Changing the size of redo logs in python

I create a lot of small databases to do testing on. The trouble is that I often need to change the size of redo log files when I'm testing large transaction workloads or loading a lot of data. Now there are lots of better ways to do whats shown in the code below but this approach gave me the chance to keep brushing up my python skills and use the might cx_oracle driver. The following should never be considered anything but a nasty hack but it does save me a little bit of time i.e. don't use this on anything but a test database… Clearly the sensible way to do this is to write my own scripts to build databases.

The following code works it's way through the redo log files drops one thats inactive and then simply recreates it. It finished when it's set all of the redo to the right size.

Running the script is simply a case of running it with the parameters shown below

python ChangeRedoSize -u sys -p welcome1 -cs myserver/orclcdb --size 300

Note : the user is the sysdba of the container database if you are using the multitenant arhcitecture and the size is in Mega Bytes.

You should then see something similar to the following



Current Redo Log configuration
+-----------+------------+--------------+-----------+---------------+----------+
| Group No. | Thread No. | Sequence No. | Size (MB) | No of Members |  Status  |
+-----------+------------+--------------+-----------+---------------+----------+
|     1     |     1      |     446      | 524288000 |       1       | INACTIVE |
|     2     |     1      |     448      | 524288000 |       1       | CURRENT  |
|     3     |     1      |     447      | 524288000 |       1       |  ACTIVE  |
+-----------+------------+--------------+-----------+---------------+----------+
alter system switch logfile
alter system switch logfile
alter database drop logfile group 2
alter database add logfile group 2 size 314572800
alter system switch logfile
alter database drop logfile group 1
alter database add logfile group 1 size 314572800
alter system switch logfile
alter system switch logfile
alter system switch logfile
alter system switch logfile
alter database drop logfile group 3
alter database add logfile group 3 size 314572800
alter system switch logfile
All logs correctly sized. Finishing...
New Redo Log configuration
+-----------+------------+--------------+-----------+---------------+----------+
| Group No. | Thread No. | Sequence No. | Size (MB) | No of Members |  Status  |
+-----------+------------+--------------+-----------+---------------+----------+
|     1     |     1      |     455      | 314572800 |       1       |  ACTIVE  |
|     2     |     1      |     454      | 314572800 |       1       | INACTIVE |
|     3     |     1      |     456      | 314572800 |       1       | CURRENT  |
+-----------+------------+--------------+-----------+---------------+----------+
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Notes on pre-parsing data for Oracle data loads

Sometimes data simply isn't in a form that is easy to load into an Oracle database i.e. column form. It would be great if everybody exchanged data in a simple CSV form with a single file to table mapping. Sadly that isn't the case and sometimes you have to do a little work to get it into a form thats useable. A recent benchmark highlighted this issue very well. The customer provided the data in compressed CSV form (so far so good) but the data was held in key value pairs (not so good). They also provided us with a mapping file that describes how it all fits together. 

Now typically the approach many people would take would be to develop some form of program that parses all of the data and writes it to staging  area and then loads all of it in one go to the target database. I make no criticism of this approach since it works well and as long as its not time critical. It's by far the simplest method. However Im a big fan of taking advantage of whats already available and one of the most underused and powerful features of the Oracle database is  the preparser. It enables you to pipeline various operations so they all run as quickly as possible. So going back to my benchmark we used this approach to load data into out target database. It consisted of 4 steps
  • Read the data of the filesystem as efficiently as possible and write it to stdout
  • Read from stdin and Unzip the the data writing it to stdout
  • Read from stdin into a java program to do the key value mapping and error detection/correction writing the output to stdout
  • Read from stdin into sqlloader
I will at this time point out I'm not really using Oracle's pre-parser I'm just using good old "Pipes" but why this is important will become clearer later This approach gave us a great deal of flexibility and simplified the code we had to write. It operates in some respects as a serialised map reduce flow but I'll come back to that another day and explain how it can be integrated directly into a massively parallel approach. It's also possible to get Java to natively read the zipped file as well having said that I offloaded that process to the os to enable me to use different compression formats when needed.

