Access patterns are used on both physical tables and views to specify the need for criteria against a set of columns. Failure to supply the criteria will result in a planning error, rather than a run-away source query. Access patterns can be applied in a set such that only one of the access patterns is required to be satisfied.

Currently any form of criteria referencing an affected column may satisfy an access pattern.

In federated database systems pushdown refers to decomposing the user level query into source queries that perform as much work as possible on their respective source system. Pushdown analysis requires knowledge of source system capabilities, which is provided to Teiid Spring Boot though the Connector API. Any work not performed at the source is then processed in Federate’s relational engine.

Based upon capabilities, Teiid Spring Boot will manipulate the query plan to ensure that each source performs as much joining, filtering, grouping, and so forth, as possible. In many cases, such as with join ordering, planning is a combination of standard relational techniques along with costing information, and heuristics for pushdown optimization.

Criteria and join push down are typically the most important aspects of the query to push down when performance is a concern. For information about how to read a plan to ensure that source queries are as efficient as possible, see Query plans.

A special optimization called a dependent join is used to reduce the rows returned from one of the two relations involved in a multi-source join. In a dependent join, queries are issued to each source sequentially rather than in parallel, with the results obtained from the first source used to restrict the records returned from the second. Dependent joins can perform some joins much faster by drastically reducing the amount of data retrieved from the second source and the number of join comparisons that must be performed.

The conditions when a dependent join is used are determined by the query planner based on access patterns, hints, and costing information. You can use the following types of dependent joins with Teiid Spring Boot:

You can use the following types of hints in Teiid Spring Boot to control dependent join behavior:

These can be placed in either the OPTION Clause or directly in the FROM Clause. As long as all Access Patterns can be met, the MAKEIND, MAKEDEP, and MAKENOTDEP hints override any use of costing information. MAKENOTDEP supersedes the other hints.

In the simplest scenario the engine will use IN clauses (or just equality predicates) to filter the values coming from the dependent side. If the number of values from the independent side exceeds the translators MaxInCriteriaSize, the values will be split into multiple IN predicates up to MaxDependentPredicates. When the number of independent values exceeds MaxInCriteriaSize*MaxDependentPredicates, then multiple dependent queries will be issued in parallel.

If the translator returns true for supportsDependentJoins, then the engine may provide the entire set of independent key values. This will occur when the number of independent values exceeds MaxInCriteriaSize*MaxDependentPredicates so that the translator may use specific logic to avoid issuing multiple queries as would happen in the simple scenario.

If the translator returns true for both supportsDependentJoins and supportsFullDependentJoins then a full pushdown may be chosen by the optimizer A full pushdown, sometimes also called as data-ship pushdown, is where all the data from independent side of the join is sent to dependent side. This has an added benefit of allowing the plan above the join to be eligible for pushdown as well. This is why the optimizer may choose to perform a full pushdown even when the number of independent values does not exceed MaxInCriteriaSize*MaxDependentPredicates. You may also force full pushdown using the MAKEDEP(JOIN) hint. The translator is typically responsible for creating, populating, and removing a temporary table that represents the independent side. For more information about how to use custom translators with dependent, key, and full pushdown, see Dependent join pushdown in Translator Development. NOTE: By default, Key/Full Pushdown is compatible with only a subset of JDBC translators. To use it, set the translator override property enableDependentJoins to true. The JDBC source must allow for the creation of temporary tables, which typically requires a Hibernate dialect. The following translators are compatible with this feature: DB2, Derby, H2, Hana, HSQL, MySQL, Oracle, PostgreSQL, SQL Server, SAP IQ, Sybase, Teiid, and Teradata.

Copy criteria is an optimization that creates additional predicates based upon combining join and where clause criteria. For example, equi-join predicates (source1.table.column = source2.table.column) are used to create new predicates by substituting source1.table.column for source2.table.column and vice versa. In a cross-source scenario, this allows for where criteria applied to a single side of the join to be applied to both source queries

Teiid Spring Boot ensures that each pushdown query only projects the symbols required for processing the user query. This is especially helpful when querying through large intermediate view layers.

Partial aggregate pushdown allows for grouping operations above multi-source joins and unions to be decomposed so that some of the grouping and aggregate functions may be pushed down to the sources.

An optional or redundant join is one that can be removed by the optimizer. The optimizer will automatically remove inner joins based upon a foreign key or left outer joins when the outer results are unique.

The optional join hint goes beyond the automatic cases to indicate to the optimizer that a joined table should be omitted if none of its columns are used by the output of the user query or in a meaningful way to construct the results of the user query. This hint is typically only used in view layers containing multi-source joins.

The optional join hint is applied as a comment on a join clause. It can be applied in both ANSI and non-ANSI joins. With non-ANSI joins an entire joined table may be marked as optional.

Suppose this example defines a view layer X. If X is queried in such a way as to not need b.column2, then the optional join hint will cause b to be omitted from the query plan. The result would be the same as if X were defined as:

In this example the ANSI join syntax allows for the join of a and b to be marked as optional. Suppose this example defines a view layer X. Only if both column a.column1 and b.column2 are not needed, for example, SELECT column3 FROM X will the join be removed.

The optional join hint will not remove a bridging table that is still required.

Suppose this example defines a view layer X. If b.column2 or c.column3 are solely required by a query to X, then the join on a be removed. However if a.column1 or both b.column2 and c.column3 are needed, then the optional join hint will not take effect.

When a join clause is omitted via the optional join hint, the relevant criteria is not applied. Thus it is possible that the query results may not have the same cardinality or even the same row values as when the join is fully applied.

Left/right outer joins where the inner side values are not used and whose rows under go a distinct operation will automatically be treated as an optional join and do not require a hint.

Teiid Spring Boot user and transformation queries can contain a meta source hint that can provide additional information to source queries. The source hint has the following form:

Union partitioning is inferred from the transformation/inline view. If one (or more) of the UNION columns is defined by constants and/or has WHERE clause IN predicates containing only constants that make each branch mutually exclusive, then the UNION is considered partitioned. UNION ALL must be used and the UNION cannot have a LIMIT, WITH, or ORDER BY clause (although individual branches may use LIMIT, WITH, or ORDER BY). Partitioning values should not be null.

The view is partitioned on column x, since the first branch can only be the value 1 and the second branch can only be the values 2 or 3.

The concept of a partitioned union is used for performing partition-wise joins, in Updatable Views, and Partial Aggregate Pushdown. These optimizations are also applied when using the multi-source feature as well - which introduces an explicit partitioning column.

Partition-wise joins take a join of unions and convert the plan into a union of joins, such that only matching partitions are joined against one another. If you want a partition-wise join to be performed implicit without the need for an explicit join predicate on the partitioning column, set the model/schema property implicit_partition.columnName to name of the partitioning column used on each partitioned view in the model/schema.

Teiid Spring Boot also incorporates many standard relational techniques to ensure efficient query plans.

Some source systems only allow "relationship" queries logically producing left outer join results. Even when queried with an inner join, Teiid Spring Boot will attempt to form an appropriate left outer join. These sources are restricted to use with key joins. In some circumstances foreign key relationships on the same source should not be traversed at all or with the referenced table on the outer side of join. The extension property teiid_rel:allow-join can be used on the foreign key to further restrict the pushdown behavior. With a value of "false" no join pushdown will be allowed, and with a value of "inner" the referenced table must be on the inner side of the join. If the join pushdown is prevented, the join will be processed as a federated join.