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Posted to commits@storm.apache.org by ka...@apache.org on 2016/01/20 23:24:29 UTC
[14/36] storm git commit: STORM-1468: remove {master}/docs
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/assets/js/bootstrap.min.js
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diff --git a/docs/assets/js/bootstrap.min.js b/docs/assets/js/bootstrap.min.js
deleted file mode 100644
index d839865..0000000
--- a/docs/assets/js/bootstrap.min.js
+++ /dev/null
@@ -1,7 +0,0 @@
-/*!
- * Bootstrap v3.3.1 (http://getbootstrap.com)
- * Copyright 2011-2014 Twitter, Inc.
- * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
- */
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\ No newline at end of file
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/assets/js/npm.js
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diff --git a/docs/assets/js/npm.js b/docs/assets/js/npm.js
deleted file mode 100644
index bf6aa80..0000000
--- a/docs/assets/js/npm.js
+++ /dev/null
@@ -1,13 +0,0 @@
-// This file is autogenerated via the `commonjs` Grunt task. You can require() this file in a CommonJS environment.
-require('../../js/transition.js')
-require('../../js/alert.js')
-require('../../js/button.js')
-require('../../js/carousel.js')
-require('../../js/collapse.js')
-require('../../js/dropdown.js')
-require('../../js/modal.js')
-require('../../js/tooltip.js')
-require('../../js/popover.js')
-require('../../js/scrollspy.js')
-require('../../js/tab.js')
-require('../../js/affix.js')
\ No newline at end of file
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/css/main.scss
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diff --git a/docs/css/main.scss b/docs/css/main.scss
deleted file mode 100755
index 352e13a..0000000
--- a/docs/css/main.scss
+++ /dev/null
@@ -1,48 +0,0 @@
----
-# Only the main Sass file needs front matter (the dashes are enough)
----
-@charset "utf-8";
-
-
-$spacing-unit: 30px;
-
-@import
- "syntax-highlighting"
-;
-
-#sidebar {
- float: left;
- background: #F6F9FB;
- border: 1px solid #E1E1E1;
- padding: 0px 10px 10px 0px;
- margin-left: 0px;
-
-}
-
-#sidebar a.current {
- color: #E00000;
-}
-
-#sidebar ul {
- list-style: none;
- font-size: 0.83em;
- padding-left: 20px;
-}
-
-#sidebar ul li {
- margin-top: 3px;
-}
-
-
-#aboutcontent {
- width: 70%;
- margin-top:0px;
- margin-left: 220px;
-}
-
-#footer {
- //margin: 100px;
- //padding: 0;
- font-size: 0.7em;
-}
-
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/doc-index.html
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diff --git a/docs/doc-index.html b/docs/doc-index.html
deleted file mode 100644
index f9f042a..0000000
--- a/docs/doc-index.html
+++ /dev/null
@@ -1,11 +0,0 @@
----
-layout: default
----
-
-<ul>
-{% for page in site.pages %}
-{% if page.documentation == true %}
-<li><a href="{{ page.url }}">{{ page.title }}</a></li>
-{% endif %} <!-- resource-p -->
-{% endfor %} <!-- page -->
-</ul>
\ No newline at end of file
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/documentation/Acking-framework-implementation.md
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diff --git a/docs/documentation/Acking-framework-implementation.md b/docs/documentation/Acking-framework-implementation.md
deleted file mode 100644
index 4099219..0000000
--- a/docs/documentation/Acking-framework-implementation.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-title: Acking Framework Implementation
-layout: documentation
-documentation: true
----
-[Storm's acker](https://github.com/apache/storm/blob/46c3ba7/storm-core/src/clj/backtype/storm/daemon/acker.clj#L28) tracks completion of each tupletree with a checksum hash: each time a tuple is sent, its value is XORed into the checksum, and each time a tuple is acked its value is XORed in again. If all tuples have been successfully acked, the checksum will be zero (the odds that the checksum will be zero otherwise are vanishingly small).
-
-You can read a bit more about the [reliability mechanism](Guaranteeing-message-processing.html#what-is-storms-reliability-api) elsewhere on the wiki -- this explains the internal details.
-
-### acker `execute()`
-
-The acker is actually a regular bolt, with its [execute method](https://github.com/apache/storm/blob/46c3ba7/storm-core/src/clj/backtype/storm/daemon/acker.clj#L36) defined withing `mk-acker-bolt`. When a new tupletree is born, the spout sends the XORed edge-ids of each tuple recipient, which the acker records in its `pending` ledger. Every time an executor acks a tuple, the acker receives a partial checksum that is the XOR of the tuple's own edge-id (clearing it from the ledger) and the edge-id of each downstream tuple the executor emitted (thus entering them into the ledger).
-
-This is accomplished as follows.
-
-On a tick tuple, just advance pending tupletree checksums towards death and return. Otherwise, update or create the record for this tupletree:
-
-* on init: initialize with the given checksum value, and record the spout's id for later.
