I'm completely new to PostGIS (and databases in general), so apologies if I use terms incorrectly.
I have two tables with multilinestring geometries, and I want to copy one field from one table to the other based on geometries. The geometries don't overlap, so I want to find the closest geometry. I've tried googling, and have found lots of ways of trying it (ST_DISTANCE, etc), but the queries always return wrong results (after checking them on the map).
e.g.
TABLE1 has the field to be copied, TABLE2 does not. I want to go through all records in TABLE2 and find it's closest record in TABLE1, then copy a field across.
Sorry if my description isn't clear, I'm finding hard to put it into a clear sentence (which makes googling it hard). I'd really appreciate it if anyone could help with this, or at least point me in the right direction. Ideally I want a SELECT statement to check the results, then an INSERT (or similar) to update the table, or possibly create a third 'joined' table.
I've been using PGAdmin, and QGIS.
Thanks,
You could create a third joined table using something like this:
CREATE TABLE joined_table (id1 int, id2 int) AS
SELECT DISTINCT ON(table1.id) table1.id,
table2.id
FROM table1, table2
WHERE table1.id <> table2.id
ORDER BY table1.id, ST_Distance(table1.the_geom,table2.the_geom)
If it seems too slow, you can restrict the results adding this
AND ST_DWithin(table1.the_geom, table2.the_geom, 300)
to the where condition.
You can find a better description of the solution here
http://www.bostongis.com/?content_name=postgis_nearest_neighbor
and similar questions on stackoverflow here
https://gis.stackexchange.com/questions/3249/postgis-assign-id-of-point-in-layer-a-to-closest-point-in-layer-b
and here
https://gis.stackexchange.com/questions/155373/postgis-nearest-point-with-lateral-join-in-postgresql-9-3
Related
I have to tables. A table that we call "The Vault" which has a ton of demographic data and Table A which has some of the demographic data. I am new at SQL Server, and I was tasked with finding a list of 21 students in The Vault table (Table B). Problem, there is no primary key or anything distinctive besides, FirstName, LastName, BirthMonth, Birthday, Birthyear.
Goal: We could not match these people in the conventional way we have, and so we are attempting a Hail Mary to try to see which of these shared combinations will perhaps land us with a match.
What I have tried doing: I have placed both tables on tempt tables, table A and table B, and I am trying to do an Inner Join but then I realized that in order to make it work, I would have to do a crazy join statement where I say (see the code below)
But the problem as you can imagine is it brings a lot more than my current 21 records and is in the thousands so then I would have to make that join statement longer but I am not sure this is the right way to do this. I believe that is where the WHERE clause would come in no?
Question: How do I compare these two tables for possible matches using a WHERE clause where I can mix and match different columns without having to filter the data constrains in the ON clause of the JOIN. I don't want to JOIN on like 6 different columns. Is there another way to do this so I can perhaps learn. I understand this is easier when you have a primary key shared and that would be the JOIN criteria I would use, but when we are comparing two tables to find possible matches, I have never done that.
FROM #Table a
INNER JOIN #table b ON (a.LAST_NAME = B.LAST_NAME AND a.FIRST_NAME = b.FIRST_NAME.....)```
Hi am hoping someone can help my SQL theory out. I have to create a set of reports which use joins from multiple tables. These reports are running far slower than I would like and I am hoping to optimize my SQL although my knowledge has hit a wall and I cant seem to find anything on Google.
I am hoping someone here can give me some best practice guidance.
Essentially I am trying to filter on the results set as it comes back to reduce the number of rows included in later joins
Items INNER JOIN BlueItems ON Items.ItemID = BlueItems.ItemID AND BlueItems.shape = 'square'
LEFT JOIN ItemHistory ON Items.ItemID = ItemHistory.ItemsID
LEFT JOIN ItemDates ON Items.ItemID = ItemDates.ItemID
WHERE ItemDates.ManufactureDate BETWEEN '01/01/2017' AND '01/05/2017'
I figure that Inner Joining on Blue items that are squares vastly reduces the data set at this point?
I also understand that the Where clause is intelligent enough to reduce the data set on run time? Am I mistaken? Is it returning all the data and then just filtering on that data?
Any guidance on essentially how to speed this kind of query up would be fantastic, Index's and such have already been put in place. Unfortunately the database is actually looked after by someone else and I am simply creating reports based on their database. This does limit me to just being able to optimize my queries rather than the data itself.
I guess at this point its time for me to try and improve my knowledge on how SQL handles the various ways you can filter on data and try to understand which actually reduce the dataset used and which simply filter on it. Any guidance would be very appreciated!
You mentioned that the primary keys are all indexed, but this is always the case for primary key fields. The only portion of your current query which would possibly benefit from this is the first join with Items. For the other joins and the WHERE clause, these primary key fields are not being used.
For this particular query, I would suggest the following indices:
ALTER TABLE BlueItems ADD INDEX bi_item_idx (ItemID, shape)
ALTER TABLE ItemHistory ADD INDEX ih_item_idx (ItemID)
ALTER TABLE ItemDates ADD INDEX id_idx (ItemID, ManufactureDate)
For the ItemHistory table, the index ih_item_idx should speed up the join involving the ItemID foreign key. A column by the same name is also involved with the other two joins, and hence is part of the other indices. The reason for the composite indices (i.e. indices involving more than one column) is that we want to cover all the columns which appear in either the join or the WHERE clause.
These comments are not really an answer but too big to put in a comment...
IF the dates being passed in as parameters (i'm guessing they are) then it might be parameter sniffing that is causing the issue. The query may be using a bad plan.
