I have an ASP .NET application that connects to an Oracle or a SQL Server database. An installer has been developed to install a fresh database to an existing SQL Server using sql commands such as "restore database..." which simply restores a ".bak" file which we keep under source control.
I'm very new to Oracle and our application has only recently been ported to be compatible with 10g.
We are currently using the "exp.exe" tool to generate a ".dmp" file and then using the "imp.exe" to import it into a developers box.
How would you go about creating an "Oracle Database Installer"?
Would you create the database using script files and then populate the database with required default data?
Would you run the "imp.exe" tool behind the scenes?
Do we need to provide a clean interface for system administrators so that they can just select the destination server and have done, or should we just provide them with the ".dmp" file? What are the best practices?
Thanks.
The question is -- what do your customers know about Oracle?
Nothing? You should probably rethink this position. Oracle is very large and complex. If you assume your customers know nothing, you'll then start providing tutorials and help that's inappropriate.
Minimally Competent? If they're competent, they know enough to run imp by themselves. Also, they know enough to run a script that executes SQL.
Actual DBA's? Most organizations that can afford Oracle can afford real DBA's. Real DBA's can cope with a lot of things -- they do not need much hand-holding. Some of them like to assign storage parameters according to their shop standards.
You should provide a script with reasonable defaults. You should define your script in a way that someone can easily find all of your storage parameters and tweak them if necessary.
Your initial data can be via export/import or via a script. I prefer a script.
I have done this repeatedly from both sides (consumer and provider) as a DBA, developer, and architect.
As a provider, one of my grand accomplishments (in 1996) was the creation of an installation CD for a commercial insurance claims management software product targeted to the largest insurance carriers (a multi-million dollar item). That installation CD installed the Oracle 7.2 RDBMS engine, the FileNet optical storage system (scans paper documents and creates cataloged binary versions), and our custom claim-processing application (built in VB 4.0), all integrated and ready to run. As part of the installation process, the user could skip the Oracle software installation or customize it, and the user could customize/override the database configuration in all of its major details (database, schemas, tablespaces, sizes, disks, etc.).
I also provided the field service for this product, which included traveling to the client site as necessary. I tested the installation CD literally hundreds of times under every imaginable scenario that I could replicate, and we NEVER had a field failure that required even a phone call, let alone a trip (I did travel on four occasions, but for pre-sales stuff instead).
More recently (2007), I scripted the creation of an Oracle 10g database for an internal system at a megacorp. In production, the database was sized at 8 TB, mostly for a single transaction table with high data volume. In test, the database was sized around 1 TB for a modest server. In development, the database was sized around 100 MB to run on my laptop. The EXACT SAME SCRIPTS created all three environments, and I could extend them to handle a new environment/machine in about five minutes. This database involved extreme performance tuning, so customization of all pertinent characteristics was absolutely crucial.
Back to the insurance claims processing product--let me please add that I was originally hired to lead its conversion from a SQL Server database to an Oracle database. That conversion was identified as a business necessity because most potential clients did not view a SQL-Server-based product as a professional, serious solution. That is not quite as common today, but it still applies in general: a software product has a better chance of market penetration if it can accommodate multiple database options as preferred by the target customers (especially enterprise-class customers).
Likewise, the installation CD was also viewed as an essential element. However, that situation and many more have revealed to me that most "real" DBAs will not accept an import-based database installation. As a DBA and architect, I know that I definitely will not for the same reasons.
Simply put, an import-based database installation gives the customer almost no control over the resulting database. It is opaque to the customer, leaving them questioning what it did. It forces the customer to expend massive efforts to attempt to exercise what little control they can. It is notoriously fragile and error-prone (Oracle imports are well known for ownership and permission problems, constraint problems, etc.). Weighing all those impacts, an import-based database installation is unprofessional--it does not put the customers' needs first.
Scripting the database installation provides the right kind of transparency, configurability, selective repeatability, and overall customer control that professionalism demands. It also encourages you to properly understand the impacts of your database design decisions in a way that an import does not.
Best wishes.
Personally I favour SQL scripts to database creation and data loads where possible. I tend to use PL/SQL Developer. It has some good options to generate scripts from an existing database. Once you have these you can run the scripts using sqlplus or any application code that can execute arbitrary SQL (eg JDBC with Java). Toad is the more common (and more expensive) tool for Oracle development.
