{"action":"created","comment":{"url":"https://api.github.com/repos/pravega/pravega/pulls/comments/228426873","pull_request_review_id":168697141,"id":228426873,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIyODQyNjg3Mw==","diff_hunk":"@@ -11,362 +11,266 @@ You may obtain a copy of the License at\n \n Pravega is an open source storage primitive implementing **Streams** for continuous and unbounded data.\n \n-This page is an overview of the key concepts in Pravega.\n- See [Terminology](terminology.md) for a concise definition for many\n-Pravega concepts.\n+An overview of the key concepts of Pravega is discussed. Please, see [Terminology](terminology.md) for a concise definition of key terms of Pravega concepts.\n \n ## Streams\n \n-Pravega organizes data into Streams.  A Stream is a durable, elastic, append-only, unbounded sequence of bytes that has good performance and strong consistency.  A Pravega Stream is\n-similar to but more flexible than a \"topic\" in popular message-oriented middleware such as [RabbitMQ](https://www.rabbitmq.com/) or [Apache Kafka](https://kafka.apache.org/). \n-\n-Pravega Streams are based on an append-only log data structure. By using\n-append-only logs, Pravega can rapidly ingest data into durable storage,\n-and support a large variety of application use cases such as stream processing using frameworks like [Flink](https://flink.apache.org), publish/subscribe\n-messaging, NoSQL databases such as a Time Series\n-Database (TSDB), workflow engines, event-oriented applications and many other\n-kinds of applications. \n-\n-When a developer creates a Stream in Pravega, s/he gives the Stream a meaningful\n-name such as \"IoTSensorData\" or \"WebApplicationLog20170330\".  The\n-Stream's name helps other developers understand the kind of data that is stored\n-in the Stream.  It is also worth noting that Pravega Stream names are organized\n-within a Scope.  A Scope is a string and should convey some sort of meaning to\n-developers such as \"FactoryMachines\" or \"HRWebsitelogs\".  A Scope acts as a\n-namespace for Stream names – all Stream names are unique within a Scope.\n- Therefore a Stream is uniquely identified by the combination of its Stream name\n-and Scope.  Scope can be used to segregate names by tenant (in a multi tenant\n-environment), by department in an organization, by geographic location or any\n-other categorization the developer chooses.\n-\n-A Stream is unbounded in size – Pravega itself does not impose any limits on how\n-many Events can be in a Stream or how many total bytes are stored in a Stream.\n-Pravega’s design horizontally scales from few machines to a whole datacenter’s capacity.\n-\n-To deal with a potentially large amount of data within a Stream, Pravega Streams\n-are divided into Stream Segments.  A Stream Segment is a shard, or partition of\n-the data within a Stream.  We go into a lot more detail on Stream Segments a bit\n-later in this document.  Stream Segments are an important concept, but we need\n-to introduce a few more things before we can dive into Stream Segments.\n-\n-Applications, such as a Java program reading from an IoT sensor, write data to\n-the tail (front) of the Stream.  Applications, such as a [Flink](https://flink.apache.org) analytics job,\n-can read from any point in the Stream. Lots of applications can read and write\n-the same Stream in parallel.  Elastic, scalable support for a large volume of\n-Streams, data and applications is at the heart of Pravega's design.  We will\n-get into more details about how applications read and write Streams a bit later\n-in this document when we detail Readers and Writers.\n+Pravega organizes data into **Streams**.  A stream is a durable, elastic, append-only, unbounded sequence of bytes having good performance and strong consistency.  A Pravega stream is\n+similar to but more flexible than a \"topic\" in popular message oriented middleware such as [RabbitMQ](https://www.rabbitmq.com/) or [Apache Kafka](https://kafka.apache.org/).\n+\n+Pravega streams are based on an append-only log data structure. By using the\n+append-only logs, Pravega rapidly ingest data into durable storage. It supports a large variety of application use cases as follows:\n+\n+- Supports stream processing by using frameworks like [Flink](https://flink.apache.org).\n+- Publish/subscribe messaging.\n+- NoSQL databases like Time Series.\n+- Database (TSDB).\n+- Workflow engines.\n+- Event-oriented applications, etc., \n+\n+In Pravega, during the creation of the stream the developers assigns a meaningful\n+name to the stream like \"IoTSensorData\" or \"WebApplicationLog20170330\" to provide\n+more information on the type of data stored in the stream. The Pravega stream names are organized\n+within a **Scope**.  A scope is a string containing meaningful informations like \"FactoryMachines\" or \"HRWebsitelogs\" to aid in better understanding for the developers. A scope acts as a\n+namespace for stream names, all stream names are unique within a scope.\n+\n+A stream is uniquely identified by its combination of the **stream name**\n+and **scope**. Scope can be used to classify names by tenant (in a multi tenant\n+environment) or by department in an organization or by geographic location or any\n+other categorization desired by the developer.\n+\n+A stream is unbounded in size. Pravega does not impose any limits on the occurrence of number of events in the stream or on the number of total bytes that are stored in a stream.