The java program simple reads from stdin and writes to stdout. To handle key value pairs just required the program to read the mapping file in and split and parse the values from stdin. The data was then written to stdout in a well know order.

Java extract from my program... 


            BufferedReader br = new BufferedReader(new InputStreamReader(System.in), OneMB);
            String line = null;
            HashMap keyValuePairs = null;
            MyTokenizer mt = null;
            while ((line = br.readLine()) != null) {
                keyValuePairs = new HashMap(200);
                mt = new MyTokenizer(line, delimitor);
                for (String token : mt) {
                    int loc = token.indexOf("=");
                    if (loc != -1) {
                        String i = token.substring(0, loc);
                        String s = token.substring(loc + 1, token.length());
                        keyValuePairs.put(i, s);
                    }
                StringBuffer outRec = new StringBuffer(1000);
                outRec.append(checkForNull(keyValuePairs.get("uniqueID"), "")).append(seperator);
                // mapping logic similar to above repeats
                System.out.println(outRec.toString());
            }

All that was needed for sqlloader to process the files was a control file that understood the order of the columns and any additional formatting. 

One of the additional benefits is that we can load the data via "direct path" and implement other features such as multi table insert. The Java preparser enables you to add all of the additional formatting to make this a trivial process.

The following diagram illustrates the process.

This equates into a Unix/Linux statement such as

/bin/dd if=myverybigfile.txt bs=1024k status=noxfer 2>/dev/null | /bin/gunzip -c | java -classpath /home/oracle/loader.jar com.dom.KeyValueParserStdIn | sqlloader bench/bench control=kv.ctl data=\"-\" direct=TRUE;

NOTE : one thing you may have noticed is that Im using dd to do 1MB I/Os. This just an efficiency operation and works well on structures such as DBFS, you could skip this part of the operation if needed.

Which brings us onto external tables and the preparser


External Tables and pre-parsers 

As I mentioned earlier I like to take advantage of functionality that's already available and one of those features in the Oracle database is external tables. I don't intend to go into much detail as to why you should use external tables other than they do much of the heavy lifting for you and they provide a seamless interface between the filesystem and the database. They effectively make files look like tables. 

This means it's trivial to implement parallelism for our pre-parser. We don't need to worry about how to handle the files and how to schedule everything, external tables take care of all of that for you. In our benchmark we used them in the following way




Our previous pipeline remains the same except that we don't need sqlloader its all managed by the table definition itself. So we end up with something similar to the following for the table definition (I've abbreviated it quite substantially and highlighted the important bits)

create table staging_ext_mydata_jan01
(    uniqueid NUMBER,
..
-- Lots of columns
..
 )
ORGANIZATION EXTERNAL
(
   TYPE oracle_loader
   DEFAULT DIRECTORY load_dir_jan01
   ACCESS PARAMETERS
   (
      RECORDS DELIMITED BY NEWLINE
      PREPROCESSOR exec_dir:'external_tab.sh'
      BADFILE log_dir: 'external.bad'
      LOGFILE log_dir: 'external.log'
fields terminated by '|'
OPTIONALLY ENCLOSED BY '"' AND '"'
   ( uniqueid char(100),
..
-- Lots of defintions
..
)
)
LOCATION('data1.txt',data2.txt'...'data100.txt'))
REJECT LIMIT UNLIMITED;

One of the things to note is that I've included the pipelined preprocessor inside of a shell script which looks like this 

/bin/dd if=$1 bs=1024k status=noxfer 2>/dev/null | /bin/gunzip -c | java -classpath /home/oracle/loader.jar com.dom.KeyValueParserStdIn

The important part of this script is the parameter ($1) that is passed to the shell script. This is the file name that the external table wants to process. 

