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From jwi...@apache.org
Subject svn commit: r1545156 - in /crunch/site/trunk/content: apidocs/current intro.mdtext
Date Mon, 25 Nov 2013 05:34:29 GMT
Author: jwills
Date: Mon Nov 25 05:34:28 2013
New Revision: 1545156

URL: http://svn.apache.org/r1545156
Log:
Intro link updates

Removed:
    crunch/site/trunk/content/apidocs/current
Modified:
    crunch/site/trunk/content/intro.mdtext

Modified: crunch/site/trunk/content/intro.mdtext
URL: http://svn.apache.org/viewvc/crunch/site/trunk/content/intro.mdtext?rev=1545156&r1=1545155&r2=1545156&view=diff
==============================================================================
--- crunch/site/trunk/content/intro.mdtext (original)
+++ crunch/site/trunk/content/intro.mdtext Mon Nov 25 05:34:28 2013
@@ -173,30 +173,30 @@ applications that can modify their downs
 
 ### Data Model and Operators
 
-The Java API is centered around three interfaces that represent distributed datasets: [PCollection<T>](apidocs/current/org/apache/crunch/PCollection.html),
-[PTable<K, V>](http://crunch.apache.org/apidocs/current/org/apache/crunch/PTable.html),
and [PGroupedTable<K, V>](apidocs/current/org/apache/crunch/PGroupedTable.html).
+The Java API is centered around three interfaces that represent distributed datasets: [PCollection<T>](apidocs/0.8.0/org/apache/crunch/PCollection.html),
+[PTable<K, V>](http://crunch.apache.org/apidocs/0.8.0/org/apache/crunch/PTable.html),
and [PGroupedTable<K, V>](apidocs/0.8.0/org/apache/crunch/PGroupedTable.html).
 
 A `PCollection<T>` represents a distributed, unordered collection of elements of type
T. For example, we represent a text file as a
-`PCollection<String>` object. `PCollection<T>` provides a method, `parallelDo`,
that applies a [DoFn<T, U>](apidocs/current/org/apache/crunch/DoFn.html)
+`PCollection<String>` object. `PCollection<T>` provides a method, `parallelDo`,
that applies a [DoFn<T, U>](apidocs/0.8.0/org/apache/crunch/DoFn.html)
 to each element in the `PCollection<T>` in parallel, and returns an new `PCollection<U>`
as its result.
 
 A `PTable<K, V>` is a sub-interface of `PCollection<Pair<K, V>>` that represents
a distributed, unordered multimap of its key type K to its value type V.
 In addition to the parallelDo operation, PTable provides a `groupByKey` operation that aggregates
all of the values in the PTable that
 have the same key into a single record. It is the groupByKey operation that triggers the
sort phase of a MapReduce job. Developers can exercise
 fine-grained control over the number of reducers and the partitioning, grouping, and sorting
strategies used during the shuffle by providing an instance
-of the [GroupingOptions](apidocs/current/org/apache/crunch/GroupingOptions.html) class to
the `groupByKey` function.
+of the [GroupingOptions](apidocs/0.8.0/org/apache/crunch/GroupingOptions.html) class to the
`groupByKey` function.
 
 The result of a groupByKey operation is a `PGroupedTable<K, V>` object, which is a
distributed, sorted map of keys of type K to an Iterable<V> that may
 be iterated over exactly once. In addition to `parallelDo` processing via DoFns, PGroupedTable
provides a `combineValues` operation that allows a
-commutative and associative [Aggregator<V>](apidocs/current/org/apache/crunch/Aggregator.html)
to be applied to the values of the PGroupedTable
+commutative and associative [Aggregator<V>](apidocs/0.8.0/org/apache/crunch/Aggregator.html)
to be applied to the values of the PGroupedTable
 instance on both the map and reduce sides of the shuffle. A number of common `Aggregator<V>`
implementations are provided in the
-[Aggregators](apidocs/current/org/apache/crunch/fn/Aggregators.html) class.
+[Aggregators](apidocs/0.8.0/org/apache/crunch/fn/Aggregators.html) class.
 
