Thursday, August 18, 2016

-- Do not forget about the Database recycle bin --

Hello Everybody

Just a quick post reminder to keep in mind that starting on Oracle 10g when you drop objects they still recide in your recycle bin. So if you wonder why after dropping all those tables you do not see the space back, you got your answer. This is specially important if you have some DW like environment where you drop and recreate tables every day part of your ETL.

Every schema in the database has its own recyclebin, if you want to know what is the content of the entire database recycle bin you can do this query.


If you only want to query your schema recycle bin then you execute the following.


In order to be able to purge an object from the recycle bin you need to either own the object or you need to have the "drop any" system privilege assigned to you. 

If you want to purge objects in the recyclebin for the entire database, you need to have the sysdba privilege, be connected as sysdba and execute the following.

SQL> purge dba_recyclebin;

If you want to purge your own recycle bin you do the following.

SQL> purge recyclebin;

If you want to purge objects in the recycle bin stored in an specific tablespace you execute the following:

SQL> purge tablespace ;

If you want to be more specific and purge objects in a specific tablespace for a specific user you execute the following.

SQL> purge tablespace user ;

Last but no least if you want to purge the recycle bin for a table you own and you just dropped you execute the following.

SQL> purge table ;

If that table has indexes associated you execute the following.

SQL> purge index ;

Enjoy. 





Wednesday, June 1, 2016

-- A Quick handy guide to generating SQL Trace --

We all have done this a time or another, and then we have to do it again and we have to go back to our notes to remember the steps, this is well-known information, but I encourage you to bookmark it and have it handy as you will eventually need to use it as well.

Tracing the execution of a SQL

alter session set tracefile_identifier='10046';
alter session set timed_statistics = true;
alter session set statistics_level=all;
alter session set max_dump_file_size = unlimited;
alter session set events '10046 trace name context forever,level 12';

/* now you execute the sql that you want to trace */

exit;

The trace file will be located in your diagnostic destination and will have the number 10046 as part of the file_name, you want to go there to format it using tkprof.  

tkprof input_file output_file waits=yes explain=username/password

Note: you can use the sort clause to sort the output in many ways, for a complete description of options please check the following resources:


Cheers!!!!


Saturday, February 13, 2016

-- Oracle 11g Optimizer and Incremental Statistics --

As I was doing some research about the 11g optimizer I found out that in 11g you can now gather Incremental statistics for partitioned tables. The idea behind this feature is to be able to capture global statistics on large partitioned tables at a lower resource cost by minimizing the time required to collect statistics.

This makes complete sense, think about a large range partitioned table, for example, SALES_DATA. Let's assume that your SALES_DATA table is partitioned by month, it is very unlikely that old sales data will change, especially data that correspond to previous years. As you know Oracle keeps statistics at the partition level and overall statistics for the table,  Oracle monitors DML operations at the table and subpartition levels, normally statistics are gathered only for those partitions that changed (> than 10%), however, global statistics are gathered by scanning the entire table and that makes it a very expensive operation.

In order to do that, you need to first set the table preferences to incremental.

SQL> exec dbms_stats.set_table_prefs('TPM','SALES_DATA','INCREMENTAL','TRUE');

Next we gather the global statistics

SQL> exec dbms_stats.gather_table_stats('TPM','SALES_DATA', GRANULARITY=> 'GLOBAL');

If you query the last analyzed column from users_table you will see that the timestamp is updated, however when you query the same column on user_tab_partitions you will see that not all the partitions got updated, furthermore you should see a different on the time it took to gather the statistics.




Tuesday, January 26, 2016

-- Oracle 12c Grid Infrastructure Management Repository MGMTDB --

After installing Oracle 12c Grid Infrastructure on an ODA X3-2 we started getting a warning from Enterprise Manager alerting us that the target MGMTDB Database SYSMGMTDATA tablespace is 85% full. As you can imagine we were surprised as we did not recognize that database. We reached out to few people before and realized that this must be something new.

Starting 12.1.0.2 Oracle creates a new mandatory database called MGMTDB, Oracle creates on it Cluster Health Monitoring (CHM) Data among others, this database gets failover to a surviving node in case one node goes down, the database needs to be up and running, it starts up automatically.

Please note: There is a minus sign in from of the database name

Database name: -MGMTDB
ORACLE_HOME: Same as the GRID_HOME

I am not sure about the password for SYS or SYSTEM on it, but you can connect as sysdba


There are 3 tablespaces on it (UNDO, SYSTEM and SYSAUX) , you do not have to worry about space management since the datafiles are auto-extensible.


MOS 2065175.1 contains information about how to use MDBUtil tool, this tool allows you to perform a variety of operations with the management repository. The best article I found with information related to this topic is from Amit Bansai and you can access it on this link.


Thursday, March 5, 2015

-- Oracle Compression Offerings --

I recently was approached by a consultant that was confused about the different compression offerings from Oracle, so I decided to write a high-level short summary to provide some clarity.

Oracle offers 3 types of Compression:

A) Basic Table and Index Compression (Good for Data Warehouses): This feature has many years in the market (at least 10 (Oracle 9i)) and it is part of Oracle Enterprise Edition (no additional license cost for you), when Oracle designed this feature the goal as the name of the feature says was to compress data to save space, however, what they found is that by compressing the data, and as a natural consequence you reduced the I/O, and if you add to it the fact that their compression / decompression algorithm is very light and simple (just consume negligent additional CPU amounts) the query performance often increases.

A.1) What are the disadvantages of it:  With this type of compression Oracle only compresses the data when you are inserting it into the table, and you need to insert it using “direct path insert”. The other disadvantage is that during updates Oracle needs to decompress the records and after updating them it does not compress it again, therefore you will end with a mix of compressed and uncompressed records. This type of compression is not good for OLTP databases, but ideal for Data Warehouses where you mostly do read-only transactions and you populate the data through an ETL tool doing the direct path insert.