-* on ack: xor the partial checksum into the existing checksum value
-* on fail: just mark it as failed
-
-Next, [put the record](https://github.com/apache/storm/blob/46c3ba7/storm-core/src/clj/backtype/storm/daemon/acker.clj#L50)), into the RotatingMap (thus resetting is countdown to expiry) and take action:
-
-* if the total checksum is zero, the tupletree is complete: remove it from the pending collection and notify the spout of success
-* if the tupletree has failed, it is also complete: remove it from the pending collection and notify the spout of failure
-
-Finally, pass on an ack of our own.
-
-### Pending tuples and the `RotatingMap`
-
-The acker stores pending tuples in a [`RotatingMap`](https://github.com/apache/storm/blob/master/storm-core/src/jvm/backtype/storm/utils/RotatingMap.java#L19), a simple device used in several places within Storm to efficiently time-expire a process.
-
-The RotatingMap behaves as a HashMap, and offers the same O(1) access guarantees.
-
-Internally, it holds several HashMaps ('buckets') of its own, each holding a cohort of records that will expire at the same time. Let's call the longest-lived bucket death row, and the most recent the nursery. Whenever a value is `.put()` to the RotatingMap, it is relocated to the nursery -- and removed from any other bucket it might have been in (effectively resetting its death clock).
-
-Whenever its owner calls `.rotate()`, the RotatingMap advances each cohort one step further towards expiration. (Typically, Storm objects call rotate on every receipt of a system tick stream tuple.) If there are any key-value pairs in the former death row bucket, the RotatingMap invokes a callback (given in the constructor) for each key-value pair, letting its owner take appropriate action (eg, failing a tuple.
-
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/documentation/BYLAWS.md
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----
-title: Apache Storm Project Bylaws
-layout: documentation
-documentation: true
----
-
-## Roles and Responsibilities
-
-Apache projects define a set of roles with associated rights and responsibilities. These roles govern what tasks an individual may perform within the project. The roles are defined in the following sections:
-
-### Users:
-
-The most important participants in the project are people who use our software. The majority of our developers start out as users and guide their development efforts from the user's perspective.
-
-Users contribute to the Apache projects by providing feedback to developers in the form of bug reports and feature suggestions. As well, users participate in the Apache community by helping other users on mailing lists and user support forums.
-
-### Contributors:
-
-Contributors are all of the volunteers who are contributing time, code, documentation, or resources to the Storm Project. A contributor that makes sustained, welcome contributions to the project may be invited to become a Committer, though the exact timing of such invitations depends on many factors.
-
-### Committers:
-
-The project's Committers are responsible for the project's technical management. Committers have access to all project source repositories. Committers may cast binding votes on any technical discussion regarding storm.
-
-Committer access is by invitation only and must be approved by lazy consensus of the active PMC members. A Committer is considered emeritus by their own declaration or by not contributing in any form to the project for over six months. An emeritus Committer may request reinstatement of commit access from the PMC. Such reinstatement is subject to lazy consensus approval of active PMC members.
-
-All Apache Committers are required to have a signed Contributor License Agreement (CLA) on file with the Apache Software Foundation. There is a [Committers' FAQ](https://www.apache.org/dev/committers.html) which provides more details on the requirements for Committers.
-
-A Committer who makes a sustained contribution to the project may be invited to become a member of the PMC. The form of contribution is not limited to code. It can also include code review, helping out users on the mailing lists, documentation, testing, etc.
-
-### Project Management Committee(PMC):
-
-The PMC is responsible to the board and the ASF for the management and oversight of the Apache Storm codebase. The responsibilities of the PMC include:
-
- * Deciding what is distributed as products of the Apache Storm project. In particular all releases must be approved by the PMC.
- * Maintaining the project's shared resources, including the codebase repository, mailing lists, websites.
- * Speaking on behalf of the project.
- * Resolving license disputes regarding products of the project.
- * Nominating new PMC members and Committers.
- * Maintaining these bylaws and other guidelines of the project.
-
-Membership of the PMC is by invitation only and must be approved by a consensus approval of active PMC members. A PMC member is considered "emeritus" by their own declaration or by not contributing in any form to the project for over six months. An emeritus member may request reinstatement to the PMC. Such reinstatement is subject to consensus approval of the active PMC members.
-
-The chair of the PMC is appointed by the ASF board. The chair is an office holder of the Apache Software Foundation (Vice President, Apache Storm) and has primary responsibility to the board for the management of the projects within the scope of the Storm PMC. The chair reports to the board quarterly on developments within the Storm project.
-
-The chair of the PMC is rotated annually. When the chair is rotated or if the current chair of the PMC resigns, the PMC votes to recommend a new chair using Single Transferable Vote (STV) voting. See http://wiki.apache.org/general/BoardVoting for specifics. The decision must be ratified by the Apache board.