The only limitation of a SQL export is it can't export CLOB/BLOB fields. If you have those, you either need to do them separately (as a PL/SQL export) or do the whole thing as a PL/SQL export. Theres no dramas with this except the file is effectively a binary export (extension .pde) and is more limited in how you can execute it.
The other big advantage of SQL source files is they can be version controlled easily. It's really handy to be able to create a database environment by running one or two scripts.
The import and export tools for Oracle I think are more applicable for backup and restore operations.
Now, as for delivering that to a customer, from your comments it seems that you'll be giving this to DBAs. Pretty much any Oracle installation will have DBAs involved. They will be fine with SQL scripts to create the schema and do the data load. They will be doing a lot of site-specific configuration (eg tuning the SGA, temp tablespaces, # of concurrent connections, etc based on expected load).
You, as the vendor, can give guidance on any relevant configuration and you may get involved in support and possibly installation but ultimately it's up to them to figure out what works for them. Oracle runs on a large number of operating systems and hardware variants with infinite variations in network topology and firewall configuraiton. You can't factor in all of these to an installer or even a set of instructions (other than the guidelines mentioned previously).
The last time I was involved in the creation of a (oracle) db (for a reasonably large company with in-house DBAs) the DBAs wanted to know things like:
what we wanted to call the db,
what tablespaces we would need, and an estimate of how much data would be in each one
how many users would be connecting.
(From memory) they set up the db and tablespaces, then we provided a combination of simple scripts that they could run (or clear instructions if a task wasn't easy to automate)
As I say this was for an in-house app, so your mileage may vary, but in my case they wanted all instructions clearly spelt out so that (a) there was no possibily of a misunderstanding leading to the wrong thing being done, and (b) no culpability on their part if something didn't work ("we were just following the instructions")
Related
How to implement a Definitive Media Library (ITIL DML) ?
I would like to know some way to implement a DML based on ITIL.
Given a library of heterogeneous software the only solution that crosses my mind is to use a system file structure (with proper security and access permissions), however this seems very simple and if the library gets too big it will be hard to find software that search.
Is there any specific software for DML?
Many tools that offer CMDB management also offer DML management. Some options for this are ServiceNow and IBM's Change and Configuration Management Database.
If you are only looking for DML functionality, a binary repository manager, such as Sonatype Nexus or Artifactory, provides metadata tagging, version control, and many other useful features. Implementing a binary repository manager and proper procedures for maintaining it serves as an excellent DML solution.
There is nothing wrong with a file system to store software in form of completed, tested (software) configuration items which passed appropriate quality assurance test, etc. But because of the controlled it environment in ITIL, it is mandatory to establish an control structure for tracking the appropriate information of every CI or software in the DML. This records have to contain all relevant informations like version, build date, development, release date, etc. Only tested, confirmed and quality checked, and deployable CIs should be hold in this system.
Because of the extensive meta-data, some years ago, we created a DML depending on postgreSQL because the handling and management for the CIs along with the mandatory tracking (time when inserted, time and logging of access, access control, maybe licenses, etc.) and meta-data is much easier in a sql database. Of course, we had to build the structure for the meta-data into the sql-db, but that was not too complicated and for our straightforward DML it was sufficient. Building and managing the metadata with each ci was supposedly easier for our system than installing, configuring, learning and managing a whole third-party DML/CML system. A caveat is when we had to save whole system images from deployed, tested, already integrated and checked systems because their size were several hundreds of GB (With the newest DB-versions, this should now also be possible, the question is, if it is useful within a SQL-DB) . But we stored the disk-images on separate disks and tracked the meta-data in our tailored DML-system (our postgreSQL) along with the information where to access it.
The advantage was, that we could easily duplicate the DML and take it for example to customer, where we only had to set up or run our (postges-based) DML and were able to access all relevant CIs we needed to set up an heterogeneous network of the target system.
In other cases, maybe it is easier to rely on already existing third party solution, but the idea of a DML can be fulfilled with every storage system as long as the appropriate proecedures, meta-data, informations and access points to the overall life-cycle management are provided and maintained.
regards
A client has been referring me to their different Oracle "databases".
After a data migration mix-up, it occurred to me that these various databases are all the same database. They've just broken up the same instance with multiple users and strict permissions.
So, user1 has a CUSTOMER table, user1.CUSTOMER and user2 has a CUSTOMER table user2.CUSTOMER.
The data in those tables is completely separate, and managed by different instances of an application.
I've never seen this done before; Is this a standard, acceptable practice?
