org.apache.spark.sql.catalyst.expressions.aggregate
to estimate the cardinality of.
the maximum estimation error allowed.
Allocate enough words to store all registers.
Allocate enough words to store all registers.
The schema of the aggregation buffer.
The schema of the aggregation buffer.
Returns the tree node at the specified number.
Returns the tree node at the specified number. Numbers for each node can be found in the numberedTreeString.
Returns a string representing the arguments to this node, minus any children
Returns a string representing the arguments to this node, minus any children
Returns a 'scala code' representation of this TreeNode and its children.
Returns a 'scala code' representation of this TreeNode and its children. Intended for use
when debugging where the prettier toString function is obfuscating the actual structure. In the
case of 'pure' TreeNodes that only contain primitives and other TreeNodes, the result can be
pasted in the REPL to build an equivalent Tree.
Checks the input data types, returns TypeCheckResult.success if it's valid,
or returns a TypeCheckResult with an error message if invalid.
Checks the input data types, returns TypeCheckResult.success if it's valid,
or returns a TypeCheckResult with an error message if invalid.
Note: it's not valid to call this method until childrenResolved == true.
to estimate the cardinality of.
Returns a Seq of the children of this node.
Returns a Seq of the children of this node. Children should not change. Immutability required for containsChild optimization
Returns true if all the children of this expression have been resolved to a specific schema and false if any still contains any unresolved placeholders.
Returns true if all the children of this expression have been resolved to a specific schema and false if any still contains any unresolved placeholders.
Returns a Seq containing the result of applying a partial function to all elements in this tree on which the function is defined.
Returns a Seq containing the result of applying a partial function to all elements in this tree on which the function is defined.
Finds and returns the first TreeNode of the tree for which the given partial function is defined (pre-order), and applies the partial function to it.
Finds and returns the first TreeNode of the tree for which the given partial function is defined (pre-order), and applies the partial function to it.
Returns the DataType of the result of evaluating this expression.
Returns the DataType of the result of evaluating this expression. It is
invalid to query the dataType of an unresolved expression (i.e., when resolved == false).
Result of the aggregate function when the input is empty.
Result of the aggregate function when the input is empty. This is currently only used for the proper rewriting of distinct aggregate functions.
Returns true when the current expression always return the same result for fixed inputs from children.
Returns true when the current expression always return the same result for fixed inputs from children.
Note that this means that an expression should be considered as non-deterministic if: - if it relies on some mutable internal state, or - if it relies on some implicit input that is not part of the children expression list. - if it has non-deterministic child or children.
An example would be SparkPartitionID that relies on the partition id returned by TaskContext.
By default leaf expressions are deterministic as Nil.forall(_.deterministic) returns true.
Estimate the bias using the raw estimates with their respective biases from the HLL++ appendix.
Estimate the bias using the raw estimates with their respective biases from the HLL++ appendix. We currently use KNN interpolation to determine the bias (as suggested in the paper).
Compute the HyperLogLog estimate.
Compute the HyperLogLog estimate.
Variable names in the HLL++ paper match variable names in the code.
Faster version of equality which short-circuits when two treeNodes are the same instance.
Faster version of equality which short-circuits when two treeNodes are the same instance.
We don't just override Object.equals, as doing so prevents the scala compiler from
generating case class equals methods
Find the first TreeNode that satisfies the condition specified by f.
Find the first TreeNode that satisfies the condition specified by f.
The condition is recursively applied to this node and all of its children (pre-order).
Returns a Seq by applying a function to all nodes in this tree and using the elements of the resulting collections.
Returns a Seq by applying a function to all nodes in this tree and using the elements of the resulting collections.
An aggregate function is not foldable.
An aggregate function is not foldable.
Runs the given function on this node and then recursively on children.
Runs the given function recursively on children then on this node.
Returns an GeneratedExpressionCode, which contains Java source code that can be used to generate the result of evaluating the expression on an input row.
Returns an GeneratedExpressionCode, which contains Java source code that can be used to generate the result of evaluating the expression on an input row.
a CodeGenContext
GeneratedExpressionCode
Returns Java source code that can be compiled to evaluate this expression.
Returns Java source code that can be compiled to evaluate this expression. The default behavior is to call the eval method of the expression. Concrete expression implementations should override this to do actual code generation.
a CodeGenContext
an GeneratedExpressionCode with unique terms.
Java source code
Appends the string represent of this node and its children to the given StringBuilder.
