Re: Update with last known location?

Hi Erik,

Do you mean in this section of the SQL?
.....
filled_geoms AS (
SELECT
ppid,
point_time,
the_geom
FROM
hybrid_location
WHERE
the_geom IS NOT NULL)
...

Thanks

James

On 29 January 2014 17:57, Erik Darling <edarling80(at)gmail(dot)com> wrote:
> Hi James,
>
> I think you're still stuck with sort of unnecessary ('too much' ) data
> coming from the right side of your left join. If so, one option I would
> consider is using DENSE_RANK() the way you use ROW_NUMBER(), in the
> filled_geoms table. If you partition by id and order by date descending, you
> can do an additional d_rank = 1 filter to only get the most recent activity.
> I believe this is what you want to set your NULL values to, no?
>
>
>
>
> On Wed, Jan 29, 2014 at 12:41 PM, James David Smith
> <james(dot)david(dot)smith(at)gmail(dot)com> wrote:
>>
>> On 29 January 2014 16:02, Erik Darling <edarling80(at)gmail(dot)com> wrote:
>> > I would re-suggest using a CTE to contain each dataset to ensure your
>> > selects are distilling them correctly, and then using a final query to
>> > join
>> > them. You can then either update your data directly through the CTE(s),
>> > or
>> > insert the results to another table to do some further testing. I think
>> > you'll find this method presents the data a bit more ergonomically for
>> > analysis.
>> >
>> > http://www.postgresql.org/docs/9.3/static/queries-with.html
>> >
>> >
>> >
>> > On Wed, Jan 29, 2014 at 10:45 AM, James David Smith
>> > <james(dot)david(dot)smith(at)gmail(dot)com> wrote:
>> >>
>> >> Hi Erik/all,
>> >>
>> >> I just tried that, but it's tricky. The 'extra' data is indeed coming
>> >> from the right side of the join, but it's hard to select only the max
>> >> from it. Maybe it's possible but I've not managed to do it. Here is
>> >> where I am, which is so very close.
>> >>
>> >> SELECT
>> >> DISTINCT(a.ppid, a.point_time, a.the_geom) as
>> >> row_that_needs_geom_updating,
>> >> max(b.point_time) OVER (PARTITION BY a.ppid, a.point_time) as
>> >> last_known_position_time
>> >> FROM
>> >> test a
>> >> INNER JOIN
>> >> (SELECT ppid,
>> >> point_time,
>> >> the_geom
>> >> FROM test
>> >> WHERE the_geom IS NOT NULL) b
>> >> ON b.point_time < a.point_time
>> >> AND a.ppid = b.ppid
>> >> WHERE a.the_geom IS NULL;
>> >>
>> >> If you see attached screen-print, the output is the rows that I want.
>> >> However I've had to use DISTINCT to stop the duplication. Also I've
>> >> not managed to pull through 'the_geom' from the JOIN. I'm not sure
>> >> how. Anyone?
>> >>
>> >> But it's kind of working. :-)
>> >>
>> >> Worst case if I can't figure out how to solve this in one query I'll
>> >> have to store the result of the above, and then use it as a basis for
>> >> another query I think.
>> >>
>> >> Thanks
>> >>
>> >> James
>> >>
>> >>
>> >>
>> >> On 29 January 2014 12:56, Erik Darling <edarling80(at)gmail(dot)com> wrote:
>> >> > I would try partitioning the second time you call row_number, perhaps
>> >> > by
>> >> > ID,
>> >> > and then selecting the MAX() from that, since I think the too much
>> >> > data
>> >> > you're referring to is coming from the right side of your join.
>> >> >
>> >> > On Jan 29, 2014 7:23 AM, "James David Smith"
>> >> > <james(dot)david(dot)smith(at)gmail(dot)com>
>> >> > wrote:
>> >> >>
>> >> >> On 28 January 2014 23:15, Gavin Flower
>> >> >> <GavinFlower(at)archidevsys(dot)co(dot)nz>
>> >> >> wrote:
>> >> >> > On 29/01/14 11:00, Kevin Grittner wrote:
>> >> >> >>
>> >> >> >> James David Smith <james(dot)david(dot)smith(at)gmail(dot)com> wrote:
>> >> >> >>
>> >> >> >>> Given the data is so large I don't want to be taking the data
>> >> >> >>> out
>> >> >> >>> to a CSV or whatever and then loading it back in. I'd like to do
>> >> >> >>> this within the database using SQL. I thought I would be able to
>> >> >> >>> do this using a LOOP to be honest.
>> >> >> >>
>> >> >> >> I would be amazed if you couldn't do this with a single UPDATE
>> >> >> >> statement. I've generally found declarative forms of such work
>> >> >> >> to
>> >> >> >> be at least one order of magnitude faster than going to either a
>> >> >> >> PL
>> >> >> >> or a script approach. I would start by putting together a SELECT
>> >> >> >> query using window functions and maybe a CTE or two to list all
>> >> >> >> the
