although i selected Full Join, i couldn't get the all rows from both tables.
how can i get all rows from both tables ? (all 12093 rows)
maybe another join type may help ?
let
Source = Table.NestedJoin(#"Beton Irsaliye Kumulatif",{"Proje No & Adi", "Firma Kodu"},#"Beton Muhasebe Kumulatif",{"Proje No & Adi", "Hesap No"},"Beton Muhasebe Kumulatif",JoinKind.FullOuter)
in
Source
Your merge is accounting for all your rows. It's just that 4 of the rows in the first table don't have matches in the second table.
Here's a simple example of what is happening. Here, I have two tables: Table1 and Table2. Both have 10 rows. In fact, both are exactly the same.
If I choose to do a Full Outer join with these, using Col1 and Col2 for matching, I'll see this:
It tells me that 10 of the rows from the first table (Table1) match rows of the second table (Table2).
Now, if I change the last two rows of Table1 (specifically, the last two rows of Col2 of Table1) like this:
Then when I try to do a Full Outer join the same way, I'll see this:
Only 8 of the rows from the first table (Table1) match rows of the second table (Table2).
But when I continue with the merge, I'll see Table1's information in a table with Table2's matching information as embedded tables in column "NewColumn" of that table:
When I then expand "NewColumn", I see all the info from Table1, as before, and all matching info from Table2, as well as rows that don't have matches between the two tables.
All rows of both tables are accounted for.
I have two postgres tables where one column listing a city name matches. I'm trying to create a view of some records which I'm displaying on a map via WMS on my GeoServer.
I need to select only records from table1 of 100k records that has a city name that matches those cities listed in table2 of 20 records.
To list everything I've tried would be a waste of your time. I've tried every join tutorial and example but, am perplexed why I can't get any success. I would really appreciate some direction.
Here's a latest query but, if this is the wrong approach just ignore since I have about 50 similar attempts.
SELECT t1.id,
t1.dba,
t1.prem_city,
t1.geom
t2.city_label
FROM schema1.table1 AS t1
LEFT JOIN schema2.table2 AS t2
ON t2.city_label = t1.prem_city;
Thanks for any help!
Your query seems correct, just a minor change - LEFT JOIN keeps all the records from the left table and only the matching record from the right one. If you want only those that appear in both - an INNER JOIN is required .
SELECT t1.id,
t1.dba,
t1.prem_city,
t1.geom,
t2.city_label
FROM schema1.table1 t1
JOIN schema2.table2 t2
ON t2.city_label = t1.prem_city;
Example scenario:
TABLE_A contains a column called ID and also contains duplicate rows. There is another table called ID_TABLE that contains IDs. Assuming no duplicates in ID_TABLE -
If I do:
SELECT * FROM TABLE_A
INNER JOIN ID_TABLE ON ID_TABLE.ID = TABLE_A.ID
There will be duplicates in the result set. However, if I do:
SELECT * FROM TABLE_A
WHERE TABLE_A.ID IN (SELECT ID_TABLE.ID FROM ID_TABLE)
There will not be any duplicates in the result set.
Does anyone know why the JOIN clause allows duplicates while the IN clause does not? I had thought they did the same thing.
Thanks
It's not that it's allowing duplicates. By joining the two tables, you are creating a product from table 1 and table 2, so if TABLE_A has two records for ID=1 and ID_Table has 1 record, the resulting product is two records. Using IN doesn't cause a multiplication of records, even if the value is listed in the IN clause multiple times as you are only getting the unique records matching the values within the IN clause.
I am running Postgres 9.1.3 32-bit on Windows 7 x64. (Have to use 32 bit because there is no Windows PostGIS release compatible with 64 bit Postgres.) (EDIT: As of PostGIS 2.0, it is compatible with Postgres 64 bit on windows.)
I have a query that left joins a table (consistent.master) with a temporary table, then inserts the resulting data into a third table (consistent.masternew).
