Re: json api WIP patch

On 01/08/2013 01:45 AM, james wrote:
>> The processing functions have been extended to provide
>> populate_record() and populate_recordset() functions.The latter in
>> particular could be useful in decomposing a piece of json
>> representing an array of flat objects (a fairly common pattern) into
>> a set of Postgres records in a single pass.
>
> So this would allow an 'insert into ... select ... from
> <unpack-the-JSON>(...)'?

Yes.

>
> I had been wondering how to do such an insertion efficiently in the
> context of SPI, but it seems that there is no SPI_copy equiv that
> would allow a query parse and plan to be avoided.

Your query above would need to be planned too, although the plan will be
trivial.

>
> Is this mechanism likely to be as fast as we can get at the moment in
> contexts where copy is not feasible?
>

You should not try to use it as a general bulk load facility. And it
will not be as fast as COPY for several reasons, including that the Json
parsing routines are necessarily much heavier than the COPY parse
routines, which have in any case been optimized over quite a long
period. Also, a single json datum is limited to no more than 1Gb. If you
have such a datum, parsing it involves having it in memory and then
taking a copy (I wonder if we could avoid that step - will take a look).
Then each object is decomposed into a hash table of key value pairs,
which it then used to construct the record datum. Each field name in
the result record is used to look up the value in the hash table - this
happens once in the case of populate_record() and once per object in the
array in the case of populate_recordset(). In the latter case the
resulting records are put into a tuplestore structure (which spills to
disk if necessary) which is then returned to the caller when all the
objects in the json array are processed. COPY doesn't have these sorts
of issues. It knows without having to look things up where each datum is
in each record, and it stashes the result straight into the target
table. It can read and insert huge numbers of rows without significant
memory implications.

Both these routines and COPY in non-binary mode use the data type input
routines to convert text values. In some cases (very notably timestamps)
these routines can easily be shown to be fantastically expensive
compared to binary input. This is part of what has led to the creation
of utilities like pg_bulkload.

Perhaps if you give us a higher level view of what you're trying to
achieve we can help you better.

cheers

andrew