A.2) What is direct path insert and what does this means: Direct path insert is a special mode if the insert where Oracle while inserting data will ignore the available free space on the table, in other words, it will not reuse the available free space on the table, it will do the insert after the existing data in the table, therefore wasting disk space, but increasing performance because it bypasses the buffer cache and writes directly to the data files.

A.3) What queries will see a performance advantage: Those queries that requires fetching millions of records and do aggregations where I/O is the bottleneck over tables that have a high compression ratio,  tables with small numbers of rows or small size will see adverse performance impact due to the CPU overhead.

A.4) What compression ratio can be achieved: It depends on the nature of the data, tables with duplicated data will achieve higher compression while tables with almost no data duplication will achieve less to none.

B) Oracle Advanced Compression (Available 11g and above) (a.k.a OLTP Compression): This is a licensed feature that can be implemented on top of Oracle Enterprise Edition only, it works similar to Basic table compression but it allows data to be compressed during all types of DML operations such as Insert or Updates, the compression algorithm is enhanced therefore reducing the overhead of write operations. The other advantage is that Oracle is able to read the rows without uncompressing them, therefore, there is almost no performance degradation in accessing compressed data, in fact in many cases you may see performance improvement due to the reduced I/O.


C) Hybrid Columnar compression (HCC): This is a feature available on Oracle Exadata, and recent rumors say that is available on the ODA X5-2. HCC uses an orchestration of Hardware and Software capabilities, it achieves higher compression rates than the other 2 methods, it has  4 different types of setting (Query high / Query Low/ Archive high / Archive low) that tells Oracle how you want  to balance the compression vs. performance impact; in other words the more compression the higher the CPU cost involved in performing operations, the lower compression the less CPU cost . Different from the other 2 methods this one stores the data in columnar format and that is the secret sauce for achieving higher compression, the disadvantage is that you could have adverse performance effects if you query more than one column at a time, although this is often offset by the use of the Exadata Smart scan feature. You still need to do bulk load of the information to maximize the compression ratio. Oracle includes an advisor that tells you what kind of compression you could expect to achieve. 

Monday, October 27, 2014

-- How to quickly change the AWR Interval and how to create one on demand --



Check the current defaults.


set linesize 100

col snap_interval format a20
col retention format a20
col topnsql format a20
select * from dba_hist_wr_control;

DBID SNAP_INTERVAL        RETENTION            TOPNSQL            
---------- -------------------- -------------------- --------------------
3610569430 0 0:60:0.0           7 0:0:0.0            DEFAULT              


Below we are changing the interval from 1 hour (Default) to 30 min.

execute dbms_workload_repository.modify_snapshot_settings ( interval => 30);

anonymous block completed

Check that the change was applied.

set linesize 100
col snap_interval format a20
col retention format a20
col topnsql format a20
select * from dba_hist_wr_control;

DBID SNAP_INTERVAL        RETENTION            TOPNSQL            
---------- -------------------- -------------------- --------------------
3610569430 0 0:30:0.0           7 0:0:0.0            DEFAULT    

Create AWR on demand

When debugging SQLs you may want to get an AWR snapshot before and after you run an specific SQL.

exec dbms_workload_repository.create_snapshot();

select * from xxxx /* Your query */


exec dbms_workload_repository.create_snapshot();


Wednesday, October 1, 2014

-- Oracle Openworld 2014 --

During my visit to the 2014 Oracle Openworld I had the opportunity to talk with some of Oracle's customers and with different vendors who are leaders in their industries.

This year there is a big focus on the cloud, which is not surprise. Companies are becoming more aggressive in adopting a hybrid between cloud and traditional information systems on premises. Oracle is trying to determine how to support 20 year old applications which are no longer supported by the original vendors, and how to avoid for those apps to age out placing customers on a bad spot in the future. A lot of companies are embracing the SaS schema, especially companies with global operations because that allows them standardization and also resolves the problem of keeping up with application upgrades.

The other emphasis is to provide real time data to the executives, including information from social media. The goal here is to enable executives to make decisions on the spot rather than weeks or months after obtaining the data when they finally get the results from their analytics. Companies believe that there is traditionally a big gap between the time they obtain the information and the time they react to it. By the time they shift gears in their business they missed some or all of the momentum. In order to achieve rapid response time, there are dedicated people constantly studying customer science and interpreting the volume and complexity of the data. This allows them to engage the customer digitally in real time before the analytics age out. 

Many companies find they are experiencing the same types of problems. Some common trends are: reducing the number of legacy applications; moving into a single CRM and ERP systems; achieving globalization and standardization by leveraging Cloud-like technologies; and simplification and modularization of infrastructure technology to enable the use of common computing power.

There has been a shift where companies are not longer organizing and following sales leads by territory and region, but by customers that are most likely to buy, with the implementation of digital technology, it is not longer that relevant to have a presence on a specific territory or  region, and companies can save in OPEX by making strategic use of their sales force. 

On the technical side Oracle is promoting the consolidation trend by recommending to implement multi tenant databases, this is specially good and true for environments such as development and test sharing the same hardware, but maintaining their inter-independence. On the analytics side once we get to Oracle 12c there is a paid feature called in memory database  which allows you non only to store tables in memory, but to organize them in a columnar fashion, which makes your analytics performance many times faster. 

Talking to some of the vendors they tell me nobody is doing money with Big Data, companies simple do not have interest on it yet, but they see a lot of potential and started to see tangible sales on SaS and other Cloud like technologies, the big concern here is still security and the big challenge is extracting your data if you decide to no longer be on a hosted Cloud service.