org.apache.spark.sql.streaming
SchemaDStream
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package streaming
The base scope associated with the operation that created this DStream.
The base scope associated with the operation that created this DStream.
This is the medium through which we pass the DStream operation name (e.g. updatedStateByKey)
to the RDDs created by this DStream. Note that we never use this scope directly in RDDs.
Instead, we instantiate a new scope during each call to compute based on this one.
This is not defined if the DStream is created outside of one of the public DStream operations.
Persist RDDs of this SchemaDStream with the default storage level (MEMORY_ONLY_SER)
Persist RDDs of this SchemaDStream with the default storage level (MEMORY_ONLY_SER)
Enable periodic checkpointing of RDDs of this SchemaDStream
Enable periodic checkpointing of RDDs of this SchemaDStream
Time interval after which generated RDD will be checkpointed
Returns all column names as an array.
Method that generates a RDD for the given time
Method that generates a RDD for the given time
Return the StreamingContext associated with this DStream
Return the StreamingContext associated with this DStream
Return a new DStream in which each RDD has a single element generated by counting each RDD of this DStream.
Return a new DStream in which each RDD has a single element generated by counting each RDD of this DStream.
Return a new DStream in which each RDD contains the counts of each distinct value in each RDD of this DStream.
Return a new DStream in which each RDD contains the counts of each distinct value in
each RDD of this DStream. Hash partitioning is used to generate
the RDDs with numPartitions partitions (Spark's default number of partitions if
numPartitions not specified).
Return a new DStream in which each RDD contains the count of distinct elements in RDDs in a sliding window over this DStream.
Return a new DStream in which each RDD contains the count of distinct elements in
RDDs in a sliding window over this DStream. Hash partitioning is used to generate
the RDDs with numPartitions partitions (Spark's default number of partitions if
numPartitions not specified).
width of the window; must be a multiple of this DStream's batching interval
sliding interval of the window (i.e., the interval after which the new DStream will generate RDDs); must be a multiple of this DStream's batching interval
number of partitions of each RDD in the new DStream.
Return a new DStream in which each RDD has a single element generated by counting the number of elements in a sliding window over this DStream.
Return a new DStream in which each RDD has a single element generated by counting the number of elements in a sliding window over this DStream. Hash partitioning is used to generate the RDDs with Spark's default number of partitions.
width of the window; must be a multiple of this DStream's batching interval
sliding interval of the window (i.e., the interval after which the new DStream will generate RDDs); must be a multiple of this DStream's batching interval
Wrap a body of code such that the call site and operation scope information are passed to the RDDs created in this body properly.
Wrap a body of code such that the call site and operation scope information are passed to the RDDs created in this body properly.
Current batch time that should be embedded in the scope names
Whether the detailed callsites and scopes of the inner RDDs generated
by body will be displayed in the UI; only the scope and callsite
of the DStream operation that generated this will be displayed.
RDD creation code to execute with certain local properties.
List of parent DStreams on which this SchemaDStream depends on
List of parent DStreams on which this SchemaDStream depends on
Return a new SchemaDStream containing only the elements that satisfy a predicate.
Return a new SchemaDStream containing only the elements that satisfy a predicate.
Return a new DStream by applying a function to all elements of this SchemaDStream, and then flattening the results
Return a new DStream by applying a function to all elements of this SchemaDStream, and then flattening the results
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each DataFrame in this SchemaDStream.
Apply a function to each DataFrame in this SchemaDStream. This is an output operator, so 'this' SchemaDStream will be registered as an output stream and therefore materialized.
Apply a function to each RDD in this DStream.
Apply a function to each RDD in this DStream. This is an output operator, so 'this' DStream will be registered as an output stream and therefore materialized.
Apply a function to each RDD in this DStream.
Apply a function to each RDD in this DStream. This is an output operator, so 'this' DStream will be registered as an output stream and therefore materialized.
Return a new DStream in which each RDD is generated by applying glom() to each RDD of this SchemaDStream.
Return a new DStream in which each RDD is generated by applying glom() to each RDD of this SchemaDStream. Applying glom() to an RDD coalesces all elements within each partition into an array.
