How do I check if an index already on SQL server if the index has 2 or more columns?
I don't want to check for name only I want to check by table by columns
Any help would be appreciated.
Your question is a little vague, but if I understand correctly, you want to find indexes on all tables where the index has two or more columns:
select t.[name] TableName, i.[name] IndexName
from (
select object_id, Index_Id
from sys.index_columns
group by object_Id, Index_Id
having Count(*)>1
)x
join sys.indexes i on i.index_id=x.index_id and i.object_id=x.object_id
join sys.tables t on t.object_id=x.object_id and t.[type]='U'
order by Tablename, IndexName
Related
I've a problem to in building a query for Python SQLite3 to do the following:
Count a word which appears in columns, if word appears more than 1 time count one.
I've attached a picture to illustrate my table format.
I tried this but the result still counts duplicate values with same ID.
"SELECT id, value, count(value) FROM table WHERE type like'%hi%' GROUP BY value ORDER BY COUNT(*)<1 DESC"
The result needs to be like:
Hi all you need can be achieved with GROUP BY clause.
This should help:
SELECT
id
,value
,1 AS cnt
FROM table
GROUP BY id, value
ORDER BY id
What you're looking for is DISTINCT clause or GROUP BY as mentioned by Peter.
for GROUP BY use this syntax:
SELECT
id
,value
,1 AS cnt
FROM table
GROUP BY id, value
for DISTINCT use this one:
SELECT DISTINCT
id
,value
,1 AS cnt
FROM table
I'm trying to join two tables in spark sql. Each table has 50+ columns. Both has column id as the key.
spark.sql("select * from tbl1 join tbl2 on tbl1.id = tbl2.id")
The joined table has duplicated id column.
We can of course specify which id column to keep like below:
spark.sql("select tbl1.id, .....from tbl1 join tbl2 on tbl1.id = tbl2.id")
But since we have so many columns in both tables, I do not want to type all the other column names in the query above. (other than id column, no other duplicated column names).
what should I do? thanks.
If id is the only column name in common, you can take advantage of the USING clause:
spark.sql("select * from tbl1 join tbl2 using (id) ")
The using clause matches columns that have the same name in both tables. When using select *, the column appears only once.
Assuming, you want to preserve the "duplicates", you can try to use the internal row-id or equivalents for your help. This helped me in the past, if I had to delete exactly one of two identical rows.
select *,ctid from table;
outputs in postgresql also the internal counter id. Your before exact identical rows become different now. I don't know about spark.sql, but I assume, that you can access a similar attribute there.
val joined = spark
.sql("select * from tbl1")
.join(
spark.sql("select * from tbl2"),
Seq("id"),
"inner" // optional
)
joined should have only one id column. Tested with Spark 2.4.8
Table A having 20 records and table B showing 19 records. How to find that one record is which is missing in table B. How to do compare/subtract records of these two tables; to find that one record. Running query in Apache Superset.
The exact answer depends on which column(s) define whether two records are the same. Assuming you wanted to use some primary key column for the comparison, you could try:
SELECT a.*
FROM TableA a
WHERE NOT EXISTS (SELECT 1 FROM TableB b WHERE b.pk = a.pk);
If you wanted to use more than one column to compare records from the two tables, then you would just add logic to the exists clause, e.g. for three columns:
WHERE NOT EXISTS (SELECT 1 FROM TableB b WHERE b.col1 = a.col1 AND
b.col2 = a.col2 AND
b.col3 = a.col3)
I am trying to do a left join on my main table using this code
select distinct VBen.BENF_NO_INDIV_BEN_BANLS as benbanls,
VBen.BENF_COD_SEXE AS Sexe,
VBen.BENF_DAT_NAISS AS DatNaiss,
VBen.BENF_DAT_DECES AS DatDec,
A.date_ch as date_chsld
from PROD.V_FICH_ID_BEN_CM AS VBen
left join (select distinct VAss.BENF_NO_INDIV_BEN_BANLS as benbanls,
vass.BENF_DD_ADMIS_ASSU_MED as date_ch
from Prod.V_ADMIS_ASSU_MED_PLAN_PRIOR_CM as vass ) as A
on VBen.BENF_NO_INDIV_BEN_BANLS =A. benbanls
where Vben.BENF_DAT_NAISS>'2016-04-01' or Vben.BENF_DAT_DECES>'2011-04-01'
The problem is that the query result is a table with of number of rows greater than the main table with the same where 'condition'. I don't understand what I am missing
Thanks for your help
Why is it a problem?