Is there a specific performance and maintenance scheme for this type of setup?
Or, is this the wild west?
thanks
This is a normal standard practice in Oracle environments. Oracle environments are one big application with one or few schemas, or a multitude of small applications grown over time.
Of course there are a number of architectural design decisions to make. For instance, when placing multiple applications in one database, the applications may influence each others. Over time, Oracle has been enhancing the technology stack to restrict the influence applications can have on each other. For instance, you can nowadays distribute the resources differently per user. But for instance an application running wild can flush the whole cache, impacting other applications. Starting with Oracle 12c, Oracle Corp. has even further improved the isolation by creating a structure that more resembles the Microsoft SQL Server approach with separate "databases", but 12c even extends that further. For instance because an Oracle container database can still contain multiple databases and it's own data dictionary (enterprise edition only allows more than 1 container database).
In general, I do not recommend putting many serious/large applications in one Oracle database. For instance, when you upgrade one of them, you need to make sure that all other applications are compatible with a possible new minor release of Oracle needed. So when you merge multiple applications in one database, make sure that you can control that they are all certified at the same time for the same Oracle version. For instance because it are inhouse packages.
I'm writing a report and thought you guys could help by providing me with the costs of company support in setting up and training a client on a data integrator for Salesforce. E.g., if someone wants to use Salesforce, but first needs a tool to consolidate and transfer data from back office systems to Salesforce how much would that support service cost?
Salesforce actually comes with a very good integration tool called Data Loader. It can be run as an interactive application under Windows or Macintosh, or it can be run as a command-line tool on Windows, Mac or Linux.
In interactive mode, it can import & export CSV files.
In batch mode it can also read data from, and write data to, a database.
For example, I have a Linux server where a daily cron job activates the Data Loader which runs several jobs. Some of these jobs run SQL against a database and upload the resulting data into Salesforce. Other jobs extract from Salesforce (using their SOQL query language, which is SQL-like) and store the information into a database.
Data Loader has a bit of a learning curve for batch mode (mostly around creating some XML configuration files), but the Interactive mode is very easy to use.
So, to answer your question... If it's a one-time data load, just run the interactive version and it's easy. If you want regularly-updated data, then use the batch mode. Support costs for operating the integration are really all in the setup. Once it's running, there shouldn't be any on-going costs unless the data structures change and you want to change the data being transferred. Better yet, if the system is setup by somebody who has done it before, you'll avoid a big learning curve.
If you want a figure to put into your report, then allow 3 days for the initial integration (allows for learning curve) and then a half-day for each additional one. That's generous, but provides extra time to debug problems.
To some degree, it depends on two factors:
Where is the data's source of truth?
How often do you want to sync the data?
If the answers are "it's a weird place and I only need to sync it once," then you probably want to figure out how to get it in CSV form and then use tools built into Salesforce to import it.
However, if the data lives in a database or data warehouse (postgres, mysql, mongo, redshift, snowflake, big query, etc) and especially if you want to keep Salesforce up to date with that source of truth continuously, then you could look into so-called "Reverse ETL" tools made for this purpose.
Costs depend on the tool chosen and the data volumes and other factors, but here are some options:
Grouparoo is an open source Reverse ETL tool. You can host it yourself for free. Paid plans start at $150/month.
Census is a SaaS Reverse ETL tool. Paid plans start at $300/month.
Hightouch is a SaaS Reverse ETL tool. Paid plans start at $350/month.
Since this doesn't touch a real problem of mine I'm somwhat uncertain, if it is even worth to be asked here. However maybe some of you would like to share your opinion on that.
In general I have to admit, that 'better' means anything and nothing at all at the same time. So I probably should be more specific, but I tried not to overflow the topic. In a regular hosted environment on one of those cheap webhosters (like Dreamhost), with around 1000 articles in Joomla, a couple of users and a few hundreds visitors a day, would a SQLite database with a persistent connection (sqlite_popen) perform noticeable faster than the MySQL equivalent (with the TCP/IP overhead etc.)?
Or in short: Would it be wise to call Joomla to support SQLite?
I have never used sqlite on a website, but I have used it extensively for other purposes and I quite like it. The truth is, you won't know till you try. If you try, I reccomend creating a db abstraction layer first so that you can easily swap in other db's.
The downside to sqlite is that it's not really meant to be a multi user database. If you rarely write to the db, but do lots of reading, sqlite will probably be fine. If you find that you need multiple processes writing to the same db, I believe sqlite uses file level locking to maintain database consistency.. So, if all you're tables are in the same file, you'll lock the whole file while it's being written to even if another process wants to modify a completely different table.