Appends the string represent of this node and its children to the given StringBuilder.
The i-th element in lastChildren indicates whether the ancestor of the current node at
depth i + 1 is the last child of its own parent node. The depth of the root node is 0, and
lastChildren for the root node should be empty.
Fill all words with zeros.
Fill all words with zeros.
Attributes of fields in input aggregation buffers (immutable aggregation buffers that are merged with mutable aggregation buffers in the merge() function or merge expressions).
Attributes of fields in input aggregation buffers (immutable aggregation buffers that are merged with mutable aggregation buffers in the merge() function or merge expressions). These attributes are created automatically by cloning the aggBufferAttributes.
The offset of this function's start buffer value in the underlying shared input aggregation buffer.
The offset of this function's start buffer value in the underlying shared input aggregation
buffer. An input aggregation buffer is used when we merge two aggregation buffers together in
the update() function and is immutable (we merge an input aggregation buffer and a mutable
aggregation buffer and then store the new buffer values to the mutable aggregation buffer).
An input aggregation buffer may contain extra fields, such as grouping keys, at its start, so mutableAggBufferOffset and inputAggBufferOffset are often different.
For example, say we have a grouping expression, key, and two aggregate functions,
avg(x) and avg(y). In the shared input aggregation buffer, the position of the first
buffer value of avg(x) will be 1 and the position of the first buffer value of avg(y)
will be 3 (position 0 is used for the value of key):
avg(x) inputAggBufferOffset = 1 | v +--------+--------+--------+--------+--------+ | key | sum1 | count1 | sum2 | count2 | +--------+--------+--------+--------+--------+ ^ | avg(y) inputAggBufferOffset = 3
Expected input types from child expressions.
Expected input types from child expressions. The i-th position in the returned seq indicates the type requirement for the i-th child.
The possible values at each position are: 1. a specific data type, e.g. LongType, StringType. 2. a non-leaf abstract data type, e.g. NumericType, IntegralType, FractionalType.
Creates a copy of this type of tree node after a transformation.
Creates a copy of this type of tree node after a transformation. Must be overridden by child classes that have constructor arguments that are not present in the productIterator.
the new product arguments.
Returns a Seq containing the result of applying the given function to each node in this tree in a preorder traversal.
Returns a Seq containing the result of applying the given function to each node in this tree in a preorder traversal.
the function to be applied.
Returns a copy of this node where f has been applied to all the nodes children.
Returns a copy of this node where f has been applied to all the nodes children.
Merge the HLL buffers by iterating through the registers in both buffers and select the maximum number of leading zeros for each register.
Merge the HLL buffers by iterating through the registers in both buffers and select the maximum number of leading zeros for each register.
The offset of this function's first buffer value in the underlying shared mutable aggregation buffer.
The offset of this function's first buffer value in the underlying shared mutable aggregation buffer.
For example, we have two aggregate functions avg(x) and avg(y), which share the same
aggregation buffer. In this shared buffer, the position of the first buffer value of avg(x)
will be 0 and the position of the first buffer value of avg(y) will be 2:
avg(x) mutableAggBufferOffset = 0 | v +--------+--------+--------+--------+ | sum1 | count1 | sum2 | count2 | +--------+--------+--------+--------+ ^ | avg(y) mutableAggBufferOffset = 2
Returns the name of this type of TreeNode.
Returns the name of this type of TreeNode. Defaults to the class name.
Returns a string representation of the nodes in this tree, where each operator is numbered.
Args to the constructor that should be copied, but not transformed.
Args to the constructor that should be copied, but not transformed. These are appended to the transformed args automatically by makeCopy
Returns a user-facing string representation of this expression's name.
Returns a user-facing string representation of this expression's name. This should usually match the name of the function in SQL.
Returns a user-facing string representation of this expression, i.
Returns a user-facing string representation of this expression, i.e. does not have developer centric debugging information like the expression id.
the maximum estimation error allowed.
Returns true if this expression and all its children have been resolved to a specific schema
and input data types checking passed, and false if it still contains any unresolved
placeholders or has data types mismatch.
Returns true if this expression and all its children have been resolved to a specific schema
and input data types checking passed, and false if it still contains any unresolved
placeholders or has data types mismatch.
Implementations of expressions should override this if the resolution of this type of
expression involves more than just the resolution of its children and type checking.
Returns true when two expressions will always compute the same result, even if they differ cosmetically (i.
