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copied!<p>Here's what I'm thinking, but I'm not sure it's optimal enough for a view.</p> <pre><code>select the_date, sum(decode(the_type,'S',the_count,0)) samples, sum(decode(the_type,'R',the_count,0)) receipts, sum(decode(the_type,'C',the_count,0)) completions, sum(decode(the_type,'A',the_count,0)) authorizations from( select trunc(sampled_on,'HH24') the_date, 'S' the_type, count(1) the_count FROM sample group by trunc(sampled_on,'HH24') union all select trunc(received_on,'HH24'), 'R', count(1) FROM sample group by trunc(received_on,'HH24') union all select trunc(completed_on,'HH24'), 'C', count(1) FROM sample group by trunc(completed_on,'HH24') union all select trunc(authorized_on,'HH24'), 'A', count(1) FROM sample group by trunc(authorized_on,'HH24') ) group by the_date </code></pre> <p>Then, to query, you could just query with normal date contructs: </p> <pre><code>select * from magic_view where the_date > sysdate-1; </code></pre> <h2>EDIT</h2> <p>Okay, so I created a sample table and did some metrics:</p> <pre><code>create table sample ( sample_id number primary key, sampled_on date, received_on date, completed_on date, authorized_on date ); insert into sample ( select level, trunc(sysdate) + dbms_random.value(0,2), trunc(sysdate) + dbms_random.value(0,2), trunc(sysdate) + dbms_random.value(0,2), trunc(sysdate) + dbms_random.value(0,2), from dual connect by level <= 1000 ); </code></pre> <p>The explain plan is:</p> <pre><code>--------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| --------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4000 | 97K| 25 (20)| | 1 | HASH GROUP BY | | 4000 | 97K| 25 (20)| | 2 | VIEW | | 4000 | 97K| 24 (17)| | 3 | UNION-ALL | | | | | | 4 | HASH GROUP BY | | 1000 | 9000 | 6 (17)| | 5 | TABLE ACCESS FULL| SAMPLE | 1000 | 9000 | 5 (0)| | 6 | HASH GROUP BY | | 1000 | 9000 | 6 (17)| | 7 | TABLE ACCESS FULL| SAMPLE | 1000 | 9000 | 5 (0)| | 8 | HASH GROUP BY | | 1000 | 9000 | 6 (17)| | 9 | TABLE ACCESS FULL| SAMPLE | 1000 | 9000 | 5 (0)| | 10 | HASH GROUP BY | | 1000 | 9000 | 6 (17)| | 11 | TABLE ACCESS FULL| SAMPLE | 1000 | 9000 | 5 (0)| --------------------------------------------------------------------- </code></pre> <p>On my machine, the a query against this view for the past 24 hours completes in 23ms. Not bad, but it's only 1,000 rows. Before you discount the 4 separate queries, you'll need to do performance analysis of the individual solutions.</p>

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