Detect all columns in an oracle table which have the same value in each row - sql

Question

Every day, the requests get weirder and weirder.
I have been asked to put together a query to detect which columns in a table contain the same value for all rows. I said "That needs to be done by program, so that we can do it in one pass of the table instead of N passes."
I have been overruled.
So long story short. I have this very simple query which demonstrates the problem. It makes 4 passes over the test set. I am looking for ideas for SQL Magery which do not involve adding indexes on every column, or writing a program, or taking a full human lifetime to run.
And sigh It needs to be able to work on any table.
Thanks in advance for your suggestions.
WITH TEST_CASE AS
(
SELECT 'X' A, 5 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 3 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 7 B, 'TUE' C, NULL D FROM DUAL
),
KOUNTS AS
(
SELECT SQRT(COUNT(*)) S, 'Column A' COLUMNS_WITH_SINGLE_VALUES
FROM TEST_CASE P, TEST_CASE Q
WHERE P.A = Q.A OR (P.A IS NULL AND Q.A IS NULL)
UNION ALL
SELECT SQRT(COUNT(*)) S, 'Column B' COLUMNS_WITH_SINGLE_VALUES
FROM TEST_CASE P, TEST_CASE Q
WHERE P.B = Q.B OR (P.B IS NULL AND Q.B IS NULL)
UNION ALL
SELECT SQRT(COUNT(*)) S, 'Column C' COLUMNS_WITH_SINGLE_VALUES
FROM TEST_CASE P, TEST_CASE Q
WHERE P.C = Q.C OR (P.C IS NULL AND Q.C IS NULL)
UNION ALL
SELECT SQRT(COUNT(*)) S, 'Column D' COLUMNS_WITH_SINGLE_VALUES
FROM TEST_CASE P, TEST_CASE Q
WHERE P.D = Q.D OR (P.D IS NULL AND Q.D IS NULL)
)
SELECT COLUMNS_WITH_SINGLE_VALUES
FROM KOUNTS
WHERE S = (SELECT COUNT(*) FROM TEST_CASE)

Answer 1

do you mean something like this?
WITH
TEST_CASE AS
(
SELECT 'X' A, 5 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 3 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 7 B, 'TUE' C, NULL D FROM DUAL
)
select case when min(A) = max(A) THEN 'A'
when min(B) = max(B) THEN 'B'
when min(C) = max(C) THEN 'C'
when min(D) = max(D) THEN 'D'
else 'No one'
end
from TEST_CASE
Edit
this works:
WITH
TEST_CASE AS
(
SELECT 'X' A, 5 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 3 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 7 B, 'TUE' C, NULL D FROM DUAL
)
select case when min(nvl(A,0)) = max(nvl(A,0)) THEN 'A ' end ||
case when min(nvl(B,0)) = max(nvl(B,0)) THEN 'B ' end ||
case when min(nvl(C,0)) = max(nvl(C,0)) THEN 'C ' end ||
case when min(nvl(D,0)) = max(nvl(D,0)) THEN 'D ' end c
from TEST_CASE
Bonus: I have also added the check for the null values, so the result now is: A and D
And the SQLFiddle demo for you.