A simple select statement from my "staging_ext_mydata_jan01" unzips and parses the data converting it to usable columns. Whats more if I issue the statement in parallel Oracle takes care of creating the processes for me and making sure everything is scheduled in an orderly fashion.

To finish the load we simply used a multi table insert to put the data into the correct tables in an efficient fashion. Using this approach we were able to read zipped files, parse them and insert them into our three target tables at over 1.5 million source records/sec.
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Timing groups of SQL operations

Some times I feel like I’ve missed out on a whole chunk on functionality in Oracle products. One little nugget is the “timing” function in SQL*Plus. This allows you to time groups of operations.

Obviously turning on is achieved with the “set timing on” operation. i.e

SQL > set timing on

SQL > select count(1) from all_objects;

COUNT(1)
----------
68653

Elapsed: 00:00:03.95

SQL>


Which is great but what if want to time mulitiple operations. Use the timing function and simply give the timer a name, in this case statement timer.

SQL> timing start statement_timer
SQL> select count(1) from all_objects;

COUNT(1)
----------
68653

SYS@orcl > /

COUNT(1)
----------
68653

SQL> timing show statement_timer;
timing for: statement_timer
Elapsed: 00:00:30.85
SQL>


Which times anything that went on in between the timer starting and finishing. In this case also my typing of the commands. Its a fantastic utility for timing stages in a batch job including call outs to os operations.
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Datawarehousing benchmark

Recently some of my colleagues and myself worked on a data warehousing benchmark. This comprised of a 1TB data set consisting of a 14 billion row fact table with 5 dimensions of a much smaller size. Nothing outrageous a classical star schema... bread and butter to Oracle. We used the following hardware configuration

2 Intel based servers.
  • 4 CPUs with Dual Cores (hyper threading enabled).
  • 64 GB of memory in each
  • 2 dual ported 4Gb HBAs
  • 2 dual ported 1Gb Nics
The storage consisted of
  • 10 low cost storage arrays
  • 20 controllers
  • 20 trays of disk with 14 15k 36GB drives in each
The fabric consisted of
  • 2 mid range 16 port fibre switches
The network consisted of
  • 1 mid range 16 port 1Gb switch (I know we really should have had two of these)

The point here is that the hardware was low end but with the ability to deliver plenty of CPU and I/O at very attractive price point. For those that aren't that interested in any more of the details the headline figures where that we performed full table scans at over 1.6GB/sec but due to compression we achieved logically three times this figure.

We used a stock 2.6 64 bit Linux kernel we modified the following kernel settings
  • wem, rmem were to set to 512k to reflect the fact that we were going to use 32k block sizes
  • Huge pages were enabled... its a much more sensible way of managing the shared memory required for the SGA
  • We enabled jumbo frames in the switch and set the MTU on the interconnect to 9000bytes
  • We used the deadline scheduler to improve I/O prioritisation.
  • Multipath was used to provide DMP over the 4 paths to disk from each of the servers.

The Oracle database was largely unchanged from the defaults with the exception of the following settings
  • 16GB for SGA and PGA
  • The fact table was compressed
  • 32k block sized to improve compression ratios
  • Two parallel instance groups to ensure execution of certain queries on a given node.
  • Query rewrite was enabled.
  • ocfs2 was used for the quorum and ocr files
  • ASM was used to provide storage for the datafiles etc. Each physical tray of disk was presented to ASM as logical disk of roughly 500Gb.
  • ASMlib was used to persist disk identity and simplify configuration.

The tests consisted of a series of SQL statements that were run serial, concurrently and as a series of streams. I cant give much in the way of specifics for obvious reasons but the machine ran at about 80% utilization during the test most of the queries returned sub minute when run against the full data and many sub second when materialized views were exploited.