I've seen this a lot especially when using the between operator. A few quick things to try as adding OPTION(RECOMPILE) to the end of your query. This might seem counter intuitive but just try it. Although compiled queries should be faster than recompiling, if a bad plan is being used, it can slow things down A LOT.
Also, If ItemDates is big, try dumping yuor filtered results to a temp table and joining to that, so something like.
SELECT * INTO #id FROM ItemDates i WHERE i.ManufactureDate BETWEEN '01/01/2017' AND '01/05/2017'
The change you main query to be something like
SELECT *
FROM Items
JOIN BlueItems ON Items.ItemID = BlueItems.ItemID AND BlueItems.shape = 'square'
JOIN #id i ON Items.ItemID = i.ItemID
LEFT JOIN ItemHistory ON Items.ItemID = ItemHistory.ItemsID
I also changed the JOIN from being a LEFT JOIN to a JOIN (implicitly an inner join) as you are only selecting items which have a match in ItemDates so LEFT joining makes no sense.
I have a search procedure which has to search in five tables for the same string. I wonder which is better regarding read performance?
To have all tables combined in one table, then add a full text index on it
To create full text indexes in all those tables and issue a query on all of them, then to combine the results
I think something to consider when working with performance, is that reading data is almost always faster than reading data, moving data and then reading again rather than just reading once.
So from your question if you are combining all the tables into a single say temporary table or table variable this will most definitely be slow because it has to query all that data and move it (depending on how much data you are working with this may or may not make much of a difference). As well regarding your table structure, indexing on strings only really becomes efficient when the same string shows up a number of times throughout the tables.
I.e. if you are searching on months (Jan, Feb, Mar, etc...) an index will be great because it can only be 1 of 12 options, and the more times a value is repeated/the less options there are to choose from the better an index is. Where if you are searching on say user entered values ("I am writing my life story....") and you are searching on a word inside that string, an index may not make any difference.
So assuming your query is searching on, in my example months, then you could do something like this:
SELECT value
FROM (
SELECT value FROM table1
UNION
SELECT value FROM table2
UNION
SELECT value FROM table3
UNION
SELECT value FROM table4
UNION
SELECT value FROM table5
) t
WHERE t.value = 'Jan'
This will combine your results into a single result set without moving data around. As well the interpreter will be able to find the most efficient way to query each table using the provided index on each table.
I'm trying to query two tables, ASSAYS, AND LITHO in a diamond drillhole database.
I was given values (SAMPLE_NO) to search for in the ASSAYS table, to return values such as HOLE-ID, FROM, and TO. So each sample that we take has a HOLE-ID, SAMPLE_NO, FROM AND TO. One hole-id can have multiple sample numbers, but each sample number is unique. The from and to will be unique in each hole-id. This I can find no problem.
My coworker also wanted to know what rock type was associated with each sample. This info is located in another table so I'll need to figure out how to query for this. The information that this table holds is HOLE-ID, FROM, TO, and ROCKTYPE.
You're looking for what is called a JOIN. This allows you to JOIN data of multiple tables based on matiching column values.
This could be your starting point:
SELECT a.*, l.*
FROM ASSAYS a LEFT JOIN LITHO l ON a.hole-id = l.hole-id
WHERE a.sample_no = 'XXXX'
Please google for JOIN and SQL to find out about the exact syntax.
are there some valid reasons, in a Oracle db, to preferring in a generic query, a filter condition expressed by a join table , instead of a filter with an IN condition with a large number of elements (some hundreds). I mean if you can write something like
SELECT .... FROM t1
WHERE t1. IN (......) with 100-200 items
or if it is better to change it with
SELECT .... FROM t1
JOIN t2 ON t1. = T2.
where the t2 table contains the values needed for the filter
many thanks
Thanks for the answers
I try to explain the situation and my doubt
I have an user interface where the user can choose in a control many items (for example one or more people a list of professionals).
I can use directly this list adding this in a IN condition, that is
SELECT .... FROM t1 WHERE t1. IN (p1... p200)
but this solution, could raise some problems:
- if the selected items are a lot, then the string can exceed a limit of sql string (I remember in Oracle existed a limit of 4000 bytes)
- an IN condition with many valuesmay be inefficient
So an alternative solution can be
1. create a temporary table with the selected item
2. using a join between the temparary table and the main table
Usually the filling of a temporary table is fast and my question is if this second solution is more efficient of the first
The two queries are not functionally equivalent, so the question is somewhat odd--I can't imagine this comes up very often (if ever).
That said, if you have a table that contains exactly the rows that need to be filtered, a JOIN would be a more natural/standard way to handle it.
Is the idea in the first example is to query t2 to get all the values, then add them to a collection and generate an IN clause? If so, I would say this would be a very bad practice.
From what I see, there are two different questions.
a) Using a Static List/table.
If the (100-200) item list is a list of static values, for eg.Let's say a list of Countries or currencies, I think it would be better to add this to a static table/parameter table and change the query to use the table instead. If you need to track a new code/country etc. later, all you need to do later is insert a new code in the look up table.
Also, if there are other queries that use the same conditions (and there usually are), this look up table will promote re-use.
select * from t1 where id in (select id from t2);
and
select * from t1,t2
where t1.id = t2.id
are both equivalent and better than
select * from t1 where
id in ('USD','EUR'..... ); -- 100 to 200 items to track.
b) The choice of Join vs IN:
It really does not matter a lot. The final query that oracle executes will be the transformed version of your query which might evaluate to the same query in both cases.
You should see which of the two queries are more easier to read and convey the intentions correctly.
Useful Link : http://explainextended.com/2009/09/30/in-vs-join-vs-exists-oracle/
http://explainextended.com/2009/09/30/in-vs-join-vs-exists-oracle/