 Finally, PCollection, PTable, and PGroupedTable all support a `union` operation, which takes
a series of distinct PCollections that all have
 the same data type and treats them as a single virtual PCollection.
 
 All of the other data transformation operations supported by the Crunch APIs (aggregations,
joins, sorts, secondary sorts, and cogrouping) are implemented
-in terms of these four primitives. The patterns themselves are defined in the [org.apache.crunch.lib](apidocs/current/org/apache/crunch/lib/package-summary.html)
+in terms of these four primitives. The patterns themselves are defined in the [org.apache.crunch.lib](apidocs/0.8.0/org/apache/crunch/lib/package-summary.html)
 package and its children, and a few of of the most common patterns have convenience functions
defined on the PCollection and PTable interfaces.
 
 ### Writing DoFns
@@ -246,7 +246,7 @@ framework won't kill it,
 
 Crunch provides a number of helper methods for working with [Hadoop Counters](http://codingwiththomas.blogspot.com/2011/04/controlling-hadoop-job-recursion.html),
all named `increment`. Counters are an incredibly useful way of keeping track of the state
of long running data pipelines and detecting any exceptional conditions that
 occur during processing, and they are supported in both the MapReduce-based and in-memory
Crunch pipeline contexts. You can retrive the value of the Counters
-in your client code at the end of a MapReduce pipeline by getting them from the [StageResult](apidocs/current/org/apache/crunch/PipelineResult.StageResult.html)
+in your client code at the end of a MapReduce pipeline by getting them from the [StageResult](apidocs/0.8.0/org/apache/crunch/PipelineResult.StageResult.html)
 objects returned by Crunch at the end of a run.
 
 (Note that there was a change in the Counters API from Hadoop 1.0 to Hadoop 2.0, and thus
we do not recommend that you work with the
@@ -271,18 +271,18 @@ memory setting for the DoFn's needs befo
 #### Common DoFn Patterns
 
 The Crunch APIs contain a number of useful subclasses of DoFn that handle common data processing
scenarios and are easier
-to write and test. The top-level [org.apache.crunch](apidocs/current/org/apache/crunch/package-summary.html)
package contains three
+to write and test. The top-level [org.apache.crunch](apidocs/0.8.0/org/apache/crunch/package-summary.html)
package contains three
 of the most important specializations, which we will discuss now. Each of these specialized
DoFn implementations has associated methods
 on the PCollection, PTable, and PGroupedTable interfaces to support common data processing
steps.
 
-The simplest extension is the [FilterFn<T>](apidocs/current/org/apache/crunch/FilterFn.html)
class, which defines a single abstract method, `boolean accept(T input)`.
+The simplest extension is the [FilterFn<T>](apidocs/0.8.0/org/apache/crunch/FilterFn.html)
class, which defines a single abstract method, `boolean accept(T input)`.
 The FilterFn can be applied to a `PCollection<T>` by calling the `filter(FilterFn<T>
fn)` method, and will return a new `PCollection<T>` that only contains
 the elements of the input PCollection for which the accept method returned true. Note that
the filter function does not include a PType argument in its
 signature, because there is no change in the data type of the PCollection when the FilterFn
is applied. It is possible to compose new FilterFn
 instances by combining multiple FilterFns together using the `and`, `or`, and `not` factory
methods defined in the
-[FilterFns](apidocs/current/org/apache/crunch/fn/FilterFns.html) helper class.
+[FilterFns](apidocs/0.8.0/org/apache/crunch/fn/FilterFns.html) helper class.
 
-The second extension is the [MapFn<S, T>](apidocs/current/org/apache/crunch/MapFn.html)
class, which defines a single abstract method, `T map(S input)`.
+The second extension is the [MapFn<S, T>](apidocs/0.8.0/org/apache/crunch/MapFn.html)
class, which defines a single abstract method, `T map(S input)`.
 For simple transform tasks in which every input record will have exactly one output, it's
easy to test a MapFn by verifying that a given input returns a
 every input record will have exactly one output, it's easy to test a MapFn by verifying that
a given input returns a given output.
 
