Adding upstream version 5:7.2.4.upstream/5%7.2.4

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

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+[Note: this is the Redis manifesto, for general information about
+       installing and running Redis read the README file instead.]
+
+Redis Manifesto
+===============
+
+1 - A DSL for Abstract Data Types. Redis is a DSL (Domain Specific Language)
+    that manipulates abstract data types and implemented as a TCP daemon.
+    Commands manipulate a key space where keys are binary-safe strings and
+    values are different kinds of abstract data types. Every data type
+    represents an abstract version of a fundamental data structure. For instance
+    Redis Lists are an abstract representation of linked lists. In Redis, the
+    essence of a data type isn't just the kind of operations that the data types
+    support, but also the space and time complexity of the data type and the
+    operations performed upon it.
+
+2 - Memory storage is #1. The Redis data set, composed of defined key-value
+    pairs, is primarily stored in the computer's memory. The amount of memory in
+    all kinds of computers, including entry-level servers, is increasing
+    significantly each year. Memory is fast, and allows Redis to have very
+    predictable performance. Datasets composed of 10k or 40 millions keys will
+    perform similarly. Complex data types like Redis Sorted Sets are easy to
+    implement and manipulate in memory with good performance, making Redis very
+    simple. Redis will continue to explore alternative options (where data can
+    be optionally stored on disk, say) but the main goal of the project remains
+    the development of an in-memory database.
+
+3 - Fundamental data structures for a fundamental API. The Redis API is a direct
+    consequence of fundamental data structures. APIs can often be arbitrary but
+    not an API that resembles the nature of fundamental data structures. If we
+    ever meet intelligent life forms from another part of the universe, they'll
+    likely know, understand and recognize the same basic data structures we have
+    in our computer science books. Redis will avoid intermediate layers in API,
+    so that the complexity is obvious and more complex operations can be
+    performed as the sum of the basic operations.
+
+4 - We believe in code efficiency. Computers get faster and faster, yet we
+    believe that abusing computing capabilities is not wise: the amount of
+    operations you can do for a given amount of energy remains anyway a
+    significant parameter: it allows to do more with less computers and, at
+    the same time, having a smaller environmental impact. Similarly Redis is
+    able to "scale down" to smaller devices. It is perfectly usable in a
+    Raspberry Pi and other small ARM based computers. Faster code having
+    just the layers of abstractions that are really needed will also result,
+    often, in more predictable performances. We think likewise about memory
+    usage, one of the fundamental goals of the Redis project is to
+    incrementally build more and more memory efficient data structures, so that
+    problems that were not approachable in RAM in the past will be perfectly
+    fine to handle in the future.
+
+5 - Code is like a poem; it's not just something we write to reach some
+    practical result. Sometimes people that are far from the Redis philosophy
+    suggest using other code written by other authors (frequently in other
+    languages) in order to implement something Redis currently lacks. But to us
+    this is like if Shakespeare decided to end Enrico IV using the Paradiso from
+    the Divina Commedia. Is using any external code a bad idea? Not at all. Like
+    in "One Thousand and One Nights" smaller self contained stories are embedded
+    in a bigger story, we'll be happy to use beautiful self contained libraries
+    when needed. At the same time, when writing the Redis story we're trying to
+    write smaller stories that will fit in to other code.
+
+6 - We're against complexity. We believe designing systems is a fight against
+    complexity. We'll accept to fight the complexity when it's worthwhile but
+    we'll try hard to recognize when a small feature is not worth 1000s of lines
+    of code. Most of the time the best way to fight complexity is by not
+    creating it at all. Complexity is also a form of lock-in: code that is
+    very hard to understand cannot be modified by users in an independent way
+    regardless of the license. One of the main Redis goals is to remain
+    understandable, enough for a single programmer to have a clear idea of how
+    it works in detail just reading the source code for a couple of weeks.
+
+7 - Threading is not a silver bullet. Instead of making Redis threaded we
+    believe on the idea of an efficient (mostly) single threaded Redis core.
+    Multiple of such cores, that may run in the same computer or may run
+    in multiple computers, are abstracted away as a single big system by
+    higher order protocols and features: Redis Cluster and the upcoming
+    Redis Proxy are our main goals. A shared nothing approach is not just
+    much simpler (see the previous point in this document), is also optimal
+    in NUMA systems. In the specific case of Redis it allows for each instance
+    to have a more limited amount of data, making the Redis persist-by-fork
+    approach more sounding. In the future we may explore parallelism only for
+    I/O, which is the low hanging fruit: minimal complexity could provide an
+    improved single process experience.
+
+8 - Two levels of API. The Redis API has two levels: 1) a subset of the API fits
+    naturally into a distributed version of Redis and 2) a more complex API that
+    supports multi-key operations. Both are useful if used judiciously but
+    there's no way to make the more complex multi-keys API distributed in an
+    opaque way without violating our other principles. We don't want to provide
+    the illusion of something that will work magically when actually it can't in
+    all cases. Instead we'll provide commands to quickly migrate keys from one
+    instance to another to perform multi-key operations and expose the
+    trade-offs to the user.
+
+9 - We optimize for joy. We believe writing code is a lot of hard work, and the
+    only way it can be worth is by enjoying it. When there is no longer joy in
+    writing code, the best thing to do is stop. To prevent this, we'll avoid
+    taking paths that will make Redis less of a joy to develop.
+
+10 - All the above points are put together in what we call opportunistic
+     programming: trying to get the most for the user with minimal increases
+     in complexity (hanging fruits). Solve 95% of the problem with 5% of the
+     code when it is acceptable. Avoid a fixed schedule but follow the flow of
+     user requests, inspiration, Redis internal readiness for certain features
+     (sometimes many past changes reach a critical point making a previously
+     complex feature very easy to obtain).