However the real benefit came from the fact that low the cost commodity hardware made the system relatively cheap and easy to put together. Like any system there were things we would have liked to have done differently if we'd had the chance... The benchmark was done in 10 days (OS Install, disk, layout, Oracle install, data load etc.) and so things were done in a rush and with a little more thought could have been done much more efficiently... We are fairly certain we could have improved the I/O performance but we didn't have the luxury of experimentation and so we made a call and lived with the consequences... I strongly recommend that any one building one of these systems spends some time with Oracle Orion disk benchmarking system to determine an optimal layout. A recent customer evaluating several possible disk layout configurations showed over 100% difference between two subtly different versions.
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On the subject of I/O

One the things that constantly surprises me when talking with clients about hardware for a new database server is that I/O is always at the bottom of the list. Typically the list will look something like this (listed in order of perceived importance)
  • CPUs, have we enough. Fast as possible.

  • Memory, as much as we can put in the box. Oracle don't charge us for that

  • SAN, big as possible.

At this stage the purchase order is usually given the nod and the hardware supplier will ship yet another run of the mill box. Don't get me wrong. Many experienced DBAs have been through this process many times before and realise that not only is the list in the wrong order but its missing some critical components.
  • HBAs, need to specify these in proportion to the CPUs and attached storage

  • NICs, might need a lot of these i.e public, cluster interconnect, storage, management, backup. And typically in multiples for resillience or performance.

  • Backup, are we using the existing backup infrastructure?

I don't blame anyone for this way of thinking, its the way its always been. When discussing a new server the first question that people tend to ask is "So whats this monster packing? 16 CPUs!!!" followed by lots of very macho grunts and hollering. The standard licensing model (not just Oracles) doesn't help. It starts with premise of a CPU describing the power of a server, and to a large degree it does but misses the point of what a database is all about and that's information. Typically that information is held in ones and zeros on a bunch of spinning scrap metal. The real power of a database comes from its ability to aggregate, analyze and process those ones and zeros, turn it into information and push results out to interested parties. Paraphrasing a little "Its all about I/O stupid".

With this in mind I'm constantly surprised by the imbalance of I/O put into servers both disk and network. Its not unusual to see a 4 cpu server running with the latest generation Intel and AMD CPUs but with a single HBA and dual ported NIC. Whilst memory is cheap many of these servers still run 32 bit kernels. This typically means only a small proportion of the database is cached in memory be it in the SGA or file cache (don't me started on file cache). I'd make a rash guess that whilst the size of the memory in a typical database server has increased the average size of the SGA hasn't increased in line with this trend. To make matters worse the typical size of a database has got significantly bigger. This has to lead us to the conclusion that less of the database is cached and as a result a bigger proportion of its is located on disk. As I said this is just a guess but its backed up with real customer engagements. What would be of interest is to have performed an analysis over the last 10 years to see if the wait event for scattered and sequential reads had decreased or increased as a proportion of the total wait event in production databases.

What I'm driving at is the need to move I/O way up the agenda when sizing a server for databases. The number of CPUs needs to be married to the number of I/O channels available. It makes no sense to buy database licenses for a machine that will simply sit and wait on I/O, Its simply wasting money. Equally it makes no sense to stuff a 4 cpu machine full of HBAs for a database application that will perform index lookups on a index that fits comfortably in the cache. Adding HBAs later to an existing server isn't necessarily a simple option either especially for a mission critical application or one that has hard coded paths to disk.

The next obvious question is "well thats well and good but how do I size the ratio of HBAs to CPUs." and in a typically vague fashion I reply "well that depends". The type of application and the type of processor should heavily influence the decision. Certainly the CPU has been winning the race in terms of performance over the last few years and it needs a lot more I/O to keep it busy. But the equation also needs to be balanced with the amount of memory available on the box. A large SGA will certainly reduce the need to visit disk. The best advice I can give is to speak to your hardware supplier and find out what the current state of play is. Also check the latest TPC-C and TPC-H figures show. Whilst these are generally edging towards the extremes of performance it does show what a hardware supplier believed was needed to show their hardware in the best light.