@@ -293,7 +293,7 @@ the key be given and constructs a `PTabl
 has methods `PTable<K1, V> mapKeys(MapFn<K, K1> mapFn)` and `PTable<K, V2>
mapValues(MapFn<V, V2>)` that handle the common case of converting
 just one of the paired values in a PTable instance from one type to another while leaving
the other type the same.
 
-The final top-level extension to DoFn is the [CombineFn<K, V>](apidocs/current/org/apache/crunch/CombineFn.html)
class, which is used in conjunction with
+The final top-level extension to DoFn is the [CombineFn<K, V>](apidocs/0.8.0/org/apache/crunch/CombineFn.html)
class, which is used in conjunction with
 the `combineValues` method defined on the PGroupedTable interface. CombineFns are used to
represent the associative operations that can be applied using
 the MapReduce Combiner concept in order to reduce the amount data that is shipped over the
network during a shuffle.
 
@@ -301,9 +301,9 @@ The CombineFn extension is different fro
 beyond the default `process` method that any other DoFn would use; rather, extending the
CombineFn class signals to the Crunch planner that the logic
 contained in this class satisfies the conditions required for use with the MapReduce combiner.
 
-Crunch supports many types of these associative patterns, such as sums, counts, and set unions,
via the [Aggregator<V>](apidocs/current/org/apache/crunch/Aggregator.html)
+Crunch supports many types of these associative patterns, such as sums, counts, and set unions,
via the [Aggregator<V>](apidocs/0.8.0/org/apache/crunch/Aggregator.html)
 interface, which is defined right alongside the CombineFn class in the top-level `org.apache.crunch`
package. There are a number of implementations of the Aggregator
-interface defined via static factory methods in the [Aggregators](apidocs/current/org/apache/crunch/fn/Aggregators.html)
class.
+interface defined via static factory methods in the [Aggregators](apidocs/0.8.0/org/apache/crunch/fn/Aggregators.html)
class.
 
 ### Serializing Data with PTypes
 
@@ -314,7 +314,7 @@ Why PTypes Are Necessary, the two type f
 The simplest way to create a new `PType<T>` for a data object is to create a _derived_
PType from one of the built-in PTypes for the Avro
 and Writable type families. If we have a base `PType<S>`, we can create a derived `PType<T>`
by implementing an input `MapFn<S, T>` and an
 output `MapFn<T, S>` and then calling `PTypeFamily.derived(Class<T>, MapFn<S,
T> in, MapFn<T, S> out, PType<S> base)`, which will return
-a new `PType<T>`. There are examples of derived PTypes in the [PTypes](apidocs/current/org/apache/crunch/types/PTypes.html)
class, including
+a new `PType<T>`. There are examples of derived PTypes in the [PTypes](apidocs/0.8.0/org/apache/crunch/types/PTypes.html)
class, including
 serialization support for protocol buffers, Thrift records, Java Enums, BigInteger, and UUIDs.
 
 ### Reading and Writing Data: Sources, Targets, and SourceTargets
@@ -340,8 +340,8 @@ or into a DoFn implementation that can u
 processed using the DoFn's `process` method (this is how Crunch supports mapside-join operations.)
 
 Support for the most common Source, Target, and SourceTarget implementations are provided
by the factory functions declared in the
-[From](apidocs/current/org/apache/crunch/io/From.html) (Sources), [To](apidocs/current/org/apache/crunch/io/To.html)
(Targets), and
-[At](apidocs/current/org/apache/crunch/io/At.html) (SourceTargets) classes in the [org.apache.crunch.io](apidocs/current/org/apache/crunch/io/package-summary.html)
+[From](apidocs/0.8.0/org/apache/crunch/io/From.html) (Sources), [To](apidocs/0.8.0/org/apache/crunch/io/To.html)
(Targets), and
+[At](apidocs/0.8.0/org/apache/crunch/io/At.html) (SourceTargets) classes in the [org.apache.crunch.io](apidocs/0.8.0/org/apache/crunch/io/package-summary.html)
 package.
 
 ### Pipeline Building and Execution



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