In my opinion it's not the big multi user databases of the world that should be worried about competition from sqlite... It's all the regular files out there (and there custom file formats) that applications create and use that should be shaking in their boots about sqlite...
Linux ISPs for whatever reason seem to have settled on MySQL. This is what they offer and you will lock yourself to a limited number of service providers if you wander outside the norm.
This seems to be an overlooked area that could really use some insight. What are your best practices for:
making an upgrade procedure
backing out in case of errors
syncing code and database changes
testing prior to deployment
mechanics of modifying the table
etc...
Liquibase
liquibase.org:
it understands hibernate definitions.
it generates better schema update sql than hibernate
it logs which upgrades have been made to a database
it handles two-step changes (i.e. delete a column "foo" and then rename a different column to "foo")
it handles the concept of conditional upgrades
the developer actually listens to the community (with hibernate if you are not in the "in" crowd or a newbie -- you are basically ignored.)
http://www.liquibase.org
opinion
the application should never handle a schema update. This is a disaster waiting to happen. Data outlasts the applications and as soon as multiple applications try to work with the same data ( the production app + a reporting app for example) -- chances are they will both use the same underlying company libraries... and then both programs decide to do their own db upgrade ... have fun with that mess.
I am a big fan of Red Gate products that help creating SQL packages to update database schemas. The database scripts can be added to source control to help with versioning and rollback.
In general my rule is: "The application should manage it's own schema."
This means schema upgrade scripts are part of any upgrade package for the application and run automatically when the application starts. In case of errors the application fails to start and the upgrade script transaction is not committed. The downside to this is that the application has to have full modification access to the schema (this annoys DBAs).
I've had great success using Hibernates SchemaUpdate feature to manage the table structures. Leaving the upgrade scripts to only handle actual data initialization and occasional removing of columns (SchemaUpdate doesn't do that).
Regarding testing, since the upgrades are part of the application, testing them becomes part of the test cycle for the application.
Afterthought: Taking on board some of the criticism in other posts here, note the rule says "it's own". It only really applies where the application owns the schema as is generally the case with software sold as a product. If your software is sharing a database with other software, use other methods.
That's a great question. ( There is a high chance this is going to end up a normalised versus denormalised database debate..which I am not going to start... okay now for some input.)
some off the top of my head things I have done (will add more when I have some more time or need a break)
client design - this is where the VB method of inline sql (even with prepared statements) gets you into trouble. You can spend AGES just finding those statements. If you use something like Hibernate and put as much SQL into named queries you have a single place for most of the sql (nothing worse than trying to test sql that is inside of some IF statement and you just don't hit the "trigger" criteria in your testing for that IF statement). Prior to using hibernate (or other orms') when I would do SQL directly in JDBC or ODBC I would put all the sql statements as either public fields of an object (with a naming convention) or in a property file (also with a naming convention for the values say PREP_STMT_xxxx. And use either reflection or iterate over the values at startup in a) test cases b) startup of the application (some rdbms allow you to pre-compile with prepared statements before execution, so on startup post login I would pre-compile the prep-stmts at startup to make the application self testing. Even for 100's of statements on a good rdbms thats only a few seconds. and only once. And it has saved my butt a lot. On one project the DBA's wouldn't communicate (a different team, in a different country) and the schema seemed to change NIGHTLY, for no reason. And each morning we got a list of exactly where it broke the application, on startup.
If you need adhoc functionality , put it in a well named class (ie. again a naming convention helps with auto mated testing) that acts as some sort of factory for you query (ie. it builds the query). You are going to have to write the equivalent code anyway right, just put in a place you can test it. You can even write some basic test methods on the same object or in a separate class.