-
-## Voting
-
-Decisions regarding the project are made by votes on the primary project development mailing list (dev@storm.apache.org). Where necessary, PMC voting may take place on the private Storm PMC mailing list. Votes are clearly indicated by subject line starting with [VOTE]. Votes may contain multiple items for approval and these should be clearly separated. Voting is carried out by replying to the vote mail. Voting may take four flavors:
-
-| Vote | Meaning |
-|------|---------|
-| +1 | 'Yes,' 'Agree,' or 'the action should be performed.' |
-| +0 | Neutral about the proposed action. |
-| -0 | Mildly negative, but not enough so to want to block it. |
-| -1 |This is a negative vote. On issues where consensus is required, this vote counts as a veto. All vetoes must contain an explanation of why the veto is appropriate. Vetoes with no explanation are void. It may also be appropriate for a -1 vote to include an alternative course of action. |
-
-All participants in the Storm project are encouraged to show their agreement with or against a particular action by voting. For technical decisions, only the votes of active Committers are binding. Non-binding votes are still useful for those with binding votes to understand the perception of an action in the wider Storm community. For PMC decisions, only the votes of active PMC members are binding.
-
-Voting can also be applied to changes already made to the Storm codebase. These typically take the form of a veto (-1) in reply to the commit message sent when the commit is made. Note that this should be a rare occurrence. All efforts should be made to discuss issues when they are still patches before the code is committed.
-
-Only active (i.e. non-emeritus) Committers and PMC members have binding votes.
-
-## Approvals
-
-These are the types of approvals that can be sought. Different actions require different types of approvals
-
-| Approval Type | Criteria |
-|---------------|----------|
-| Consensus Approval | Consensus approval requires 3 binding +1 votes and no binding vetoes. |
-| Majority Approval | Majority approval requires at least 3 binding +1 votes and more +1 votes than -1 votes. |
-| Lazy Consensus | Lazy consensus requires no -1 votes ('silence gives assent'). |
-| 2/3 Majority | 2/3 majority votes requires at least 3 votes and twice as many +1 votes as -1 votes. |
-
-### Vetoes
-
-A valid, binding veto cannot be overruled. If a veto is cast, it must be accompanied by a valid reason explaining the reasons for the veto. The validity of a veto, if challenged, can be confirmed by anyone who has a binding vote. This does not necessarily signify agreement with the veto - merely that the veto is valid.
-
-If you disagree with a valid veto, you must lobby the person casting the veto to withdraw their veto. If a veto is not withdrawn, any action that has been vetoed must be reversed in a timely manner.
-
-## Actions
-
-This section describes the various actions which are undertaken within the project, the corresponding approval required for that action and those who have binding votes over the action.
-
-| Actions | Description | Approval | Binding Votes | Minimum Length | Mailing List |
-|---------|-------------|----------|---------------|----------------|--------------|
-| Code Change | A change made to a source code of the project and committed by a Committer. | A minimum of one +1 from a Committer other than the one who authored the patch, and no -1s. The code can be committed after the first +1. If a -1 is received to the patch within 7 days after the patch was posted, it may be reverted immediately if it was already merged. | Active Committers | 1 day from initial patch (**Note:** Committers should consider allowing more time for review based on the complexity and/or impact of the patch in question.)|JIRA or Github pull ( with notification sent to dev@storm.apache.org) |
-| Non-Code Change | A change made to a repository of the project and committed by a Committer. This includes documentation, website content, etc., but not source code, unless only comments are being modified. | Lazy Consensus | Active Committers | At the discression of the Committer |JIRA or Github pull (with notification sent to dev@storm.apache.org) |
-| Product Release | A vote is required to accept a proposed release as an official release of the project. Any Committer may call for a release vote at any point in time. | Majority Approval | Active PMC members | 3 days | dev@storm.apache.org |
-| Adoption of New Codebase | When the codebase for an existing, released product is to be replaced with an alternative codebase. If such a vote fails to gain approval, the existing code base will continue. This also covers the creation of new sub-projects and submodules within the project as well as merging of feature branches. | 2/3 Majority | Active PMC members | 6 days | dev@storm.apache.org |
-| New Committer | When a new Committer is proposed for the project. | Consensus Approval | Active PMC members | 3 days | private@storm.apache.org |
-| New PMC Member | When a member is proposed for the PMC. | Consensus Approval | Active PMC members | 3 days | private@storm.apache.org |
-| Emeritus PMC Member re-instatement | When an emeritus PMC member requests to be re-instated as an active PMC member. | Consensus Approval | Active PMC members | 6 days | private@storm.apache.org |
-| Emeritus Committer re-instatement | When an emeritus Committer requests to be re-instated as an active Committer. | Consensus Approval | Active PMC members | 6 days | private@storm.apache.org |
-| Committer Removal | When removal of commit privileges is sought. Note: Such actions will also be referred to the ASF board by the PMC chair. | 2/3 Majority | Active PMC members (excluding the Committer in question if a member of the PMC). | 6 Days | private@storm.apache.org |
-| PMC Member Removal | When removal of a PMC member is sought. Note: Such actions will also be referred to the ASF board by the PMC chair. | 2/3 Majority | Active PMC members (excluding the member in question). | 6 Days | private@storm.apache.org |
-| Modifying Bylaws | Modifying this document. | 2/3 Majority | Active PMC members | 6 Days | dev@storm.apache.org |
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/documentation/Clojure-DSL.md
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----
-title: Clojure DSL
-layout: documentation
-documentation: true
----
-Storm comes with a Clojure DSL for defining spouts, bolts, and topologies. The Clojure DSL has access to everything the Java API exposes, so if you're a Clojure user you can code Storm topologies without touching Java at all. The Clojure DSL is defined in the source in the [backtype.storm.clojure](https://github.com/apache/storm/blob/0.5.3/src/clj/backtype/storm/clojure.clj) namespace.
