Github user alpinegizmo commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3301#discussion_r101011358
  
    --- Diff: docs/internals/filesystems.md ---
    @@ -0,0 +1,138 @@
    +---
    +title: "File Systems"
    +nav-parent_id: internals
    +nav-pos: 10
    +---
    +<!--
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    +
    +* Replaced by the TOC
    +{:toc}
    +
    +Flink has its own file system abstraction via the 
`org.apache.flink.core.fs.FileSystem` class.
    +This abstraction provides a common set of operations and minimal 
guarantees across various types
    +of file system implementations.
    +
    +The `FileSystem`'s set of available operations is quite limited, in order 
to suport a wide
    +range of file systems. For example, appending to or mutating existing 
files is not supported.
    +
    +File systems are identified by a *file system scheme*, such as `file://`, 
`hdfs://`, etc.
    +
    +# Implementations
    +
    +Flink implements the file systems directly, with the following file system 
schemes:
    +
    +  - `file`, which represents the machines local file system.
    +
    +Other file system types are accessed by an implementation that bridges to 
the suite of file systems supported by
    +[Apache Hadoop](https://hadoop.apache.org/). The following is an 
incomplete list of examples:
    +
    +  - `hdfs`: Hadoop Distributed File System
    +  - `s3`, `s3n`, and `s3a`: Amazon S3 file system
    +  - `gcs`: Google Cloud Storage
    +  - `maprfs`: The MapR distributed file system
    +  - ...
    +
    +Flink loads Hadoop's file systems transparently if it finds the Hadoop 
File System classes in the class path and finds a valid
    +Hadoop configuration. By default, it looks for the Hadoop configuration in 
the class path. Alternatively, one can specify a
    +custom location via the configuration entry `fs.hdfs.hadoopconf`.
    +
    +
    +# Persistence Guarantees
    +
    +These `FileSystem` and its `FsDataOutputStream` instances are used to 
persistently store data, both for results of applications
    +and for fault tolerance and recovery. It is therefore crucial that the 
persistence semantics of these streams are well defined.
    +
    +## Definition of Persistence Guarantees
    +
    +Data written to an output stream is considered persistent, if two 
requirements are met:
    +
    +  1. **Visibility Requirement:** It must be guaranteed that all other 
processes, machines,
    +     virtual machines, containers, etc. that are able to access the file 
see the data consistently
    +     when given the absolute file path. This requirement is similar to the 
*close-to-open*
    +     semantics defined by POSIX, but restricted to the file itself (by its 
absolute path).
    +
    +  2. **Durability Requirement:** The file system's specific 
durability/persistence requirements
    +     must be met. These are specific to the particular file system. For 
example the
    +     {@link LocalFileSystem} does not provide any durability guarantees 
for crashes of both
    +     hardware and operating system, while replicated distributed file 
systems (like HDFS)
    +     guarantee typically durability in the presence of up to concurrent 
failure or *n*
    --- End diff --
    
     typically guarantee durability in the presence of at most *n* concurrent 
node failures,


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