If you can , also try to use stored procedures. They are a bit harder to test as above. Some db's also don't pre-validate the sql in stored procs against the schema at compile time only at run time. It usually involves say taking a copy of the schema structure (no data) and then creating all stored procs against this copy (in case the db team making the changes DIDn't validate correctly). Thus the structure can be checked. but as a point of change management stored procs are great. On change all get it. Especially when the db changes are a result of business process changes. And all languages (java, vb, etc get the change )
I usually also setup a table I use called system_setting etc. In this table we keep a VERSION identifier. This is so that client libraries can connection and validate if they are valid for this version of the schema. Depending on the changes to your schema, you don't want to allow clients to connect if they can corrupt your schema (ie. you don't have a lot of referential rules in the db, but on the client). It depends if you are also going to have multiple client versions (which does happen in NON - web apps, ie. they are running the wrong binary). You could also have batch tools etc. Another approach which I have also done is define a set of schema to operation versions in some sort of property file or again in a system_info table. This table is loaded on login, and then used by each "manager" (I usually have some sort of client side api to do most db stuff) to validate for that operation if it is the right version. Thus most operations can succeed, but you can also fail (throw some exception) on out of date methods and tells you WHY.
managing the change to schema -> do you update the table or add 1-1 relationships to new tables ? I have seen a lot of shops which always access data via a view for this reason. This allows table names to change , columns etc. I have played with the idea of actually treating views like interfaces in COM. ie. you add a new VIEW for new functionality / versions. Often, what gets you here is that you can have a lot of reports (especially end user custom reports) that assume table formats. The views allow you to deploy a new table format but support existing client apps (remember all those pesky adhoc reports).
Also, need to write update and rollback scripts. and again TEST, TEST, TEST...
------------ OKAY - THIS IS A BIT RANDOM DISCUSSION TIME --------------
Actually had a large commercial project (ie. software shop) where we had the same problem. The architecture was a 2 tier and they were using a product a bit like PHP but pre-php. Same thing. different name. anyway i came in in version 2....
It was costing A LOT OF MONEY to do upgrades. A lot. ie. give away weeks of free consulting time on site.
And it was getting to the point of wanting to either add new features or optimize the code. Some of the existing code used stored procedures , so we had common points where we could manage code. but other areas were this embedded sql markup in html. Which was great for getting to market quickly but with each interaction of new features the cost at least doubled to test and maintain. So when we were looking at pulling out the php type code out, putting in data layers (this was 2001-2002, pre any ORM's etc) and adding a lot of new features (customer feedback) looked at this issue of how to engineer UPGRADES into the system. Which is a big deal, as upgrades cost a lot of money to do correctly. Now, most patterns and all the other stuff people discuss with a degree of energy deals with OO code that is running, but what about the fact that your data has to a) integrate to this logic, b) the meaning and also the structure of the data can change over time, and often due to the way data works you end up with a lot of sub process / applications in your clients organisation that needs that data -> ad hoc reporting or any complex custom reporting, as well as batch jobs that have been done for custom data feeds etc.
With this in mind i started playing with something a bit left of field. It also has a few assumptions. a) data is heavily read more than write. b) updates do happen, but not at bank levels ie. one or 2 a second say.
The idea was to apply a COM / Interface view to how data was accessed by clients over a set of CONCRETE tables (which varied with schema changes). You could create a seperate view for each type operation - update, delete, insert and read. This is important. The views would either map directly to a table , or allow you to trigger of a dummy table that does the real updates or inserts etc. What i actually wanted was some sort of trappable level indirection that could still be used by crystal reports etc. NOTE - For inserts , update and deletes you could also use stored procs. And you had a version for each version of the product. That way your version 1.0 had its version of the schema, and if the tables changed, you would still have the version 1.0 VIEWS but with NEW backend logic to map to the new tables as needed, but you also had version 2.0 views that would support new fields etc. This was really just to support ad hoc reporting, which if your a BUSINESS person and not a coder is probably the whole point of why you have the product. (your product can be crap but if you have the best reporting in the world you can still win, the reverse is true - your product can be the best feature wise, but if its the worse on reporting you can very easily loose).
okay, hope some of those ideas help.
These are all weighty topics, but here is my recommendation for updating.
You did not specify your platform, but for NANT build environments I use Tarantino. For every database update you are ready to commit, you make a change script (using RedGate or another tool). When you build to production, Tarantino checks if the script has been run on the database (it adds a table to your database to keep track). If not, the script is run. It takes all the manual work (read: human error) out of managing database versions.
I've heard good things about iBATIS 3 Schema Migrations System:
User Guide: http://svn.apache.org/repos/asf/ibatis/java/ibatis-3/trunk/doc/en/iBATIS-3-Migrations.pdf
As Pat said, use liquibase. Especially when you have several developers with their own dev databases
making changes that will become part of the production database.
If there's only one dev, as on one project I'm on now(ha), I just commit the schema changes as SQL text files into a CVS repo, which I check out in batches on the production server when the code changes go in.
But liquibase is better organized than that!