-
-This page outlines all the pieces of the Clojure DSL, including:
-
-1. Defining topologies
-2. `defbolt`
-3. `defspout`
-4. Running topologies in local mode or on a cluster
-5. Testing topologies
-
-### Defining topologies
-
-To define a topology, use the `topology` function. `topology` takes in two arguments: a map of "spout specs" and a map of "bolt specs". Each spout and bolt spec wires the code for the component into the topology by specifying things like inputs and parallelism.
-
-Let's take a look at an example topology definition [from the storm-starter project](https://github.com/apache/storm/blob/master/examples/storm-starter/src/clj/storm/starter/clj/word_count.clj):
-
-```clojure
-(topology
- {"1" (spout-spec sentence-spout)
- "2" (spout-spec (sentence-spout-parameterized
- ["the cat jumped over the door"
- "greetings from a faraway land"])
- :p 2)}
- {"3" (bolt-spec {"1" :shuffle "2" :shuffle}
- split-sentence
- :p 5)
- "4" (bolt-spec {"3" ["word"]}
- word-count
- :p 6)})
-```
-
-The maps of spout and bolt specs are maps from the component id to the corresponding spec. The component ids must be unique across the maps. Just like defining topologies in Java, component ids are used when declaring inputs for bolts in the topology.
-
-#### spout-spec
-
-`spout-spec` takes as arguments the spout implementation (an object that implements [IRichSpout](/javadoc/apidocs/backtype/storm/topology/IRichSpout.html)) and optional keyword arguments. The only option that exists currently is the `:p` option, which specifies the parallelism for the spout. If you omit `:p`, the spout will execute as a single task.
-
-#### bolt-spec
-
-`bolt-spec` takes as arguments the input declaration for the bolt, the bolt implementation (an object that implements [IRichBolt](/javadoc/apidocs/backtype/storm/topology/IRichBolt.html)), and optional keyword arguments.
-
-The input declaration is a map from stream ids to stream groupings. A stream id can have one of two forms:
-
-1. `[==component id== ==stream id==]`: Subscribes to a specific stream on a component
-2. `==component id==`: Subscribes to the default stream on a component
-
-A stream grouping can be one of the following:
-
-1. `:shuffle`: subscribes with a shuffle grouping
-2. Vector of field names, like `["id" "name"]`: subscribes with a fields grouping on the specified fields
-3. `:global`: subscribes with a global grouping
-4. `:all`: subscribes with an all grouping
-5. `:direct`: subscribes with a direct grouping
-
-See [Concepts](Concepts.html) for more info on stream groupings. Here's an example input declaration showcasing the various ways to declare inputs:
-
-```clojure
-{["2" "1"] :shuffle
- "3" ["field1" "field2"]
- ["4" "2"] :global}
-```
-
-This input declaration subscribes to three streams total. It subscribes to stream "1" on component "2" with a shuffle grouping, subscribes to the default stream on component "3" with a fields grouping on the fields "field1" and "field2", and subscribes to stream "2" on component "4" with a global grouping.
-
-Like `spout-spec`, the only current supported keyword argument for `bolt-spec` is `:p` which specifies the parallelism for the bolt.
-
-#### shell-bolt-spec
-
-`shell-bolt-spec` is used for defining bolts that are implemented in a non-JVM language. It takes as arguments the input declaration, the command line program to run, the name of the file implementing the bolt, an output specification, and then the same keyword arguments that `bolt-spec` accepts.
-
-Here's an example `shell-bolt-spec`:
-
-```clojure
-(shell-bolt-spec {"1" :shuffle "2" ["id"]}
- "python"
- "mybolt.py"
- ["outfield1" "outfield2"]
- :p 25)
-```
-
-The syntax of output declarations is described in more detail in the `defbolt` section below. See [Using non JVM languages with Storm](Using-non-JVM-languages-with-Storm.html) for more details on how multilang works within Storm.
-
-### defbolt
-
-`defbolt` is used for defining bolts in Clojure. Bolts have the constraint that they must be serializable, and this is why you can't just reify `IRichBolt` to implement a bolt (closures aren't serializable). `defbolt` works around this restriction and provides a nicer syntax for defining bolts than just implementing a Java interface.
-
-At its fullest expressiveness, `defbolt` supports parameterized bolts and maintaining state in a closure around the bolt implementation. It also provides shortcuts for defining bolts that don't need this extra functionality. The signature for `defbolt` looks like the following:
-
-(defbolt _name_ _output-declaration_ *_option-map_ & _impl_)
-
-Omitting the option map is equivalent to having an option map of `{:prepare false}`.
