=======================================
GAVO DaCHS: DirectGrammars and Boosters
=======================================

:Author: Markus Demleitner
:Email: gavo@ari.uni-heidelberg.de

The import architecture of DaCHS with grammars and rowmakers producing
material suitable for SQL INSERT statements is designed to be flexible
and as declarative as possible.  Its one big drawback is that once you
have to ingest more than a couple of million rows (or less rows with
hundreds of columns) it tends to become slow, leading to ingestion times
in excess of hours or even days.

To remedy this, DaCHS supports "boosters", programs that bypass both
DaCHS' intenstines and SQL INSERT statements, both of which are
responsible for quite some overhead.  Boosters, in constrast, use C code
to fetch data and output binary COPY material to be dumped into the
table.  The net result are very significant speedups; a factor of 100 is
easily attainable.

Of course, there are several downsides.  One is that you have to write
(and probably debug) C code, and schema changes will become fairly
painful, requiring surgery in the C code (a notable exception are direct
grammars reading from FITS binary tables; the latter contain sufficient
metadata to allow fully automatic code generation in simple cases).
Also, direct grammars can only operate on single tables; data
descriptors containing more than one ``make`` cannot have direct
grammars.  As direct grammars talk to the database engine fairly
directly, the table definition must have ``onDisk="true"``.

Rowmakers given in ``make`` elements sitting behind direct grammars are
ignored; any manipulations to the data coming in must be made within the
C code.  It is not an error for rowmakers to be present, though.  This
lets you test and debug with normal DaCHS grammars and then use a
booster for the whole (potentially big) dataset by just commenting out
the conventional grammar and commenting in the direct grammar.  This is
especially useful for table compares (e.g., using ``gavo info``) to
verify that the booster does the same thing as the conventional
grammar/rowmaker combo.

To use a booster, say::

  <directGrammar id="boost"
    type="(something)" cBooster="res/boosterfunc.c"/>

in a ``data`` element.  The path in the ``cBooster`` attribute is interpreted 
relative to the RD's resdir.  The type argument says rougly what kind of
source you're parsing from.  Values allowed here include:

* ``col`` (the default) – parse from stuff conventionally handled by a
  ``columnGrammar``
* ``bin`` – parse from data that has fixed-length binary records (this
  is stuff that a ``binaryGrammar`` would grok)
* ``split`` – parse from files that have fields separated by some 
  constant sequence of character (conventionally, these can be parsed
  by a ``reGrammar``)
* ``fits`` – parse from FITS binary tables (that's what a
  ``fitsTableGrammar`` can read).

You will then need to generate the C source using the ``mkboost``
subcommand, which needs the reference of the ``directGrammar`` element
as an argument::

  gavo mkboost myresdir/q#boost > res/boosterfunc.c

You will then (typically) need to edit ``boosterfunc.c``; if you're
done, just say ``gavo imp`` as usual.

The source code generated typically is really mean.  The preference
is to make it coredump rather than give fancy errors, under the
assumption that error messages from the booster would in general help
less than the post-mortem dumps; this of course also means that you
should not use direct grammars to parse from potentially malicious
sources unless you substantially harden the generated code.  

To figure out what's wrong if things go wrong, say::

  ulimit -c unlimited  # bash and friends
  gavo imp q
  gdb bin/booster core
  where # that's for gdb

This should give you the line where things failed, and of course the
full power of gdb to inspect how that happened.


Booster source code
-------------------

Once you've generated the booster source, you're free to change it in
whatever way you fancy.  On schema updates, unfortunately, you'll have
to merge in changes manually, as we've not found a  sensible and general
way to preserve arbitrary source changes when (re-)generating a booster.
If you have a creative idea how better to separate generated and
hand-made code, we're certainly interested.  The way things are now, if
you change the schema, you can re-run ``gavo mkboost`` but have to merge
any changes manually.

The code generated starts somewhat like this::

  #include <math.h>
  #include <string.h>
  #include "boosterskel.h"

  #define QUERY_N_PARS 33

  enum outputFields {
    fi_localid,              /* Identifier, text */
    fi_pmra,                 /* PM (alpha), real */
    fi_pmde,                 /* PM (delta), real */

The definition of ``QUERY_N_PARS`` (which is the number of columns in the
table) is essential and must remain in this form, as the function
building the booster greps it out of the source code to communicate this
value to the booster boilerplate; this, however, means that you're free
to change the concrete number if the number of table columns changes in
the source file (you'd have to adjust the outputFields as well; this is
typcially going to be a cut-and-paste job from a repeated run of ``gavo
mkboost``).  Again, ``QUERY_N_PARS`` must always be equal to the number
of columns in the target table.

The code continues with an enumeration mapping symbolic names to the
indices of the corresponding columns in the target table; the names are
simple fi\_ and the field destination lowercased.  If you only use these
names to access fields, cutting and pasting on later schema changes
should be fairly painless and safe.

While you shouldn't need to change any of this, you in general have to
change the ``getTuple`` function.  What it looks like strongly depends
on the sort of booster you're generating for; this includes the
prototype.

