catalyst
An abstract class for row used internal in Spark SQL, which only contain the columns as internal types.
Root class of SQL Parser Dialect, and we don't guarantee the binary compatibility for the future release, let's keep it as the internal interface for advanced user.
Root class of SQL Parser Dialect, and we don't guarantee the binary compatibility for the future release, let's keep it as the internal interface for advanced user.
Support for generating catalyst schemas for scala objects.
Support for generating catalyst schemas for scala objects. Note that unlike its companion object, this trait able to work in both the runtime and the compile time (macro) universe.
A CatalystConf that can be used for local testing.
Functions to convert Scala types to Catalyst types and vice versa.
A trivial conf that is empty.
A trivial conf that is empty. Used for testing when all relations are already filled in and the analyser needs only to resolve attribute references.
Type-inference utilities for POJOs and Java collections.
A default version of ScalaReflection that uses the runtime universe.
A JVM-global lock that should be used to prevent thread safety issues when using things in scala.reflect.*.
A JVM-global lock that should be used to prevent thread safety issues when using things in scala.reflect.*. Note that Scala Reflection API is made thread-safe in 2.11, but not yet for 2.10.* builds. See SI-6240 for more details.
A very simple SQL parser.
A very simple SQL parser. Based loosely on: https://github.com/stephentu/scala-sql-parser/blob/master/src/main/scala/parser.scala
Limitations:
This is currently included mostly for illustrative purposes. Users wanting more complete support for a SQL like language should checkout the HiveQL support in the sql/hive sub-project.
Provides a logical query plan Analyzer and supporting classes for performing analysis.
Provides a logical query plan Analyzer and supporting classes for performing analysis. Analysis consists of translating UnresolvedAttributes and UnresolvedRelations into fully typed objects using information in a schema Catalog.
A collection of implicit conversions that create a DSL for constructing catalyst data structures.
A collection of implicit conversions that create a DSL for constructing catalyst data structures.
scala> import org.apache.spark.sql.catalyst.dsl.expressions._ // Standard operators are added to expressions. scala> import org.apache.spark.sql.catalyst.expressions.Literal scala> Literal(1) + Literal(1) res0: org.apache.spark.sql.catalyst.expressions.Add = (1 + 1) // There is a conversion from 'symbols to unresolved attributes. scala> 'a.attr res1: org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute = 'a // These unresolved attributes can be used to create more complicated expressions. scala> 'a === 'b res2: org.apache.spark.sql.catalyst.expressions.EqualTo = ('a = 'b) // SQL verbs can be used to construct logical query plans. scala> import org.apache.spark.sql.catalyst.plans.logical._ scala> import org.apache.spark.sql.catalyst.dsl.plans._ scala> LocalRelation('key.int, 'value.string).where('key === 1).select('value).analyze res3: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan = Project [value#3] Filter (key#2 = 1) LocalRelation [key#2,value#3], []
Functions for attaching and retrieving trees that are associated with errors.
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.
Contains classes for enumerating possible physical plans for a given logical query plan.
A a collection of common abstractions for query plans as well as a base logical plan representation.
A framework for applying batches rewrite rules to trees, possibly to fixed point.
A library for easily manipulating trees of operators.
A library for easily manipulating trees of operators. Operators that extend TreeNode are granted the following interface:
- transform - accepts a partial function that is used to generate a new tree. When the partial function can be applied to a given tree segment, that segment is replaced with the result. After attempting to apply the partial function to a given node, the transform function recursively attempts to apply the function to that node's children.
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.