-
-#### Simple bolts
-
-Let's start with the simplest form of `defbolt`. Here's an example bolt that splits a tuple containing a sentence into a tuple for each word:
-
-```clojure
-(defbolt split-sentence ["word"] [tuple collector]
- (let [words (.split (.getString tuple 0) " ")]
- (doseq [w words]
- (emit-bolt! collector [w] :anchor tuple))
- (ack! collector tuple)
- ))
-```
-
-Since the option map is omitted, this is a non-prepared bolt. The DSL simply expects an implementation for the `execute` method of `IRichBolt`. The implementation takes two parameters, the tuple and the `OutputCollector`, and is followed by the body of the `execute` function. The DSL automatically type-hints the parameters for you so you don't need to worry about reflection if you use Java interop.
-
-This implementation binds `split-sentence` to an actual `IRichBolt` object that you can use in topologies, like so:
-
-```clojure
-(bolt-spec {"1" :shuffle}
- split-sentence
- :p 5)
-```
-
-
-#### Parameterized bolts
-
-Many times you want to parameterize your bolts with other arguments. For example, let's say you wanted to have a bolt that appends a suffix to every input string it receives, and you want that suffix to be set at runtime. You do this with `defbolt` by including a `:params` option in the option map, like so:
-
-```clojure
-(defbolt suffix-appender ["word"] {:params [suffix]}
- [tuple collector]
- (emit-bolt! collector [(str (.getString tuple 0) suffix)] :anchor tuple)
- )
-```
-
-Unlike the previous example, `suffix-appender` will be bound to a function that returns an `IRichBolt` rather than be an `IRichBolt` object directly. This is caused by specifying `:params` in its option map. So to use `suffix-appender` in a topology, you would do something like:
-
-```clojure
-(bolt-spec {"1" :shuffle}
- (suffix-appender "-suffix")
- :p 10)
-```
-
-#### Prepared bolts
-
-To do more complex bolts, such as ones that do joins and streaming aggregations, the bolt needs to store state. You can do this by creating a prepared bolt which is specified by including `{:prepare true}` in the option map. Consider, for example, this bolt that implements word counting:
-
-```clojure
-(defbolt word-count ["word" "count"] {:prepare true}
- [conf context collector]
- (let [counts (atom {})]
- (bolt
- (execute [tuple]
- (let [word (.getString tuple 0)]
- (swap! counts (partial merge-with +) {word 1})
- (emit-bolt! collector [word (@counts word)] :anchor tuple)
- (ack! collector tuple)
- )))))
-```
-
-The implementation for a prepared bolt is a function that takes as input the topology config, `TopologyContext`, and `OutputCollector`, and returns an implementation of the `IBolt` interface. This design allows you to have a closure around the implementation of `execute` and `cleanup`.
-
-In this example, the word counts are stored in the closure in a map called `counts`. The `bolt` macro is used to create the `IBolt` implementation. The `bolt` macro is a more concise way to implement the interface than reifying, and it automatically type-hints all of the method parameters. This bolt implements the execute method which updates the count in the map and emits the new word count.
-
-Note that the `execute` method in prepared bolts only takes as input the tuple since the `OutputCollector` is already in the closure of the function (for simple bolts the collector is a second parameter to the `execute` function).
-
-Prepared bolts can be parameterized just like simple bolts.
-
-#### Output declarations
-
-The Clojure DSL has a concise syntax for declaring the outputs of a bolt. The most general way to declare the outputs is as a map from stream id a stream spec. For example:
-
-```clojure
-{"1" ["field1" "field2"]
- "2" (direct-stream ["f1" "f2" "f3"])
- "3" ["f1"]}
-```
-
-The stream id is a string, while the stream spec is either a vector of fields or a vector of fields wrapped by `direct-stream`. `direct stream` marks the stream as a direct stream (See [Concepts](Concepts.html) and [Direct groupings]() for more details on direct streams).
-
-If the bolt only has one output stream, you can define the default stream of the bolt by using a vector instead of a map for the output declaration. For example:
-
-```clojure
-["word" "count"]
-```
-This declares the output of the bolt as the fields ["word" "count"] on the default stream id.
-
-#### Emitting, acking, and failing
-
-Rather than use the Java methods on `OutputCollector` directly, the DSL provides a nicer set of functions for using `OutputCollector`: `emit-bolt!`, `emit-direct-bolt!`, `ack!`, and `fail!`.
-
-1. `emit-bolt!`: takes as parameters the `OutputCollector`, the values to emit (a Clojure sequence), and keyword arguments for `:anchor` and `:stream`. `:anchor` can be a single tuple or a list of tuples, and `:stream` is the id of the stream to emit to. Omitting the keyword arguments emits an unanchored tuple to the default stream.
-2. `emit-direct-bolt!`: takes as parameters the `OutputCollector`, the task id to send the tuple to, the values to emit, and keyword arguments for `:anchor` and `:stream`. This function can only emit to streams declared as direct streams.
-2. `ack!`: takes as parameters the `OutputCollector` and the tuple to ack.
-3. `fail!`: takes as parameters the `OutputCollector` and the tuple to fail.
-
-See [Guaranteeing message processing](Guaranteeing-message-processing.html) for more info on acking and anchoring.
-
-### defspout
-
-`defspout` is used for defining spouts in Clojure. Like bolts, spouts must be serializable so you can't just reify `IRichSpout` to do spout implementations in Clojure. `defspout` works around this restriction and provides a nicer syntax for defining spouts than just implementing a Java interface.
