Getting a raw constant number of rows from oracle’s table sample function

You may of course know these two famous posts called To sample or not to sample… (part-2) about data sampling by Mark Hornick. Although very limited in scope, the two posts (imho) very well sketch why we may employ data sampling and how we may lift off table sampling in oracle.
In general, sampling is used to make a representative statement about a collection of data while only regarding a limited random selection, the sample. As long as you are ok to analyze just a sufficient subset of your 1o million rows table for an analysis, you will save your environment a lot of resources and time. On some other scenario, a limited random data selection may also serve verification or testing purposes where, however, not the representativeness but the randomness at a more or less constant sample size, determines the quality of the sample output. Again, as long as you are ok to not exceed this 15 minutes time window overnight, you will be allowed to run that live unit test on any table in question, on 1, 10 or 100 million rows.
In sql, selecting in regard to gain a representative statement will feed the sample function with a requested percentage of rows to sample from. This is what the oracle sample function already offers. Yet another sql to accept a requested actual number of rows to return, independent of the table size, is not available so far (although most people do expect exactly this behaviour when they spot the sql sample function for the first time, weird). The following text will outline a snippet of pl/sql to provide for a sample function to accept the expected number of rows as a parameter.



Deprecation announcement of oracle restart along 12c withdrawn

As being spotted on Bjoern Rost’s blog, commented by Trap, today, Oracle obviously has been backing down on the deprecation announcement of oracle restart along 12c. On metalink, see:

Withdrawn: Deprecation Announcement of Oracle Restart with Oracle Database 12c (Doc ID 1584742.1)

This is good news, accepted with delight, since we do no longer need to turn back the hands of time into the nifty-oracle-bounce-handycraft-scripts-era. In fact, I wonder how many dba’s are already comfortable with systemd service registration. I suppose, a lot of dba’s would have been resorting back to the dusty sysv configurations, using the systemd-sysv-compatibility engine, which is sort of retrofitting a car-key-starter with a car that already comes with wireless keying and just some starter button. Look around, the major share of on-premise oracle database installations is still single instance compared to rac and even 12c-containers.

Have fun, Peter

Undo retention, flashback query and ora-01555 snapshot too old

Setting up a fault aware database environment is in charge of regarding possible physical and logical error scenarios. On the physical side of the medal, you got real-application-cluster or dataguard at your disposal. The logical one usually comprises backup and replication. Recently, oracle and others introduced features that enables a database to recover from logical errors without or with less remote systems and data. Namely flashback is a powerful technology to look back into (query), back out (transaction) or fully restore (database) the history of data. Flashback of course takes accompanying (history) (meta)data to do its job, namely again, undo-before-images, archived-redo-logs and flashback-logs. So, essentially, the convenience of your course into history depends on the amount of history metadata that is available to the database at the time of a logical error, say an inadvertant delete from.

You may already have learned or heard about or even hardly experienced that flashback-logs may be purged from the recovery-area in favour of archived-redo-logs, rendering your configured flashback-retention-time (DB_FLASHBACK_RETENTION_TARGET) a value of theory. So far, sizing the file-system recovery-area is a task to be performed in a clear-sighted manner. The same is true then for undo-before-images (compare to logs) und the undo-tablespace (compare to area) to accomodate enough data to meet your configured undo-retention-time (UNDO_RETENTION) in UNDO_MANAGEMENT=AUTO mode, while in addition still support long running workload queries (not to overwrite old undo). This article discusses the usability of the (enterprise-manager) undo-advisor in sizing your undo-tablespace to always foster successful flashback queries up to the configured undo-retention-time (as opposed to the nasty surprise of getting an ora-01555, see below, which is also misleading here, imho, in suggesting that the undo-tablespace is to small now, as we know it from workload queries – nope, it has been to small before now, in the past, as regarded to flashback queries – also see : ora-01555 snapshot too old when running flashback query).


XMLType.schemaValidate is your only true friend for xmlschema validation

When it comes to introducing xml-data into your database storage, you might, as all sincere developers do, at first attempt to take care of proper data integrity checking on import. Since xml is a really powerful but a somewhat complex document-alike data representation, such integrity checking must incorporate proving the document strucuture, as sort of integrated data types, iff you like, as well as the document data, in terms of facets of given actual values. According to the xml standard, xmlschema is the means of choice here, offering another xml-spelled specification layer to achive the two beforementioned goals. Eventually, a given xml-instance will have to be thrown against the xmlschema provided, to assure its integrity (and being well-formed too, btw), the earlier the better, at best on data import already.

The paragraph above is actually not very oracle specific. Any implementation of the xml standard, as oracle’s xml db does, proposes this course of action. However, since some xml operations may become quite costly when the xml-instances get large and the whole dom tree has to be set up in memory, oracle, as others, dabbles at dodging and shifting pricey work to the most reasonable extend possible. You may load xml into the database, claiming any xml-instances are just fine, validate xml-instances only to be well-formed, manage the validation status of xml-instances at your own responsibility and so forth. There is nothing wrong about that whatsoever. The point is, though, it might be a stony walkway to learn to distinguish the maybe from the certain, to establish a reliable check to safeguard your xml data integrity, just as simple as ALTER TABLE mytab ADD(CONSTRAINT mytab_CHK CHECK(INSERT_TS is not null) NOT DEFERRABLE ENABLE);.

Jep, what next? I’m going to briefly discuss the xmlschema / xmlinstance used below and then show what I experienced will happen using the various ways of “validating” the instance against the schema. The post is somewhat lengthy, but do not get frightened, this is for the c&p examples all along the way.


Understanding “occurrences before alerts” in oracle enterprise manager 13c

The Incident Manager within Oracle Enterprise Manager 13c is a powerful tool for monitoring a wealth of target types such as databases, hosts, middleware or just services in general from a bird’s eye view or right down into the manifold details of a dedicated application. As with all powerful means around, where there is a lot of power, there also usually is a lot to do wrong (or even employ counterproductive). This is why it is important to understand the Incident Manager concepts from bottom up and be able to identify the knobs and wheels to poke with to meet a certain requirement.

Basically, Incident Manager is a professional toolset to facilitate the management of non-critical and critical system alerts against metric values (registered as problems and incidents, see About Incidents and Problems) in a larger quantity and time scale along with alert management templating and alert assigment and so forth.