Since this is a left join, the resulting table should have the same number of rows as the left table in the query. However, if I run this:
SELECT count(*)
FROM consistent.master
I get 2085343. But if I run this:
SELECT count(*)
FROM consistent.masternew
I get 2085703.
How can masternew have more rows than master? Shouldn't masternew have the same number of rows as master, the left table in the query?
Below is the query. The master and masternew tables should be identically-structured.
--temporary table created here
--I am trying to locate where multiple tickets were written on
--a single traffic stop
WITH stops AS (
SELECT citation_id,
rank() OVER (ORDER BY offense_timestamp,
defendant_dl,
offense_street_number,
offense_street_name) AS stop
FROM consistent.master
WHERE citing_jurisdiction=1
)
--Here's the insert statement. Below you'll see it's
--pulling data from a select query
INSERT INTO consistent.masternew (arrest_id,
citation_id,
defendant_dl,
defendant_dl_state,
defendant_zip,
defendant_race,
defendant_sex,
defendant_dob,
vehicle_licenseplate,
vehicle_licenseplate_state,
vehicle_registration_expiration_date,
vehicle_year,
vehicle_make,
vehicle_model,
vehicle_color,
offense_timestamp,
offense_street_number,
offense_street_name,
offense_crossstreet_number,
offense_crossstreet_name,
offense_county,
officer_id,
offense_code,
speed_alleged,
speed_limit,
work_zone,
school_zone,
offense_location,
source,
citing_jurisdiction,
the_geom)
--Here's the select query that the insert statement is using.
SELECT stops.stop,
master.citation_id,
defendant_dl,
defendant_dl_state,
defendant_zip,
defendant_race,
defendant_sex,
defendant_dob,
vehicle_licenseplate,
vehicle_licenseplate_state,
vehicle_registration_expiration_date,
vehicle_year,
vehicle_make,
vehicle_model,
vehicle_color,
offense_timestamp,
offense_street_number,
offense_street_name,
offense_crossstreet_number,
offense_crossstreet_name,
offense_county,
officer_id,
offense_code,
speed_alleged,
speed_limit,
work_zone,
school_zone,
offense_location,
source,
citing_jurisdiction,
the_geom
FROM consistent.master LEFT JOIN stops
ON stops.citation_id = master.citation_id
In case it matters, I have run a VACUUM FULL ANALYZE and reindexed both tables. (Not sure of exact commands; did it through pgAdmin III.)
A left join does not necessarily have the same number of rows as the number of rows in the left table. Basically, it is like a normal join, except rows of the left table that would not appear in the normal join are also added. So, if you have more than one row in the right table that matches one row in the left table, you can have more rows in your results than the number of rows of the left table.
In order to do what you want to do, you should use a group by, and a count to detect multiples.
select citation_id
from stops join master on stops.citation_id = master.citation_id
group by citation_id
having count(*) > 1
Sometimes you know there are multiples, but don't care. You just want to take the first or top entry.
If so, you can use SELECT DISTINCT ON:
FROM consistent.master LEFT JOIN (SELECT DISTINCT ON (citation_id) * FROM stops) s
ON s.citation_id = master.citation_id
Where citation_id is the column that you want to take the first (any) row for each match.
You might want to ensure this is deterministic and use ORDER BY with some other orderable column:
SELECT DISTINCT ON (citation_id) * FROM stops ORDER BY citation_id, created_at
I am developing a t-sql query to return left join of two tables, but when I just select records from Table A, it gives me only 2 records. The problem though is when I left join it Table B, it gives me 4 records. How can I reduce this to just 2 records?
One problem though is that I am only aware of one PK/FK to link these two tables.
The field you are using for the join must exist more than once in table B - this is why multiple rows are being returned in the join. In order to reduce the row count you will have to either add further fields to the join, or add a where clause to filter out rows not required.
Alternatively you could use a GROUP BY statement to group the rows up, but this may not be what you need.
Remember that the left join brings you null fields from joined table.
Also you can use select(distinct), but i can't see well you issue. Can you give us more details?