-
-The signature for `defspout` looks like the following:
-
-(defspout _name_ _output-declaration_ *_option-map_ & _impl_)
-
-If you leave out the option map, it defaults to {:prepare true}. The output declaration for `defspout` has the same syntax as `defbolt`.
-
-Here's an example `defspout` implementation from [storm-starter](https://github.com/apache/storm/blob/master/examples/storm-starter/src/clj/storm/starter/clj/word_count.clj):
-
-```clojure
-(defspout sentence-spout ["sentence"]
- [conf context collector]
- (let [sentences ["a little brown dog"
- "the man petted the dog"
- "four score and seven years ago"
- "an apple a day keeps the doctor away"]]
- (spout
- (nextTuple []
- (Thread/sleep 100)
- (emit-spout! collector [(rand-nth sentences)])
- )
- (ack [id]
- ;; You only need to define this method for reliable spouts
- ;; (such as one that reads off of a queue like Kestrel)
- ;; This is an unreliable spout, so it does nothing here
- ))))
-```
-
-The implementation takes in as input the topology config, `TopologyContext`, and `SpoutOutputCollector`. The implementation returns an `ISpout` object. Here, the `nextTuple` function emits a random sentence from `sentences`.
-
-This spout isn't reliable, so the `ack` and `fail` methods will never be called. A reliable spout will add a message id when emitting tuples, and then `ack` or `fail` will be called when the tuple is completed or failed respectively. See [Guaranteeing message processing](Guaranteeing-message-processing.html) for more info on how reliability works within Storm.
-
-`emit-spout!` takes in as parameters the `SpoutOutputCollector` and the new tuple to be emitted, and accepts as keyword arguments `:stream` and `:id`. `:stream` specifies the stream to emit to, and `:id` specifies a message id for the tuple (used in the `ack` and `fail` callbacks). Omitting these arguments emits an unanchored tuple to the default output stream.
-
-There is also a `emit-direct-spout!` function that emits a tuple to a direct stream and takes an additional argument as the second parameter of the task id to send the tuple to.
-
-Spouts can be parameterized just like bolts, in which case the symbol is bound to a function returning `IRichSpout` instead of the `IRichSpout` itself. You can also declare an unprepared spout which only defines the `nextTuple` method. Here is an example of an unprepared spout that emits random sentences parameterized at runtime:
-
-```clojure
-(defspout sentence-spout-parameterized ["word"] {:params [sentences] :prepare false}
- [collector]
- (Thread/sleep 500)
- (emit-spout! collector [(rand-nth sentences)]))
-```
-
-The following example illustrates how to use this spout in a `spout-spec`:
-
-```clojure
-(spout-spec (sentence-spout-parameterized
- ["the cat jumped over the door"
- "greetings from a faraway land"])
- :p 2)
-```
-
-### Running topologies in local mode or on a cluster
-
-That's all there is to the Clojure DSL. To submit topologies in remote mode or local mode, just use the `StormSubmitter` or `LocalCluster` classes just like you would from Java.
-
-To create topology configs, it's easiest to use the `backtype.storm.config` namespace which defines constants for all of the possible configs. The constants are the same as the static constants in the `Config` class, except with dashes instead of underscores. For example, here's a topology config that sets the number of workers to 15 and configures the topology in debug mode:
-
-```clojure
-{TOPOLOGY-DEBUG true
- TOPOLOGY-WORKERS 15}
-```
-
-### Testing topologies
-
-[This blog post](http://www.pixelmachine.org/2011/12/17/Testing-Storm-Topologies.html) and its [follow-up](http://www.pixelmachine.org/2011/12/21/Testing-Storm-Topologies-Part-2.html) give a good overview of Storm's powerful built-in facilities for testing topologies in Clojure.
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/documentation/Command-line-client.md
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----
-title: Command Line Client
-layout: documentation
-documentation: true
----
-This page describes all the commands that are possible with the "storm" command line client. To learn how to set up your "storm" client to talk to a remote cluster, follow the instructions in [Setting up development environment](Setting-up-a-development-environment.html).
-
-These commands are:
-
-1. jar
-1. kill
-1. activate
-1. deactivate
-1. rebalance
-1. repl
-1. classpath
-1. localconfvalue
-1. remoteconfvalue
-1. nimbus
-1. supervisor
-1. ui
-1. drpc
-
-### jar
-
-Syntax: `storm jar topology-jar-path class ...`
-
-Runs the main method of `class` with the specified arguments. The storm jars and configs in `~/.storm` are put on the classpath. The process is configured so that [StormSubmitter](/javadoc/apidocs/backtype/storm/StormSubmitter.html) will upload the jar at `topology-jar-path` when the topology is submitted.
-
-### kill
-
-Syntax: `storm kill topology-name [-w wait-time-secs]`
-
-Kills the topology with the name `topology-name`. Storm will first deactivate the topology's spouts for the duration of the topology's message timeout to allow all messages currently being processed to finish processing. Storm will then shutdown the workers and clean up their state. You can override the length of time Storm waits between deactivation and shutdown with the -w flag.