What's common is that getTuple needs to return a ``Field`` array.  All
boosters declare the return value like this::

    static Field vals[QUERY_N_PARS];

– it needs to be static as a pointer to it is returned from the
function; don't rely on anything in there to be stable across function
calls, though, as the serialization to COPY material might mess around
in that memory.  The name ``vals`` is expected by, e.g., the ``F`` macro and
must therefore not be changed.

``Field`` is defined as follows::

  typedef struct Field_s {
    valType type;
    int length; /* ignored for anything but VAL_TEXT */
    union {
      char *c_ptr;
      double c_double;
      float c_float;
      int32_t c_int32;
      int8_t c_int8;
    } val;
  } Field;

where ``type`` is one of::

  typedef enum valType_e {
	  VAL_NULL,
	  VAL_BOOL,
	  VAL_CHAR,
	  VAL_SHORT,
	  VAL_INT,
	  VAL_BIGINT,
	  VAL_FLOAT,
	  VAL_DOUBLE,
	  VAL_TEXT,
	  VAL_JDATE,  /* a julian year ("J2000.0"); this is stored as a simple double */
	  VAL_DATE,   /* date expressed as a time_t */
	  VAL_DATETIME, /* date and time expressed as a time_t */
  } valType;


JDATE is a julian day number to be dumped as a date (rather than a
datetime).  For other ways to represent dates and datetimes, see below.

You can, and frequently will, fill the stuff by hand.  There are,
however, a couple of functions that take care of some standard
situations:

* ``void linearTransform(Field *field, double offset, double factor)`` --
  changes field in place to ``offset+factor*oldValue``.  Handles NULL
  correctly, silently does nothing for anything non-numeric
* ``void parseFloatWithMagicNULL(char *src, Field *field, int start, int
  len, char *magicVal)`` -- parses a float from ``src[start:start+len]`` into
  field, writing NULL when magicVal is found in the field.
* ``void parseDouble(char *src, Field *field, int start, int len)`` --
  parses a double from ``src[start:start+len]`` into field, writing NULL if 
  it's whitespace only.
* ``void parseInt(char *src, Field *field, int start, int len)`` -- parses a
  32-bit int from ``src[start:start+len]`` into field.
* ``void parseShort(char *src, Field *field, int start, int len)`` -- parses a
  16-bit int from ``src[start:start+len]`` into field.
* ``void parseBlankBoolean(char *src, Field *field, int srcInd)`` -- parses
  a boolean such that field becomes true when src[srcInd] is nonempty.
* ``void parseString(char *src, Field *field, int start, int len, char
  *space)`` -- copies len bytes starting at start from src into space (you
  are responsible for allocating that; usually, a static buffer should
  do, since the postgres input is generated before the next input line
  is parsed) and stuffs the whole thing into field.
* ``void parseChar(char *src, Field *field, int srcInd)`` -- guess.
* ``MAKE_NULL(fi)`` -- makes fi NULL
* ``MAKE_DOUBLE(fi, value)`` -- make fi a double with value
* ``MAKE_FLOAT(fi, value)`` -- 
* ``MAKE_SHORT(fi, value)`` -- 
* ``MAKE_CHAR(fi, value)`` --
* ``MAKE_JDATE(fi, value)`` --
* ``MAKE_TEXT(fi, value)`` -- note that you must manage the memory of value
  yourself.  In particular, it must not be automatic memory of getTuple,
  since that will not be valid when the tuple actually is built.  Most
  commonly, you'll be using a static buffer here.
* ``MAKE_CHAR_NULL(fi, value, nullvalue)`` -- makes fi a char with value
  unless value==nullvalue; in that case, fi becomes a NULL
* ``double mjdToJYear(mjd)`` -- returns a julian year for mjd
* ``AS2DEG(field)`` -- turns a field value in arcsecs to degrees
* ``MAS2DEG(field)`` -- turns a field value in milli-arcsecs to degrees

Of course, you can also manually copy or delimit data and use fieldscanf
as documented in `split boosters`_

Boosters are linked together with ``boosterskel.c`` and must include
``boosterskel.h``.  If you're interested what these things do (or want
to fix bugs, or whatever), you can get the files using::

  gavo admin dumpDF src/boosterskel.c # or .h


Line-based boosters
-------------------

These are boosters that read from a text file, line by line.  Currently,
the maximum line length is set to 4000 (``INPUT_LINE_MAX`` in
``boosterskel.c``).  It is up to the parsing function to split and
digest this text line.


Col boosters
''''''''''''

For col boosters, the getTuple function looks somewhat like this::

  Field *getTuple(char *inputLine)
  {
    static Field vals[QUERY_N_PARS];

    parseWhatever(inputLine, F(fi_localid), start, len);
    parseFloat(inputLine, F(fi_pmra), start, len);
    parseFloat(inputLine, F(fi_pmde), start, len);
    parseFloat(inputLine, F(fi_raerr), start, len);

Here, it's your job to fill out start and len (at least; start is
zero-based).  ``gavo mkboost`` inserts parseXXX function calls according
to the table metadata, which should be what you want in general.  Add
scaling or other processing as required.


