How original is Miller?
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It isn't. Miller is one of many, many participants in the online-analytical-processing culture. Other key participants include ``awk``, SQL, spreadsheets, etc. etc.  etc.  Far from being an original concept, Miller explicitly strives to imitate several existing tools:

**The Unix toolkit**: Intentional similarities as described in :doc:`feature-comparison`.

Recipes abound for command-line data analysis using the Unix toolkit. Here are just a couple of my favorites:

* http://en.wikibooks.org/wiki/Ad_Hoc_Data_Analysis_From_The_Unix_Command_Line
* http://www.gregreda.com/2013/07/15/unix-commands-for-data-science
* https://github.com/dbohdan/structured-text-tools

**RecordStream**: Miller owes particular inspiration to `RecordStream <https://github.com/benbernard/RecordStream>`_. The key difference is that RecordStream is a Perl-based tool for manipulating JSON (including requiring it to separately manipulate other formats such as CSV into and out of JSON), while Miller is fast C which handles its formats natively.  The similarities include the ``sort``, ``stats1`` (analog of RecordStream's ``collate``), and ``delta`` operations, as well as ``filter`` and ``put``, and pretty-print formatting.

**stats_m**: A third source of lineage is my Python `stats_m <https://github.com/johnkerl/scripts-math/tree/master/stats>`_ module.  This includes simple single-pass algorithms which form Miller's ``stats1`` and ``stats2`` subcommands.

**SQL**: Fourthly, Miller's ``group-by`` command name is from SQL, as is the term ``aggregate``.

**Added value**: Miller's added values include:

* Name-indexing, compared to the Unix toolkit's positional indexing.
* Raw speed, compared to ``awk``, RecordStream, ``stats_m``, or various other kinds of Python/Ruby/etc. scripts one can easily create.
* Compact keystroking for many common tasks, with a decent amount of flexibility.
* Ability to handle text files on the Unix pipe, without need for creating database tables, compared to SQL databases.
* Various file formats, and on-the-fly format conversion.

**jq**: Miller does for name-indexed text what `jq <https://stedolan.github.io/jq/>`_ does for JSON. If you're not already familiar with ``jq``, please check it out!.

**What about similar tools?**

Here's a comprehensive list: https://github.com/dbohdan/structured-text-tools.  Last I knew it doesn't mention `rows <https://github.com/turicas/rows>`_ so here's a plug for that as well.  As it turns out, I learned about most of these after writing Miller.

**What about DOTADIW?** One of the key points of the `Unix philosophy <http://en.wikipedia.org/wiki/Unix_philosophy>`_ is that a tool should do one thing and do it well.  Hence ``sort`` and ``cut`` do just one thing. Why does Miller put ``awk``-like processing, a few SQL-like operations, and statistical reduction all into one tool (see also :doc:`reference`)?  This is a fair question. First note that many standard tools, such as ``awk`` and ``perl``, do quite a few things -- as does ``jq``.  But I could have pushed for putting format awareness and name-indexing options into ``cut``, ``awk``, and so on (so you could do ``cut -f hostname,uptime`` or ``awk '{sum += $x*$y}END{print sum}'``).  Patching ``cut``, ``sort``, etc. on multiple operating systems is a non-starter in terms of uptake.  Moreover, it makes sense for me to have Miller be a tool which collects together format-aware record-stream processing into one place, with good reuse of Miller-internal library code for its various features.

**Why not use Perl/Python/Ruby etc.?** Maybe you should. With those tools you'll get far more expressive power, and sufficiently quick turnaround time for small-to-medium-sized data.  Using Miller you'll get something less than a complete programming language, but which is fast, with moderate amounts of flexibility and much less keystroking.

When I was first developing Miller I made a survey of several languages. Using low-level implementation languages like C, Go, Rust, and Nim, I'd need to create my own domain-specific language (DSL) which would always be less featured than a full programming language, but I'd get better performance.  Using high-level interpreted languages such as Perl/Python/Ruby I'd get the language's ``eval`` for free and I wouldn't need a DSL; Miller would have mainly been a set of format-specific I/O hooks. If I'd gotten good enough performance from the latter I'd have done it without question and Miller would be far more flexible.  But C won the performance criteria by a landslide so we have Miller in C with a custom DSL.

**No, really, why one more command-line data-manipulation tool?** I wrote Miller because I was frustrated with tools like ``grep``, ``sed``, and so on being *line-aware* without being *format-aware*. The single most poignant example I can think of is seeing people grep data lines out of their CSV files and sadly losing their header lines.  While some lighter-than-SQL processing is very nice to have, at core I wanted the format-awareness of `RecordStream <https://github.com/benbernard/RecordStream>`_ combined with the raw speed of the Unix toolkit. Miller does precisely that.