-
-### activate
-
-Syntax: `storm activate topology-name`
-
-Activates the specified topology's spouts.
-
-### deactivate
-
-Syntax: `storm deactivate topology-name`
-
-Deactivates the specified topology's spouts.
-
-### rebalance
-
-Syntax: `storm rebalance topology-name [-w wait-time-secs]`
-
-Sometimes you may wish to spread out where the workers for a topology are running. For example, let's say you have a 10 node cluster running 4 workers per node, and then let's say you add another 10 nodes to the cluster. You may wish to have Storm spread out the workers for the running topology so that each node runs 2 workers. One way to do this is to kill the topology and resubmit it, but Storm provides a "rebalance" command that provides an easier way to do this.
-
-Rebalance will first deactivate the topology for the duration of the message timeout (overridable with the -w flag) and then redistribute the workers evenly around the cluster. The topology will then return to its previous state of activation (so a deactivated topology will still be deactivated and an activated topology will go back to being activated).
-
-### repl
-
-Syntax: `storm repl`
-
-Opens up a Clojure REPL with the storm jars and configuration on the classpath. Useful for debugging.
-
-### classpath
-
-Syntax: `storm classpath`
-
-Prints the classpath used by the storm client when running commands.
-
-### localconfvalue
-
-Syntax: `storm localconfvalue conf-name`
-
-Prints out the value for `conf-name` in the local Storm configs. The local Storm configs are the ones in `~/.storm/storm.yaml` merged in with the configs in `defaults.yaml`.
-
-### remoteconfvalue
-
-Syntax: `storm remoteconfvalue conf-name`
-
-Prints out the value for `conf-name` in the cluster's Storm configs. The cluster's Storm configs are the ones in `$STORM-PATH/conf/storm.yaml` merged in with the configs in `defaults.yaml`. This command must be run on a cluster machine.
-
-### nimbus
-
-Syntax: `storm nimbus`
-
-Launches the nimbus daemon. This command should be run under supervision with a tool like [daemontools](http://cr.yp.to/daemontools.html) or [monit](http://mmonit.com/monit/). See [Setting up a Storm cluster](Setting-up-a-Storm-cluster.html) for more information.
-
-### supervisor
-
-Syntax: `storm supervisor`
-
-Launches the supervisor daemon. This command should be run under supervision with a tool like [daemontools](http://cr.yp.to/daemontools.html) or [monit](http://mmonit.com/monit/). See [Setting up a Storm cluster](Setting-up-a-Storm-cluster.html) for more information.
-
-### ui
-
-Syntax: `storm ui`
-
-Launches the UI daemon. The UI provides a web interface for a Storm cluster and shows detailed stats about running topologies. This command should be run under supervision with a tool like [daemontools](http://cr.yp.to/daemontools.html) or [monit](http://mmonit.com/monit/). See [Setting up a Storm cluster](Setting-up-a-Storm-cluster.html) for more information.
-
-### drpc
-
-Syntax: `storm drpc`
-
-Launches a DRPC daemon. This command should be run under supervision with a tool like [daemontools](http://cr.yp.to/daemontools.html) or [monit](http://mmonit.com/monit/). See [Distributed RPC](Distributed-RPC.html) for more information.
http://git-wip-us.apache.org/repos/asf/storm/blob/2f5c31d2/docs/documentation/Common-patterns.md
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diff --git a/docs/documentation/Common-patterns.md b/docs/documentation/Common-patterns.md
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--- a/docs/documentation/Common-patterns.md
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----
-title: Common Topology Patterns
-layout: documentation
-documentation: true
----
-
-This page lists a variety of common patterns in Storm topologies.
-
-1. Streaming joins
-2. Batching
-3. BasicBolt
-4. In-memory caching + fields grouping combo
-5. Streaming top N
-6. TimeCacheMap for efficiently keeping a cache of things that have been recently updated
-7. CoordinatedBolt and KeyedFairBolt for Distributed RPC
-
-### Joins
-
-A streaming join combines two or more data streams together based on some common field. Whereas a normal database join has finite input and clear semantics for a join, a streaming join has infinite input and unclear semantics for what a join should be.
-
-The join type you need will vary per application. Some applications join all tuples for two streams over a finite window of time, whereas other applications expect exactly one tuple for each side of the join for each join field. Other applications may do the join completely differently. The common pattern among all these join types is partitioning multiple input streams in the same way. This is easily accomplished in Storm by using a fields grouping on the same fields for many input streams to the joiner bolt. For example:
-
-```java
-builder.setBolt("join", new MyJoiner(), parallelism)
- .fieldsGrouping("1", new Fields("joinfield1", "joinfield2"))
- .fieldsGrouping("2", new Fields("joinfield1", "joinfield2"))
- .fieldsGrouping("3", new Fields("joinfield1", "joinfield2"));
-```
-
-The different streams don't have to have the same field names, of course.
-
-
-### Batching
-
-Oftentimes for efficiency reasons or otherwise, you want to process a group of tuples in batch rather than individually. For example, you may want to batch updates to a database or do a streaming aggregation of some sort.