Returns true when two expressions will always compute the same result, even if they differ cosmetically (i.e. capitalization of names in attributes may be different).
Returns the hash for this expression.
Returns the hash for this expression. Expressions that compute the same result, even if they differ cosmetically should return the same hash.
String representation of this node without any children
String representation of this node without any children
The arguments that should be included in the arg string.
The arguments that should be included in the arg string. Defaults to the productIterator.
Indicates if this function supports partial aggregation.
Indicates if this function supports partial aggregation. Currently Hive UDAF is the only one that doesn't support partial aggregation.
Wraps this AggregateFunction in an AggregateExpression and set isDistinct field of the AggregateExpression to the given value because AggregateExpression is the container of an AggregateFunction, aggregation mode, and the flag indicating if this aggregation is distinct aggregation or not.
Wraps this AggregateFunction in an AggregateExpression and set isDistinct field of the AggregateExpression to the given value because AggregateExpression is the container of an AggregateFunction, aggregation mode, and the flag indicating if this aggregation is distinct aggregation or not. An AggregateFunction should not be used without being wrapped in an AggregateExpression.
Wraps this AggregateFunction in an AggregateExpression because AggregateExpression is the container of an AggregateFunction, aggregation mode, and the flag indicating if this aggregation is distinct aggregation or not.
Wraps this AggregateFunction in an AggregateExpression because AggregateExpression is the container of an AggregateFunction, aggregation mode, and the flag indicating if this aggregation is distinct aggregation or not. An AggregateFunction should not be used without being wrapped in an AggregateExpression.
Returns the string representation of this expression that is safe to be put in code comments of generated code.
Returns the string representation of this expression that is safe to be put in code comments of generated code.
Returns a copy of this node where rule has been recursively applied to the tree.
Returns a copy of this node where rule has been recursively applied to the tree.
When rule does not apply to a given node it is left unchanged.
Users should not expect a specific directionality. If a specific directionality is needed,
transformDown or transformUp should be used.
the function use to transform this nodes children
Returns a copy of this node where rule has been recursively applied to all the children of
this node.
Returns a copy of this node where rule has been recursively applied to all the children of
this node. When rule does not apply to a given node it is left unchanged.
the function used to transform this nodes children
Returns a copy of this node where rule has been recursively applied to it and all of its
children (pre-order).
Returns a copy of this node where rule has been recursively applied to it and all of its
children (pre-order). When rule does not apply to a given node it is left unchanged.
the function used to transform this nodes children
Returns a copy of this node where rule has been recursively applied first to all of its
children and then itself (post-order).
Returns a copy of this node where rule has been recursively applied first to all of its
children and then itself (post-order). When rule does not apply to a given node, it is left
unchanged.
the function use to transform this nodes children
Returns a string representation of the nodes in this tree
Returns a string representation of the nodes in this tree
The rsd of HLL++ is always equal to or better than the rsd requested.
The rsd of HLL++ is always equal to or better than the rsd requested.
This method returns the rsd this instance actually guarantees.
the actual rsd.
Update the HLL++ buffer.
Update the HLL++ buffer.
Variable names in the HLL++ paper match variable names in the code.
Returns a copy of this node with the children replaced.
Returns a copy of this node with the children replaced. TODO: Validate somewhere (in debug mode?) that children are ordered correctly.
Returns a copy of this ImperativeAggregate with an updated mutableAggBufferOffset.
Returns a copy of this ImperativeAggregate with an updated mutableAggBufferOffset. This new copy's attributes may have different ids than the original.
Returns a copy of this ImperativeAggregate with an updated mutableAggBufferOffset.
Returns a copy of this ImperativeAggregate with an updated mutableAggBufferOffset. This new copy's attributes may have different ids than the original.
HyperLogLog++ (HLL++) is a state of the art cardinality estimation algorithm. This class implements the dense version of the HLL++ algorithm as an Aggregate Function.
This implementation has been based on the following papers: HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm http://algo.inria.fr/flajolet/Publications/FlFuGaMe07.pdf
HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en/us/pubs/archive/40671.pdf
Appendix to HyperLogLog in Practice: Algorithmic Engineering of a State of the Art Cardinality Estimation Algorithm https://docs.google.com/document/d/1gyjfMHy43U9OWBXxfaeG-3MjGzejW1dlpyMwEYAAWEI/view?fullscreen#
to estimate the cardinality of.
the maximum estimation error allowed.