Return a new DStream by applying a function to all elements of this SchemaDStream.
Return a new DStream by applying a function to all elements of this SchemaDStream.
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs of this SchemaDStream.
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs of this SchemaDStream. Applying mapPartitions() to an RDD applies a function to each partition of the RDD.
Persist RDDs of this SchemaDStream with the default storage level (MEMORY_ONLY_SER)
Persist RDDs of this SchemaDStream with the default storage level (MEMORY_ONLY_SER)
Persist the RDDs of this SchemaDStream with the given storage level
Persist the RDDs of this SchemaDStream with the given storage level
Print the first num elements of each RDD generated in this DStream.
Print the first num elements of each RDD generated in this DStream. This is an output operator, so this DStream will be registered as an output stream and there materialized.
Print the first ten elements of each RDD generated in this DStream.
Print the first ten elements of each RDD generated in this DStream. This is an output operator, so this DStream will be registered as an output stream and there materialized.
Return a new DStream in which each RDD has a single element generated by reducing each RDD of this DStream.
Return a new DStream in which each RDD has a single element generated by reducing each RDD of this DStream.
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream. However, the reduction is done incrementally using the old window's reduced value :
associative and commutative reduce function
inverse reduce function; such that for all y, invertible x:
invReduceFunc(reduceFunc(x, y), x) = y
width of the window; must be a multiple of this DStream's batching interval
sliding interval of the window (i.e., the interval after which the new DStream will generate RDDs); must be a multiple of this DStream's batching interval
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
Return a new DStream in which each RDD has a single element generated by reducing all elements in a sliding window over this DStream.
associative and commutative reduce function
width of the window; must be a multiple of this DStream's batching interval
sliding interval of the window (i.e., the interval after which the new DStream will generate RDDs); must be a multiple of this DStream's batching interval
Registers this SchemaDStream as a table in the catalog.
Return a new SchemaDStream with an increased or decreased level of parallelism.
Return a new SchemaDStream with an increased or decreased level of parallelism. Each RDD in the returned SchemaDStream has exactly numPartitions partitions.
Save each RDD in this DStream as a Sequence file of serialized objects.
Save each RDD in this DStream as a Sequence file of serialized objects.
The file name at each batch interval is generated based on prefix and
suffix: "prefix-TIME_IN_MS.suffix".
Save each RDD in this DStream as at text file, using string representation of elements.
Save each RDD in this DStream as at text file, using string representation
of elements. The file name at each batch interval is generated based on
prefix and suffix: "prefix-TIME_IN_MS.suffix".
Returns the schema of this SchemaDStream (represented by a StructType).
Return all the RDDs between 'fromTime' to 'toTime' (both included)
Return all the RDDs between 'fromTime' to 'toTime' (both included)
Return all the RDDs defined by the Interval object (both end times included)
Return all the RDDs defined by the Interval object (both end times included)
Time interval after which the SchemaDStream generates a RDD
Time interval after which the SchemaDStream generates a RDD
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' SchemaDStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' SchemaDStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' SchemaDStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' SchemaDStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' DStream and 'other' DStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' SchemaDStream and 'other' SchemaDStream.
Return a new DStream in which each RDD is generated by applying a function on each RDD of 'this' SchemaDStream and 'other' SchemaDStream.
Return a new DStream by unifying data of another DStream with this DStream.
Return a new DStream by unifying data of another DStream with this DStream.
Another DStream having the same slideDuration as this DStream.
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
width of the window; must be a multiple of this DStream's batching interval
sliding interval of the window (i.e., the interval after which the new DStream will generate RDDs); must be a multiple of this DStream's batching interval
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream.
Return a new DStream in which each RDD contains all the elements in seen in a sliding window of time over this DStream. The new DStream generates RDDs with the same interval as this DStream.
width of the window; must be a multiple of this DStream's interval.
A SQL based DStream with support for schema/Product This class offers the ability to manipulate SQL query on DStreams It is similar to SchemaRDD, which offers the similar functions Internally, RDD of each batch duration is treated as a small table and CQs are evaluated on those small tables Some of the abstraction and code is borrowed from the project: https://github.com/Intel-bigdata/spark-streamingsql