I am running a CREATE TABLE TBL AS SELECT statement as below. I want to write a CASE STATEMENT that will compare
values from column X.PRESC_ID to values from column Y.PRSC_NPI and if there is match, it should INSERT to TBL.PRESC_ID,
and for all the X.PRESC_ID that do not match with any value in Y.PRSC_NPI should be INSERTED to TBL.PRSC_NPI_N
CREATE TABLE TBL (
Col1,
Col2,
PRESC_ID,
PRSC_NPI_N,
AS
(
SELECT
Col1,
Col2,
PRESC_ID,
PRSC_NPI_N,
FROM TBL2 X
JOIN
(SELECT CLAIM_ID,PRSC_NPI FROM TBL3) Y
ON Y.CLAIM_ID = Y.Col1
I have tried the one below but it is not working
CASE
WHEN X.PRESC_ID = Y.PRSC_NPI THEN TBL.PRESC_ID
ELSE TBL.PRSC_NPI_N
END
Seems you really want two CASE expressions, one for each result column. Something like
CASE WHEN X.PRESC_ID = Y.PRSC_NPI THEN X.PRESC_ID END AS PRESC_ID,
CASE WHEN NOT(X.PRESC_ID = Y.PRSC_NPI) THEN X.PRSC_NPI_N END AS PRSC_NPI_N
Related
I did find some examples but they do not merge into single column.
So, I am trying to join 2 table columns data into single column
I have Url1, site1, url2, site2, endurl 5 columns in table1
and keywords column in table2
I want to join or merge these columns into one column like
url1 site1 keywords,url2 site2 keywords endurl this will convert to a url generation just for understanding.
I tried
SELECT table1.Url1, table1.site1, table1.url2, table1.site2, table1.endurl, table2.keywords
FROM table1
LEFT JOIN table2
ON table1.site1 = table2.keywords AND table1.site2 = table2.keywords;
want to merge all columns into single column.
What you're probably looking for is the format function which uses SQLite's builtin printf implementation. So, assuming your columns are all TEXT columns, this will give you what you're looking for:
SELECT format('%s, %s, %s, %s, %s, %s', table1.Url1, table1.site1, table1.url2, table1.site2, table1.endurl, table2.keywords) as my_column
FROM table1
LEFT JOIN table2
ON table1.site1 = table2.keywords AND table1.site2 = table2.keywords;
You could probably concat those columns into one.
Edit: Now for SQLite
SELECT t1.Url1 || ' ' || t1.site1 || ' ' || t2.keywords ||',' ||t1.url2||' '||t1.site2||' '||t3.keywords as column_name
FROM table1 t1, table2 t2, table2 t3
WHERE t1.site1 = t2.keywords AND t1.site2 = t3.keywords;
select m.value
from MY_TABLE m
where m.value in (select m2.some_third_value, m2.some_fourth_value
from MY_TABLE_2 m2
where m2.first_val member of v_my_array
or m2.second_val member of v_my_array_2)
Is it possible to write a select similar to this, where m.value is compared to two columns and has to match at least one of those? Something like where m.value in (select m2.first_val, m2.second_val). Or is writing two separate selects unavoidable here?
No. When there are multiple columns in the IN clause, there must be the same number of columns in the WHERE clause. The pairwise query compares each record in the WHERE clause against the records returned by the sub-query. The statement below
SELECT *
FROM table_main m
WHERE ( m.col_1, m.col_2 ) IN (SELECT s.col_a,
s.col_b
FROM table_sub s)
is equivalent to
SELECT *
FROM table_main m
WHERE EXISTS (SELECT 1
FROM table_sub s
WHERE m.col_1 = s.col_a
AND m.col_2 = s.col_b)
The only way to search both columns in one SELECT statement would be to OUTER JOIN the second table to the first table.
SELECT m.*
FROM table_main m
LEFT JOIN table_sub s ON (m.col_1 = s.col_a OR m.col_1 = s.col_b)
WHERE m.col_1 = s.col_a
OR m.col_1 = s.col_b
I have a table with more than 15 columns. 2 of of them are of the type varchar, and most of them of type int and float.
I am new to SQL and am trying to figure out a way by which I can check if any of the columns have a NULL value in it.
Had there been just 4 or 5 columns I could have checked them individually with
SELECT COUNT(*) FROM table_name WHERE col1 IS NULL OR col2 IS NULL OR col3 IS NULL ...
But is there any efficient way to do this on a lot of columns in SQLite specifically?
I have referred to other questions regarding this here but I cannot use xml or store anything. Also I am using SQLite and can only run a query.
There is no way (that I know of) to check all columns if they contain null without explicitly listing all the column names.
Your query is the proper way to do it.
If you want to shorten (not significantly) the code you could use these alternatives:
SELECT COUNT(*) FROM table_name WHERE col1 + col2 + col3 IS NULL;
or:
SELECT COUNT(*) FROM table_name WHERE col1 || col2 || col3 IS NULL;
or:
SELECT COUNT(*) FROM table_name WHERE MAX(col1, col2, col3) IS NULL;
The above queries work, for any data type of the columns, because if there is even only 1 column equal to null then addition, concatenation and the scalar function MAX() (and MIN()) all return null.
