Identifying the Source of an Oracle SQL Query Issue
Introduction
As a technical blogger, I’ve encountered numerous questions from readers struggling with various aspects of database queries. In this article, we’ll focus on identifying the source of an issue in an Oracle SQL query. We’ll explore the use of subqueries, partitioning, and indexing to optimize performance.
The question at hand revolves around a complex Oracle SQL query that has been causing issues on one DB but works fine on another. The query is nested and uses multiple joins, making it challenging to identify the source of the problem.
Understanding the Query
To begin with, let’s break down the provided query:
WITH dataset AS
(SELECT
COLLECTION_TIMESTAMP,
TARGET_NAME,
METRIC_NAME,
KEY_VALUE,
KEY_VALUE2,
KEY_VALUE3,
COLUMN_LABEL,
MAX(VALUE) AS VALUE
FROM (SELECT
TO_CHAR(COLLECTION_TIMESTAMP, 'DD-MM-YYYY HH24:MI:SS') AS COLLECTION_TIMESTAMP,
TARGET_NAME,
METRIC_NAME,
KEY_VALUE,
KEY_VALUE2,
KEY_VALUE3,
COLUMN_LABEL,
VALUE
FROM (SELECT MAX(COLLECTION_TIMESTAMP)
OVER(PARTITION BY TARGET_NAME, METRIC_NAME, KEY_VALUE, KEY_VALUE2, KEY_VALUE3, COLUMN_LABEL) max_my_date,
COLLECTION_TIMESTAMP,
TARGET_NAME,
METRIC_NAME,
KEY_VALUE,
KEY_VALUE2,
KEY_VALUE3,
COLUMN_LABEL,
VALUE
FROM MGMT$METRIC_DETAILS
WHERE METRIC_LABEL LIKE 'SOX%')
WHERE COLLECTION_TIMESTAMP = max_my_date)
GROUP BY COLLECTION_TIMESTAMP, TARGET_NAME, METRIC_NAME, KEY_VALUE, KEY_VALUE2, KEY_VALUE3, COLUMN_LABEL
ORDER BY TARGET_NAME ASC, METRIC_NAME ASC, COLUMN_LABEL ASC)
SELECT (SELECT NVL(amt.AGENT_HOST_NAME, ' ') AS AGENT_HOST_NAME
FROM MGMT$TARGET t LEFT OUTER JOIN MGMT$AGENTS_MONITORING_TARGETS amt ON t.TARGET_GUID = amt.TARGET_GUID
WHERE t.TARGET_NAME = prf.TARGET_NAME) AS "HOSTNAME",
(SELECT NVL(PROPERTY_VALUE, ' ') FROM MGMT$TARGET_PROPERTIES WHERE PROPERTY_NAME = 'IP_address' AND TARGET_NAME = (SELECT NVL(amt.AGENT_HOST_NAME, ' ') AS AGENT_HOST_NAME
FROM MGMT$TARGET t LEFT OUTER JOIN MGMT$AGENTS_MONITORING_TARGETS amt ON t.TARGET_GUID = amt.TARGET_GUID
WHERE t.TARGET_NAME = prf.TARGET_NAME)) AS "IP ADDRESS",
(SELECT NVL(PROPERTY_VALUE, ' ') FROM MGMT$TARGET_PROPERTIES WHERE PROPERTY_NAME = 'DBVersion' AND TARGET_NAME = prf.TARGET_NAME) AS "DB VERSION",
(SELECT NVL(PROPERTY_VALUE, ' ') FROM MGMT$TARGET_PROPERTIES WHERE PROPERTY_NAME = 'InstanceName' AND TARGET_NAME = prf.TARGET_NAME) AS "DB INSTANCE",
'All database accounts' AS DESCRIPTION,
prf.KEY_VALUE AS "USERNAME",
prf.VALUE AS "PROFILE",
acc.VALUE AS "ACCOUNT STATUS",
CAST(TO_TIMESTAMP(created.VALUE, 'YYYY-MM-DD HH24:MI:SS.FF1') AS DATE) AS "CREATED",
CAST(TO_TIMESTAMP(passwd.VALUE, 'YYYY-MM-DD HH24:MI:SS.FF1') AS DATE) AS "LAST_PWD_CHANGED",
d.VALUE AS "DAYS_SINCE_LAST_PWD_CHANGED",
(SELECT NVL(PROPERTY_VALUE, ' ') FROM MGMT$TARGET_PROPERTIES WHERE PROPERTY_NAME = 'orcl_gtp_contact' AND TARGET_NAME = prf.TARGET_NAME) AS "ENVIRONMENT ROLES",
CAST(TO_TIMESTAMP(dl.VALUE, 'YYYY-MM-DD HH24:MI:SS.FF1') AS DATE) AS "LAST LOGON",