>> >> >> >> primary keys which need updating and the new values they should
>> >> >> >> have. Once that SELECT was looking good, I would put it in the
>> >> >> >> FROM clause of an UPDATE statement.
>> >> >> >>
>> >> >> >> That should work, but if you are updating a large percentage of
>> >> >> >> the
>> >> >> >> table, I would go one step further before running this against
>> >> >> >> the
>> >> >> >> production tables. I would put a LIMIT on the above-mentioned
>> >> >> >> SELECT of something like 10000 rows, and script a loop that
>> >> >> >> alternates between the UPDATE and a VACUUM ANALYZE on the table.
>> >> >> >>
>> >> >> >> --
>> >> >> >> Kevin Grittner
>> >> >> >> EDB: http://www.enterprisedb.com
>> >> >> >> The Enterprise PostgreSQL Company
>> >> >> >>
>> >> >> >>
>> >> >> > James, you might consider dropping as many indexes on the table as
>> >> >> > you
>> >> >> > safely can, and rebuilding them after the mass update. If you
>> >> >> > have
>> >> >> > lots
>> >> >> > of
>> >> >> > such indexes, you will find this apprtoach to be a lot faster.
>> >> >> >
>> >> >> >
>> >> >> > Cheers,
>> >> >> > Gavin
>> >> >>
>> >> >> Hi all,
>> >> >>
>> >> >> Thanks for your help and assistance. I think that window functions,
>> >> >> and inparticular the PARTITION function, is 100% the way to go.
>> >> >> I've
>> >> >> been concentrating on a SELECT statement for now and am close but
>> >> >> not
>> >> >> quite close enough. The below query gets all the data I want, but
>> >> >> *too* much. What I've essentially done is:
>> >> >>
>> >> >> - Select all the rows that don't have any geom information
>> >> >> - Join them with all rows before this point that *do* have geom
>> >> >> information.
>> >> >> - Before doing this join, use partition to generate row numbers.
>> >> >>
>> >> >> The attached screen grab shows the result of my query below.
>> >> >> Unfortunately this is generating alot of joins that I don't want.
>> >> >> This
>> >> >> won't be practical when doing it with 75,000 people.
>> >> >>
>> >> >> Thoughts and code suggestions very much appreciated... if needed I
>> >> >> could put together some SQL to create an example table?
>> >> >>
>> >> >> Thanks
>> >> >>
>> >> >> SELECT row_number() OVER (PARTITION BY test.point_time ORDER BY
>> >> >> test.point_time) as test_row,
>> >> >> test.ppid as test_ppid,
>> >> >> test.point_time as test_point_time,
>> >> >> test.the_geom as test_the_geom,
>> >> >> a.ppid as a_ppid,
>> >> >> a.point_time as a_point_time,
>> >> >> a.the_geom as a_the_geom,
>> >> >> a.a_row
>> >> >> FROM test
>> >> >> LEFT JOIN (
>> >> >> SELECT the_geom,
>> >> >> ppid,
>> >> >> point_time,
>> >> >> row_number() OVER (ORDER BY ppid, point_time) as a_row
>> >> >> FROM test
>> >> >> WHERE the_geom IS NOT NULL) a
>> >> >> ON a.point_time < test.point_time
>> >> >> AND a.ppid = test.ppid
>> >> >> WHERE test.the_geom IS NULL
>> >> >> ORDER BY test.point_time)
>> >> >>
>>
>>
>> Hi Erik / all,
>>
>> So I think I've managed to re-write my queries using CTEs. The below
>> code now does get me the data that I want from this. But to do so it
>> is going to create a frankly huge table in the bit of the SQL where it
>> makes the table called 'partitioned'. My rough guess is that it'll
>> have to make a table of about 100 billion rows in order to get data I
>> need ( about 108 million rows).
>>
>> Could someone please glance through it for me and suggest how to write
>> it more efficiently?
>>
>> Thanks
>>
>> James
>>
>> WITH missing_geoms AS (
>> SELECT ppid,
>> point_time,
>> the_geom
>> FROM hybrid_location
>> WHERE the_geom IS NULL)
>> -----------------
>> ,filled_geoms AS (
>> SELECT ppid,
>> point_time,
>> the_geom
>> FROM hybrid_location
>> WHERE the_geom IS NOT NULL)
>> ----------------
>> ,partitioned AS (
>> SELECT missing_geoms.ppid,
>> missing_geoms.point_time,
>> missing_geoms.the_geom,
>> filled_geoms.ppid,
>> filled_geoms.point_time,
>> filled_geoms.the_geom,
>> row_number() OVER ( PARTITION BY missing_geoms.ppid,
>> missing_geoms.point_time
>> ORDER BY missing_geoms.ppid,
>> missing_geoms.point_time,
>> filled_geoms.ppid,
>> filled_geoms.point_time DESC)
>> FROM missing_geoms
>> LEFT JOIN filled_geoms
>> ON filled_geoms.point_time < missing_geoms.point_time
>> AND filled_geoms.ppid = missing_geoms.ppid)
>> --------------
>> SELECT *
>> FROM partitioned
>> WHERE row_number = 1;
>>
>> James
>
>