See the demo.
I have a oracle query
select id from (
select ID, ROW_NUMBER() over (partition by LATEST_RECEIPT order by ID) rownumber
from Table
where LATEST_RECEIPT in
(
select LATEST_RECEIPT from Table
group by LATEST_RECEIPT
having COUNT(1) > 1
)
) t
where rownumber <> 1;
The data type of LATEST_RECEIPT was earlier varchar2(4000) and this query worked fine. Since the length of the column needs to be extended i modified it to CLOB, after which this fails. Could anyone help me fix this issue or provide a work around?
You can change your inner query to look for other rows with the same last_receipt value but a different ID (assuming ID is unique); if another row exists then that is equivalent to your count returning greater than one. But you can't simply test two CLOB values for equality, you need to use dbms_lob.compare:
select ID
from your_table t1
where exists (
select null from your_table t2
where dbms_lob.compare(t2.LATEST_RECEIPT, t1.LATEST_RECEIPT) = 0
and t2.ID != t1.ID
-- or if ID isn't unique: and t2.ROWID != t1.ROWID
);
Applying the row number filter is tricker, as you also can't use a CLOB in the analytic partition by clause. As André Schild suggested, you can use a hash; here passing the integer value 3, which is the equivalent of dbms_crypto.hash_sh1 (though in theory that could change in a future release!):
select id from (
select ID, ROW_NUMBER() over (partition by dbms_crypto.hash(LATEST_RECEIPT, 3)
order by ID) rownumber
from your_table t1
where exists (
select null from your_table t2
where dbms_lob.compare(t2.LATEST_RECEIPT, t1.LATEST_RECEIPT) = 0
and t2.ID != t1.ID
-- or if ID isn't unique: and t2.ROWID != t1.ROWID
)
)
where rownumber > 1;
It is of course possible to get a hash collision, and if that happened - you had two latest_receipt values which both appeared more than once and both hashed to the same value - then you could get too many rows back. That seems pretty unlikely, but it's something to consider.
So rather than ordering you can only look for rows which have the same lastest_receipt and a lower ID:
select ID
from your_table t1
where exists (
select null from your_table t2
where dbms_lob.compare(t2.LATEST_RECEIPT, t1.LATEST_RECEIPT) = 0
and t2.ID < t1.ID
);
Again that assumes ID is unique. If it isn't then you could still use rowid instead, but you would have less control over which rows were found - the lowest rowid isn't necessarily the lowest ID. Presumably you're using this to dine rows to delete. If you actually don't mind which row you keep and which you delete then you could still do:
and t2.ROWID < t1.ROWID
But since you are currently ordering that probably isn't acceptable, and hashing might be preferable, despite the small risk.
I have 2 tables with 150 columns and trying to join those tables and fetch the result set one by one and process them:
qry = '''select a.*, b.*
from table_a a
full outer join table_b b
where a.id = b.id'''
table_row = conn.execute(qry) #execute method yields a generator
Now, I need to access the resultset which is generator and determine the values of each and every column of table-1 & table-2
For example:- if table-1 & table-2 has a column named name, I need to compare it..
How can I access the resultset by columnnname, im using Pyodbc,
ie resultset.table1.name = resultset.table2.name
Use the ISO information schema views (I'm using SQL Server in the
example) to return column names for each table, substituting
database and schema parameters values as appropriate.
Merge the resulting lists into a set containing column names present in both tables.
Use this set to build a string representing column names to select from each table, aliasing each column by prefixing with a table name. Defining column aliases will allow you to differentiate columns by table.
Execute select query and print values for comparison.
Code sample
# assumes connection, cursor already setup
# build SQL for retrieving column names
sql = '''SELECT COLUMN_NAME
FROM INFORMATION_SCHEMA.COLUMN
WHERE TABLE_CATALOG = ? AND TABLE_SCHEMA = ?
AND TABLE_NAME = ?'''
# get column names from table_a
rows = cursor.execute(sql, ('database', 'schema', 'table_a')).fetchall()
table_a_columns = [column[0] for column in rows]
# get column names from table_b
rows = cursor_b.execute(sql, ('database', 'schema', 'table_b')).fetchall()
table_b_columns = [column[0] for column in rows]
# get unique matching columns from lists
matches = set(table_a_columns).intersection(table_b_columns)
# get string of column names to use in query, setting column alias prefixed with
# table name for each column
column_alias = 'a.{0} as a_{0}, b.{0} as b_{0}'
columns = ', '.join([column_alias.format(column) for column in matches])
sql = 'SELECT {} FROM table_a a FULL OUTER JOIN table_b b ON a.id = b.id'
sql = sql.format(columns)
# print values to compare
for row in cursor.execute(sql):
print row
There's probably a less complicated way, but it's eluding me.