\n+Pravega’s design architecture scales up horizontally from few machines into a datacenter.\n+\n+Pravega streams are divided into **Stream Segments**, to handle the large volume of data within a stream. A stream segment is a shard, or partition of the data within a stream. For more information, please see [Stream Segments](#stream-segments) section.\n+\n+The data from the IoT sensor is extracted or read by a variety of applications (_e.g.,_ Java applications) and writes the read or fetched data to the tail (front) of the stream. Applications, such as a [Flink](https://flink.apache.org), can read from any point in the stream. Many applications can read and write the same stream in parallel. Elasticity, scalability, support for large volume of\n+stream data and applications are the highlights of Pravega's design. More information on read and write operations in the streams will be discussed in the [Readers and Writers](#writer) section.\n \n ## Events\n \n-Pravega's client API allows applications to read and write data in Pravega in terms of an Event.  An Event is a\n-set of bytes within a Stream.  An Event could be as simple as a small\n-number of bytes containing a temperature reading from an IoT sensor composed of\n-a timestamp, a metric identifier and a value.  An Event could be web log data\n-associated with a user click on a website.  Events can be anything you can\n-represent as a set of bytes.  Applications make sense of Events using\n-standard Java serializers and deserializers, allowing them to read and write\n-objects in Pravega using similar techniques to reading and writing objects from\n+Pravega's client API allows applications to read and write data in Pravega using **Events**.  An event is represented as a set of bytes within a stream. For example, an event could be as simple as a small number of bytes containing a temperature reading from an IoT sensor composed of\n+a timestamp, a metric identifier and a value or an event could be web log data\n+associated with a user click on a website. Applications make sense of events using\n+standard Java **Serializers** and **Deserializers**, allowing them to read and write\n+objects in Pravega similar to reading and writing objects from","path":"documentation/src/docs/pravega-concepts.md","position":null,"original_position":96,"commit_id":"ecadd202a7ec8321e366f50487b2f14a81de3b25","original_commit_id":"0aada8d063e11a111e398f6d672b27929b5931bc","user":{"login":"Aparnarr","id":40591559,"node_id":"MDQ6VXNlcjQwNTkxNTU5","avatar_url":"https://avatars3.githubusercontent.com/u/40591559?v=4","gravatar_id":"","url":"https://api.github.com/users/Aparnarr","html_url":"https://github.com/Aparnarr","followers_url":"https://api.github.com/users/Aparnarr/followers","following_url":"https://api.github.com/users/Aparnarr/following{/other_user}","gists_url":"https://api.github.com/users/Aparnarr/gists{/gist_id}","starred_url":"https://api.github.com/users/Aparnarr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Aparnarr/subscriptions","organizations_url":"https://api.github.com/users/Aparnarr/orgs","repos_url":"https://api.github.com/users/Aparnarr/repos","events_url":"https://api.github.com/users/Aparnarr/events{/privacy}","received_events_url":"https://api.github.com/users/Aparnarr/received_events","type":"User","site_admin":false},"body":"Accepted Suggestion","created_at":"2018-10-26T07:19:49Z","updated_at":"2018-10-26T07:19:49Z","html_url":"https://github.com/pravega/pravega/pull/3005#discussion_r228426873","pull_request_url":"https://api.github.com/repos/pravega/pravega/pulls/3005","author_association":"CONTRIBUTOR","_links":{"self":{"href":"https://api.github.com/repos/pravega/pravega/pulls/comments/228426873"},"html":{"href":"https://github.com/pravega/pravega/pull/3005#discussion_r228426873"},"pull_request":{"href":"https://api.github.com/repos/pravega/pravega/pulls/3005"}},"in_reply_to_id":227957205},"pull_request":{"url":"https://api.github.com/repos/pravega/pravega/pulls/3005","id":225279543,"node_id":"MDExOlB1bGxSZXF1ZXN0MjI1Mjc5NTQz","html_url":"https://github.com/pravega/pravega/pull/3005","diff_url":"https://github.com/pravega/pravega/pull/3005.diff","patch_url":"https://github.com/pravega/pravega/pull/3005.patch","issue_url":"https://api.github.com/repos/pravega/pravega/issues/3005","number":3005,"state":"open","locked":false,"title":"Issue 2966: Document fix pravegaconcepts doc","user":{"login":"Aparnarr","id":40591559,"node_id":"MDQ6VXNlcjQwNTkxNTU5","avatar_url":"https://avatars3.githubusercontent.com/u/40591559?v=4","gravatar_id":"","url":"https://api.github.com/users/Aparnarr","html_url":"https://github.com/Aparnarr","followers_url":"https://api.github.com/users/Aparnarr/followers","following_url":"https://api.github.com/users/Aparnarr/following{/other_user}","gists_url":"https://api.github.com/users/Aparnarr/gists{/gist_id}","starred_url":"https://api.github.com/users/Aparnarr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Aparnarr/subscriptions","organizations_url":"https://api.github.com/users/Aparnarr/orgs","repos_url":"https://api.github.com/users/Aparnarr/repos","events_url":"https://api.github.com/users/Aparnarr/events{/privacy}","received_events_url":"https://api.github.com/users/Aparnarr/received_events","type":"User","site_admin":false},"body":"**Change log description**  \r\n1. Major content revised\r\n2. Few hyperlinks added\r\n3. All hyperlinks checked.\r\n4. Typos and formats corrected\r\n\r\n**Purpose of the change**  \r\n Fixes 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