Split boosters
''''''''''''''

When the input data comes as xSV (e.g., values separated by vertical
bars, commas, or tabs), give a ``splitChar`` and set the ``type``
attribute to ``split`` in the ``directGrammar``.

This then creates a source like::

 	char *curCont = strtok(inputLine, "\t");
	fieldscanf(curCont, fi_objid, VAL_INT_64);
	curCont = strtok(NULL, "\t");
	fieldscanf(curCont, fi_run, VAL_SHORT);

etc.  Thus, the input line is parsed using strtok, and each value is
parsed using the ``fieldscanf`` function.  This function takes the string
containing the literal in the first argument, the field index in the
second, and finally the type specifier.  If the data comes in the
sequence of the table columns, the generated source *might* just work.

*Warning*: C's standard strtok function merges adjacent separators,
i.e., ``foo|bar||baz`` would just yield three tokens, foo, bar, and baz.
With astronomical data, this is typically not what you want.  Therefore,
the generated booster function will have a line like::

  #define strtok strtok_u

Delete it in case that you need the POSIX strtok behaviour. This would
in particular apply if you have whitespace separated data with a
variable number of blanks (which, however, would suggest that you're
really looking at material for a col booster).



Bin boosters
------------

When you get binary data of fixed record length, set the ``recordSize``
attribute on the ``DirectGrammar`` element::

  <DirectGrammar type="bin" recordSize="300"...

Note that  a ``recordSize`` larger than ``INPUT_LINE_MAX`` will cause a
buffer overflow.

You are mainly on your own in terms of segmentation, but for entering
values, you can use the ``MAKE_*`` discussed above.

For these in particular, use the the portable type specifiers for
integral types, viz., ``int8_t``, ``int16_t``, ``int32_t``, and
``int64_t`` and these names with a ``u`` in front.

In particular with binary boosters, it is essential you always properly
cast what you read, e.g.,::

  MAKE_DOUBLE(fi_dej2000, -90+*(int32_t*)(line+4)/1e6); /* SPD */

when a declination is given as mas of south polar distance.


FITS boosters
-------------

These read from FITS binary tables and are really a somewhat special
beast.  To build one of those, DaCHS inspects the first file matched by
the parent data's ``sources`` element (which also means these won't work
outside of a ``data`` element).  DaCHS expects each table column to have
a match (i.e., after lowercasing the name in the FITS table) in the FITS
table.  FITS table column without a match in the database table are
ignored.

FITS binary tables are organized by columns rather than by rows, bearing
witness to their FORTRAN heritage.  The way the boosters are currently
generated, all these columns are completely read into memory, which
means you cannot ingest FITS binary tables that do not fit into your
machine's memory.  Fixing this would be fairly straightforward (patches
are welcome, but we'll also fix this if you ask for it).

If you need to postprocess the items, we recommend you do that again in
the ``getTuple`` function (note how that gets passed the row index) for
maintainability, rather than directly after reading the rows.


Filling in data manually
------------------------

The ``F(index)`` macro lets you access the field info directly.  So, you
could enter a fixed-length piece of memory into ``fi_magic`` like this::

  static char bufForMagic[8];

  memcpy(bufForMagic, inputLine+20, 8);
  F(fi_magic)->type = VAL_TEXT;
  F(fi_magic)->val.c_ptr =  bufForMagic;
  F(fi_magic)->length = 8;

Having static buffers in ``getTuple`` is usually ok since the COPY input
is generated before ``getTuple`` is called again.

It is quite common to have to handle null values.  In the example above,
this could look like this if a NULL for magic were signified by a F in
``inputLine[19]``::

  static char bufForMagic[8];

  if (inputLine[19]=='F') {
    F(fi_magic)->type = VAL_NULL;
  } else {
    memcpy(bufForMagic, inputLine+20, 8);
    ...


Skipping a record
'''''''''''''''''

If you need to skip a record, do::

  longjmp(ignoreRecord)

in ``getTuple``.  That works independently of the booster type.



Dates and times
'''''''''''''''

The boosters treat "normal" dates and datetimes as ``struct tm``s.  If you
need a larger range, use ``VAL_JDATE``, which lets you store julian
dates in floats.  Julian dates are serialized to dates rather than
datetimes.

To parse ``VAL_DATE`` or ``VAL_DATETIME``, you will write something
like::

	fieldscanf(curCont, fi_date, VAL_DATE, "%Y-%m-%d");

if parsing from date strings.  If your input is something weird, figure
out a way to generate a ``struct tm`` as defined in ``time.h``.  Then
write::

  struct tm timeParts;
  timeParts.tm_sec = 12;
  ...
  timeParts.tm_year = 1920;
  F(fi_dt)->val.time = timeParts;
  F(fi_dt).type = VAL_DATETIME;

(or ``VAL_DATE``, as the case may be).

Having said all this, long experience has taught us it's ususally best
do have dates and such in the database as MJD or julian years.  You can
format those to ISO strings (or, really, anything else you want) on
output by using display hints on ``outpuField`` or even ``column``
itself.

MJDs are just so much easier to handle within ADQL queries.  Support for
timestamps, on the other hand, is extremely lousy.