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SQL Developer goes production.

SQL Developer has gone production. Congratulations to the entire development team. I've been using it every day now and it feels solid and performs well and I continue to find out new tricks and features each day. If you've not given it ago, try it...
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SQLDeveloper

If you haven't tried this tool out I strongly recomend you pop over here. Its a massive step forward for database developers/DBA who really have felt a little neglected by Oracle over the last few years. I've had countless complaints about how SQLPlus/vi/notepad are still used by many as their development tools of choice and how it really isn't good enough. Well I've know about th tool for a while now and have had to keep quite but Im glad the cats out of the bag and its got such positive reviews... especially because of its price... free.

It features much of the functionality you'd expect in a top end development tool plus features that many of its competitors charge top dollar for. The best piece of news is that its an extensible framework and plugins have started to pop up all of the place... One of my particular favourites is at fourthelephant. Perhaps a little over the top for a text man like myself but I appreciate the work that must have gone into it.

They've inspired me to think about putting one together myself... The API is pretty simple and so it shouldn't be too taxing.... Any ideas? drop me a line and I'll see what I can do.
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rlwrap : Command line editing in sqlplus

I imagine alot of people in the Linux comunity already use this. However if you new to Linux and struggling with recalling text on the commandline from within sqlplus, rlwrap might be the tool for you... its just a wrapper you put around a command line program and provides command line editing.... I've been using it for the last few months and couldn't live without it

You can find the tool here
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Server side failover

I've had a number of emails recently with requests for help with the new server side failover functionaility in 10g release 2. This functionality is described in the Oracle10g release 2 documentation but I've been told its not really obvious.

Let start by explaining what it is. Server side failover allows the sysadmin/dba to configure the profile of connection availablity on the server using a service. Users are effectively unaware of what will happen in the advent of a node in the cluster failing. Previously in (9i and 10g) users needed an entry in their local tnsnames file to describe which nodes they could failover to and which nodes were used to load balance connections on. Unless you used a remote naming service to maintain the connection information every time you added or removed nodes from a cluster it meant an update to potentially hundreds or thousands of tnsnames files.

This was simplified with easy connect in 10g release 1 which allowed the creation and connection to a service specified on the server. For the first time users only needed to connect to a nominated "listener node" and know the name of the service, for example imagine we have a nominated server inside of our organisation called "oracleservice", this of course is the name used for our virtual ip that will float between our cluster of listeners. In 10g release 1 we could create a service called "orderentry" using either dbca or srvctl that would allow our users to connect to it using a connect string of the form

sqlplus soe/soe@//oracleservice/orderentry

This greatly simplifies Oracle network maintenance. In some cases it could mean the removal of tnsnames files from the client or application server. It has other advantages for the DBA as well. If some business event occurs that requires the provisioning of a new application or a new resource profile for a short period of time the DBA can provision it in seconds and trivially remove it when it is no longer required.

Sadly in Oracle10g release 1 this functionality didn't support Transparent Application Failover (TAF), this meant that DBAs still needed to maintain tnsnames files contain a description of what nodes a service could failover on. The good news is that in Oracle10g release 2 this all changed. DBA's could set up a service specifying TAF and the Oracle OCI layer would use this definition provided by the server to describe the load balancing and failover profile.

Implementing this functionality is pretty trivial but there is a step that might catch you out. So lets go through it step by step

To set up the service you can use either Oracle DBCA, the DBMS_SERVICE package, Enterprise Manager or srvctl. The choice is entirely dependent on what you have running. DBCA or Enterprise manager provide the simplest mechanism but you will still have to run the final step using the dbms_service package to tell the database about its failover profile.

I'll use the DBMS_SERVICE package and srvctl for the sake of brevity. In the following example I have a database called db10g2 with two instances db10g21 and db10g22. Im going to create a service called "orderentry" that will provide transparent application failover between the two instances.