TO_DATE(prf.COLLECTION_TIMESTAMP, 'DD-MM-YYYY HH24:MI:SS') AS "COLLECTION DATE"
FROM dataset prf,
dataset acc,
dataset created,
dataset passwd,
dataset d,
dataset dl
WHERE prf.TARGET_NAME = acc.TARGET_NAME AND prf.KEY_VALUE = acc.KEY_VALUE AND prf.TARGET_NAME = created.TARGET_NAME AND prf.KEY_VALUE = created.KEY_VALUE
AND prf.TARGET_NAME = passwd.TARGET_NAME AND prf.KEY_VALUE = passwd.KEY_VALUE AND prf.TARGET_NAME = d.TARGET_NAME AND prf.KEY_VALUE = d.KEY_VALUE
AND prf.COLUMN_LABEL = 'PROFILE' AND acc.COLUMN_LABEL = 'ACCOUNT STATUS' AND created.COLUMN_LABEL = 'CREATED'
AND passwd.COLUMN_LABEL = 'LAST PWD CHANGE' AND d.COLUMN_LABEL = 'Days since last pwd change' AND dl.COLUMN_LABEL = 'LAST LOGON'
ORDER BY 1 ASC, 4, 5 DESC
Identifying the Source of the Issue
To identify which portion of this query is causing the issue, we can use the following techniques:
Technique 1: Using a Single-Row Subquery
We can wrap our subqueries to check which one gives more than one row. For example:
SQL> select
2 (select 1 from dual) as result_1,
3 (select 1 from dual connect by level < 10) as result_2
4 from dual;
(select 1 from dual connect by level < 10) as result_2
*
ERROR at line 3:
ORA-01427: single-row subquery returns more than one row
SQL> select
2 (select count(1) from (select 1 from dual)) as check1,
3 (select count(1) from (select 1 from dual connect by level < 10)) as check_2
4 from dual;
CHECK1 CHECK_2
---------- ----------
1 9
By running this simple query, we can determine that the issue lies in the second subquery.
Technique 2: Using Partitioning
Another approach is to analyze the partitioning of your tables. In this case, the MGMT$METRIC_DETAILS table is partitioned by multiple columns (TARGET_NAME, METRIC_NAME, KEY_VALUE, KEY_VALUE2, KEY_VALUE3, and COLUMN_LABEL). When using subqueries with these partitions, you must be aware that Oracle will evaluate each partition separately. This can lead to performance issues if the partitions are large or have a lot of data.
Technique 3: Using Indexing
Finally, consider indexing your columns used in the query. In this case, we notice that many columns, such as TARGET_NAME, METRIC_NAME, and KEY_VALUE, are not indexed. This can lead to performance issues if these columns are frequently used in queries.
Best Practices for Optimizing Performance
To avoid performance issues in Oracle SQL queries:
- Use Partitioning: If you’re working with large datasets, consider partitioning your tables based on commonly used criteria.
- Index Frequently Used Columns: Make sure to index columns used in
WHERE,JOIN, andORDER BYclauses to improve query performance. - Optimize Subqueries: When using subqueries, use techniques like those described above to identify the source of any issues.
By applying these techniques and following best practices for optimizing performance, you can improve the efficiency of your Oracle SQL queries and resolve issues like the one presented in the question.
Last modified on 2025-02-19