The results simply indicate you have a 1:M (one to many) relationship between VBen:Vass(A)
If you don't have a 1:M relationship and it should be 1:1 then...
you're missing join criteria between the tables.
you should be getting a min/max on your date instead of all dates per benbanls
To better understand and answer we would need to know what VBen and Vass actually represent; but to put simply, you have multiple VASS(A) per VBEN
To illustrate with an example: Think about Order_Header and Order_Line tables...
Order_header contains (order_Number PK)
Order_line contains (Order_Number, Order_Line PK)
An order can have multiple lines, each line could have it's own ship date several items may have gone out on the same shipment/day. where some that were backordered went out on a different day. In this situation, an order would still have multiple lines even though we distinct order_number and shipmentdate in a subquery. I would guess your situation is similar.
so 1 in base table * 2 rows in derived/lines table gives us 2 records
1 < 2 which is the situation you have now; and that to me is perfectly fine and expected if it's a 1:M relationship.
Maybe you need to do a min or max on date instead of a distinct?
If not you're missing join criteria to make a 1:1 relationship
maybe your expectation is just flawed.
The below will give you a 1:1 relationship but I'm not sure it's what you're after.
SELECT distinct VBen.BENF_NO_INDIV_BEN_BANLS as benbanls,
VBen.BENF_COD_SEXE AS Sexe,
VBen.BENF_DAT_NAISS AS DatNaiss,
VBen.BENF_DAT_DECES AS DatDec,
A.date_ch as date_chsld
FROM PROD.V_FICH_ID_BEN_CM AS VBen
LEFT JOIN (SELECT VAss.BENF_NO_INDIV_BEN_BANLS as benbanls,
Max(vass.BENF_DD_ADMIS_ASSU_MED) as date_ch
FROM Prod.V_ADMIS_ASSU_MED_PLAN_PRIOR_CM as vass
GROUP BY VAss.BENF_NO_INDIV_BEN_BANLS) as A
on VBen.BENF_NO_INDIV_BEN_BANLS = A. benbanls
WHERE (Vben.BENF_DAT_NAISS>'2016-04-01'
or Vben.BENF_DAT_DECES>'2011-04-01)
It is likely that there is more than one counterpart in the detail table of a record on the main table.
I try your scenario on my db get a correct result.
In my DB:
select distinct p.PollId as PollId,
p.Title AS Title,
p.InsertDate AS DatDec,
ps.date_ch as date_chsld
from dbo.Poll AS p
left join (select distinct pSt.PollId as pollId,
Max(pSt.InsertDate) as date_ch
from dbo.PollStore as pSt
Group by pSt.PollId ) as ps
on p.PollId =ps.pollId
As Your Query like this :
select distinct VBen.BENF_NO_INDIV_BEN_BANLS as benbanls,
VBen.BENF_COD_SEXE AS Sexe,
VBen.BENF_DAT_NAISS AS DatNaiss,
VBen.BENF_DAT_DECES AS DatDec,
A.date_ch as date_chsld
please try this query
from PROD.V_FICH_ID_BEN_CM AS VBen
left join (select distinct VAss.BENF_NO_INDIV_BEN_BANLS as benbanls,
Max(vass.BENF_DD_ADMIS_ASSU_MED) as date_ch
from Prod.V_ADMIS_ASSU_MED_PLAN_PRIOR_CM Group by VAss.BENF_NO_INDIV_BEN_BANLS as vass ) as A
on VBen.BENF_NO_INDIV_BEN_BANLS =A. benbanls
where Vben.BENF_DAT_NAISS>'2016-04-01' or Vben.BENF_DAT_DECES>'2011-04-01'
This is not a question asking how to delete all data for a table.
That's what TRUNCATE does.
I want to delete all rows for a specific column at once in cassandra.
I can delete only one row for a specific column using DELETE or UPDATE like the follows.
DELETE column_name FROM table_name WHERE primary_key = value_of_primary_key;
or
UPDATE table_name SET column_name = null WHERE primary_key = value_of_primary_key;
However, what I want to do is like the follows.
TRUNCATE key_name.table_name.column_name;
The above TRUNCATE code doesn't work since it doesn't take column_name, but I hope you understand what I want to do.
Is it possible to delete all rows for a specific column at once?
If so, how can I do that?
If not, what is the best workaround for this?
Try Drop the column and Add the column again.
Example :
ALTER TABLE table_name DROP column_name;
ALTER TABLE table_name ADD column_name text;