The first step is to create the service using srvctl

srvctl add service -d db10g2 -s orderentry -r "db10g21,db10g22" -a "db10g21,db10g22" -P BASIC

and check on its status

$ > srvctl status service -d db10g2 -s "orderentry"
Service orderentry is not running.

So we'll have to start the service first

$ > srvctl start service -d db10g2 -s "orderentry"

if we now use sqlplus connecting as system/sys we can see the service.

SYSTEM@db10g21 > select SERVICE_ID, NAME, NETWORK_NAME, failover_method from dba_services;

id Name Network Name Failover
--- ------------------ ------------------------- ------------
1 SYS$BACKGROUND
2 SYS$USERS
3 orderentry orderentry


The thing to note is that the service hasn't got a failover profile associated with it. So we'll have to modify it using the DBMS_SERVICE package

SYS@db10g21 > get t1.sql
1 begin
2 DBMS_SERVICE.MODIFY_SERVICE(
3 service_name => 'orderentry',
4 failover_method => DBMS_SERVICE.FAILOVER_METHOD_BASIC,
5 failover_type => DBMS_SERVICE.FAILOVER_TYPE_SELECT,
6 failover_retries => 180,
7 failover_delay => 5);
8* end;
SYS@db10g21 >

if we now select the service information again

id Name Network Name Failover
--- ------------------ ------------------------- ------------
1 SYS$BACKGROUND
2 SYS$USERS
3 orderentry orderentry BASIC

We can now test the service using sqlplus.

sqlplus soe/soe@//node1/orderentry

SQL*Plus: Release 10.2.0.1.0 - Production on Wed Jan 18 14:11:47 2006

Copyright (c) 1982, 2005, Oracle. All rights reserved.


Connected to:
Oracle Database 10g Enterprise Edition Release 10.2.0.1.0 - Production
With the Partitioning, Real Application Clusters, OLAP and Data Mining options

SOE@//node1/orderentry >

So all we need to do now is to fire up swingbench and use the service we've created.

[oracle@node1 bin]$ ./charbench -cs //node1/orderentry -dt oci -uc 30 -a
Author : Dominic Giles
Version : 2.2

Results will be written to results.xml.
Users : 30 TPM : 272 Nested TPM : 0

If we log onto the database we can see that the connections have being balanced across the two nodes

SYS@db10g21 >;

1 select instance_name, count(1) usercount, nvl(username,'INTERNAL') user_name,
2 failover_type, failover_method
3 from gv$session s, gv$instance i
4 where s.inst_id = i.inst_id
5 group by instance_name, username, failover_type, failover_method
6* order by username, instance_name
SYS@db10g21 > /

Instance No. of Users Username Fail Over Type Fail Over Method
---------- ------------ ---------- ------------------ ------------------
db10g21 15 SOE SELECT BASIC
db10g22 15 SOE SELECT BASIC
db10g21 6 SYS NONE NONE
db10g22 6 SYS NONE NONE
db10g21 23 INTERNAL NONE NONE
db10g22 25 INTERNAL NONE NONE

so lets shut down of the instances

SQL*Plus: Release 10.2.0.1.0 - Production on Wed Jan 18 15:28:22 2006

Copyright (c) 1982, 2005, Oracle. All rights reserved.


Connected to:
Oracle Database 10g Enterprise Edition Release 10.2.0.1.0 - Production
With the Partitioning, Real Application Clusters, OLAP and Data Mining options

SYS@db10g22 > shutdown abort;
ORACLE instance shut down.
SYS@db10g22 >

And re-query the session profile

Instance No. of Users Username Fail Over Type Fail Over Method
---------- ------------ ---------- ------------------ ------------------
db10g21 30 SOE SELECT BASIC
6 SYS NONE NONE
25 INTERNAL NONE NONE


There's a lot more thats possible using the service approach to database connection but I'll discuss that in another blog.





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