Answer 2

Optimizer statistics can easily identify columns with more than one distinct value. After statistics are gathered a simple query against the data dictionary will return the results almost instantly.
The results will only be accurate on 10g if you use ESTIMATE_PERCENT = 100. The results will be accurate on 11g+ if you use ESTIMATE_PERCENT = 100 or AUTO_SAMPLE_SIZE.
Code
create table test_case(a varchar2(1), b number, c varchar2(3),d number,e number);
--I added a new test case, E. E has null and not-null values.
--This is a useful test because null and not-null values are counted separately.
insert into test_case
SELECT 'X' A, 5 B, 'FRI' C, NULL D, NULL E FROM DUAL UNION ALL
SELECT 'X' A, 3 B, 'FRI' C, NULL D, NULL E FROM DUAL UNION ALL
SELECT 'X' A, 7 B, 'TUE' C, NULL D, 1 E FROM DUAL;
--Gather stats with default settings, which uses AUTO_SAMPLE_SIZE.
--One advantage of this method is that you can quickly get information for many
--tables at one time.
begin
dbms_stats.gather_schema_stats(user);
end;
/
--All columns with more than one distinct value.
--Note that nulls and not-nulls are counted differently.
--Not-nulls are counted distinctly, nulls are counted total.
select owner, table_name, column_name
from dba_tab_columns
where owner = user
and num_distinct + least(num_nulls, 1) <= 1
order by column_name;
OWNER TABLE_NAME COLUMN_NAME
------- ---------- -----------
JHELLER TEST_CASE A
JHELLER TEST_CASE D
Performance
On 11g, this method might be about as fast as mucio's SQL statement. Options like cascade => false would improve performance by not analyzing indexes.
But the great thing about this method is that it also produces useful statistics. If the system is already gathering statistics at regular intervals the hard work may already be done.
Details about AUTO_SAMPLE_SIZE algorithm
AUTO_SAMPLE_SIZE was completely changed in 11g. It does not use sampling for estimating number of distinct values (NDV). Instead it scans the whole table and uses a hash-based distinct algorithm. This algorithm does not require large amounts of memory or temporary tablespace. It's much faster to read the whole table than to sort even a small part of it. The Oracle Optimizer blog has a good description of the algorithm here. For even more details, see this presentation by Amit Podder. (You'll want to scan through that PDF if you want to verify the details in my next section.)
Possibility of a wrong result
Although the new algorithm does not use a simple sampling algorithm it still does not count the number of distinct values 100% correctly. It's easy to find cases where the estimated number of distinct values is not the same as the actual. But if the number of distinct values are clearly inaccurate, how can they be trusted in this solution?
The potential inaccuracy comes from two sources - hash collisions and synopsis splitting. Synopsis splitting is the main source of inaccuracy but does not apply here. It only happens when there are 13864 distinct values. And it never throws out all of the values, the final estimate will certainly be much larger than 1.
The only real concern is what are the chances of there being 2 distinct values with a hash collision. With a 64-bit hash the chance could be as low as 1 in 18,446,744,073,709,551,616. Unfortunately I don't know the details of their hashing algorithm and don't know the real probability. I was unable to produce any collisions from some simple testing and from previous real-life tests. (One of my tests was to use large values, since some statistics operations only use the first N bytes of data.)
Now also consider that this will only happen if all of the distinct values in the table collide. What are the chances of there being a table with only two values that just happen to collide? Probably much less than the chance of winning the lottery and getting struck by a meteorite at the same time.

Answer 3

If you can live with the result on a single line, this should only scan once;
WITH TEST_CASE AS
(
SELECT 'X' A, 5 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 3 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 7 B, 'TUE' C, NULL D FROM DUAL
)
SELECT
CASE WHEN COUNT(DISTINCT A) +
COUNT(DISTINCT CASE WHEN A IS NULL THEN 1 END) = 1
THEN 1 ELSE 0 END SAME_A,
CASE WHEN COUNT(DISTINCT B) +
COUNT(DISTINCT CASE WHEN B IS NULL THEN 1 END) = 1
THEN 1 ELSE 0 END SAME_B,
CASE WHEN COUNT(DISTINCT C) +
COUNT(DISTINCT CASE WHEN C IS NULL THEN 1 END) = 1
THEN 1 ELSE 0 END SAME_C,
CASE WHEN COUNT(DISTINCT D) +
COUNT(DISTINCT CASE WHEN D IS NULL THEN 1 END) = 1
THEN 1 ELSE 0 END SAME_D
FROM TEST_CASE
An SQLfiddle to test with.

Answer 4

this will be done in a single scan
WITH
TEST_CASE AS
(
SELECT 'X' A, 5 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 3 B, 'FRI' C, NULL D FROM DUAL UNION ALL
SELECT 'X' A, 7 B, 'TUE' C, NULL D FROM DUAL
)
select decode(count(distinct nvl(A,0)),1,'SINGLE','MULTP') COL_A,
decode(count(distinct nvl(B,0)),1,'SINGLE','MULTP') COL_B,
decode(count(distinct nvl(C,0)),1,'SINGLE','MULTP') COL_C,
decode(count(distinct nvl(D,0)),1,'SINGLE','MULTP') COL_D
from TEST_CASE