-
-If you want reliability in your data processing, the right way to do this is to hold on to tuples in an instance variable while the bolt waits to do the batching. Once you do the batch operation, you then ack all the tuples you were holding onto.
-
-If the bolt emits tuples, then you may want to use multi-anchoring to ensure reliability. It all depends on the specific application. See [Guaranteeing message processing](Guaranteeing-message-processing.html) for more details on how reliability works.
-
-### BasicBolt
-Many bolts follow a similar pattern of reading an input tuple, emitting zero or more tuples based on that input tuple, and then acking that input tuple immediately at the end of the execute method. Bolts that match this pattern are things like functions and filters. This is such a common pattern that Storm exposes an interface called [IBasicBolt](/javadoc/apidocs/backtype/storm/topology/IBasicBolt.html) that automates this pattern for you. See [Guaranteeing message processing](Guaranteeing-message-processing.html) for more information.
-
-### In-memory caching + fields grouping combo
-
-It's common to keep caches in-memory in Storm bolts. Caching becomes particularly powerful when you combine it with a fields grouping. For example, suppose you have a bolt that expands short URLs (like bit.ly, t.co, etc.) into long URLs. You can increase performance by keeping an LRU cache of short URL to long URL expansions to avoid doing the same HTTP requests over and over. Suppose component "urls" emits short URLS, and component "expand" expands short URLs into long URLs and keeps a cache internally. Consider the difference between the two following snippets of code:
-
-```java
-builder.setBolt("expand", new ExpandUrl(), parallelism)
- .shuffleGrouping(1);
-```
-
-```java
-builder.setBolt("expand", new ExpandUrl(), parallelism)
- .fieldsGrouping("urls", new Fields("url"));
-```
-
-The second approach will have vastly more effective caches, since the same URL will always go to the same task. This avoids having duplication across any of the caches in the tasks and makes it much more likely that a short URL will hit the cache.
-
-### Streaming top N
-
-A common continuous computation done on Storm is a "streaming top N" of some sort. Suppose you have a bolt that emits tuples of the form ["value", "count"] and you want a bolt that emits the top N tuples based on count. The simplest way to do this is to have a bolt that does a global grouping on the stream and maintains a list in memory of the top N items.
-
-This approach obviously doesn't scale to large streams since the entire stream has to go through one task. A better way to do the computation is to do many top N's in parallel across partitions of the stream, and then merge those top N's together to get the global top N. The pattern looks like this:
-
-```java
-builder.setBolt("rank", new RankObjects(), parallelism)
- .fieldsGrouping("objects", new Fields("value"));
-builder.setBolt("merge", new MergeObjects())
- .globalGrouping("rank");
-```
-
-This pattern works because of the fields grouping done by the first bolt which gives the partitioning you need for this to be semantically correct. You can see an example of this pattern in storm-starter [here](https://github.com/apache/storm/blob/master/examples/storm-starter/src/jvm/storm/starter/RollingTopWords.java).
-
-If however you have a known skew in the data being processed it can be advantageous to use partialKeyGrouping instead of fieldsGrouping. This will distribute the load for each key between two downstream bolts instead of a single one.
-
-```java
-builder.setBolt("count", new CountObjects(), parallelism)
- .partialKeyGrouping("objects", new Fields("value"));
-builder.setBolt("rank" new AggregateCountsAndRank(), parallelism)
- .fieldsGrouping("count", new Fields("key"))
-builder.setBolt("merge", new MergeRanksObjects())
- .globalGrouping("rank");
-```
-
-The topology needs an extra layer of processing to aggregate the partial counts from the upstream bolts but this only processes aggregated values now so the bolt it is not subject to the load caused by the skewed data. You can see an example of this pattern in storm-starter [here](https://github.com/apache/storm/blob/master/examples/storm-starter/src/jvm/storm/starter/SkewedRollingTopWords.java).
-
-### TimeCacheMap for efficiently keeping a cache of things that have been recently updated
-
-You sometimes want to keep a cache in memory of items that have been recently "active" and have items that have been inactive for some time be automatically expires. [TimeCacheMap](/javadoc/apidocs/backtype/storm/utils/TimeCacheMap.html) is an efficient data structure for doing this and provides hooks so you can insert callbacks whenever an item is expired.
-
-### CoordinatedBolt and KeyedFairBolt for Distributed RPC
-
-When building distributed RPC applications on top of Storm, there are two common patterns that are usually needed. These are encapsulated by [CoordinatedBolt](/javadoc/apidocs/backtype/storm/task/CoordinatedBolt.html) and [KeyedFairBolt](/javadoc/apidocs/backtype/storm/task/KeyedFairBolt.html) which are part of the "standard library" that ships with the Storm codebase.
-
-`CoordinatedBolt` wraps the bolt containing your logic and figures out when your bolt has received all the tuples for any given request. It makes heavy use of direct streams to do this.
-
-`KeyedFairBolt` also wraps the bolt containing your logic and makes sure your topology processes multiple DRPC invocations at the same time, instead of doing them serially one at a time.
-
-See [Distributed RPC](Distributed-RPC.html) for more details.