Catalyst is a library for manipulating relational query plans.
Catalyst is a library for manipulating relational query plans. All classes in catalyst are considered an internal API to Spark SQL and are subject to change between minor releases.
A set of classes that can be used to represent trees of relational expressions.
A set of classes that can be used to represent trees of relational expressions. A key goal of the expression library is to hide the details of naming and scoping from developers who want to manipulate trees of relational operators. As such, the library defines a special type of expression, a NamedExpression in addition to the standard collection of expressions.
A library of standard expressions (e.g., Add, EqualTo), aggregates (e.g., SUM, COUNT), and other computations (e.g. UDFs). Each expression type is capable of determining its output schema as a function of its children's output schema.
Some expression are named and thus can be referenced by later operators in the dataflow graph.
The two types of named expressions are AttributeReferences and Aliases.
AttributeReferences refer to attributes of the input tuple for a given operator and form
the leaves of some expression trees. Aliases assign a name to intermediate computations.
For example, in the SQL statement SELECT a+b AS c FROM ..., the expressions a and b would
be represented by AttributeReferences and c would be represented by an Alias.
During analysis, all named expressions are assigned a globally unique expression id, which can be used for equality comparisons. While the original names are kept around for debugging purposes, they should never be used to check if two attributes refer to the same value, as plan transformations can result in the introduction of naming ambiguity. For example, consider a plan that contains subqueries, both of which are reading from the same table. If an optimization removes the subqueries, scoping information would be destroyed, eliminating the ability to reason about which subquery produced a given attribute.
The result of expressions can be evaluated using the Expression.apply(Row) method.
A collection of generators that build custom bytecode at runtime for performing the evaluation of catalyst expression.
A collection of generators that build custom bytecode at runtime for performing the evaluation of catalyst expression.