only tuples with the same hash code need to be compared for equality in equijoins.
For example, one variant of the block nested loop join reads an entire page of tuples into memory and loads them into a hash table. It then scans S {\displaystyle S} , and probes the hash table to find S {\displaystyle S} tuples that match any of the tuples in the current page of R {\displaystyle R} .
The set of query plans examined is formed by examining the possible access paths (e.g., primary index access, secondary index access, full file scan) and various relational table join techniques (e.g., merge join, hash join, product join). The search space can become quite large depending on the complexity of the SQL query. There are two types ...
A bitmap join index is used for low-cardinality columns (i.e., columns containing fewer than 300 distinct values, according to the Oracle documentation): it combines low-cardinality columns from multiple related tables. The example Oracle uses is that of an inventory system, where different suppliers provide different parts.
Note (4): Used for InMemory ColumnStore index, temporary hash index for hash join, Non/Cluster & fill factor. Note (5): InnoDB automatically generates adaptive hash index [125] entries as needed. Note (6): Can be implemented using Function-based Indexes in Oracle 8i and higher, but the function needs to be used in the sql for the index to be used.
Ingres supports joins with hash join, sort-merge join, and nested loop join algorithms. The query optimizer determines which type of join algorithm to use based on its analysis of the query. Nested-loop joins are most often seen on disjoint queries, where correlation variables and table names are arbitrarily used in random order.
A distributed hash table (DHT) is a distributed system that provides a lookup service similar to a hash table. Key–value pairs are stored in a DHT, and any participating node can efficiently retrieve the value associated with a given key.
For example, if the input is 123 456 789 and the hash table size 10 000, then squaring the key produces 15 241 578 750 190 521, so the hash code is taken as the middle 4 digits of the 17-digit number (ignoring the high digit) 8750. The mid-squares method produces a reasonable hash code if there is not a lot of leading or trailing zeros in the key.