Is there a way to programmatically check for database object corruption in Access 2003?
My development project has gotten complex enough that it's hard to manually check all the objects after a day of programming to see if some small control, form, report, query, or code object has been corrupted somehow. I already have the data split off into a separate SQL Database stored on another machine, and this project is merely a front-end application to work with the data.
Mostly an academic musing, as I just don't want to get so far - then have corruption put me back several weeks because some seldom used object got corrupted way back when.
Any ideas out there? Thanks in advance for any pointers!
EDITED 12/03/2009 # 11:51
Sadly, I can only accept one answer - though I got a few very good ones, thank you for all the pointers!
You might like to look at: Is it possible to programmatically detect corrupt Access 2007 database tables?
I am inclined to keep a copy of important databases at each compact & repair and to compare the new database against the previous one. You can also check for non-standard characters.
Neither Compact/Repair nor Decompile/Recompile catches all corruption problems, although you should be doing this anyway.
I use a function to export all Container Docs (and QueryDefs) using SaveAsText into a date/time stamped folder, and use it regularly throughout the day. If I suspect any corruption, I create a new mdb, and use LoadFromText to recreate the objects.
Proper compilation practices will prevent corruption of the VBA project (which is what you're talking about here).
That entails:
use OPTION EXPLICIT in all modules.
turn off COMPILE ON DEMAND in the VBE options.
compile your code regularly, while working.
periodically (e.g., once a day after a full day of coding) decompile and recompile the code.
If you do this, you'll never encounter corruption in the first place so you won't need to test for it (which is impossible in the first place).
Related
I am working using Tableau and have to write down multiple different SQL each time, while making new data sources.
I have to save all changes on SQL for every data source.
Currently I would paste the SQL on notepad and save them on separate folder in my computer, along with description of the changes.
Is there any better way to do this?
Assuming you have permission to create objects in the database, begin by creating database views, As #Nick.McDermaid commented.
Then, instead of using Custom SQL data source in Tableau, just connect to the View as if it were a table.
If you need to track the changes to these SQL views of your data, you will need to learn how to use source control for the .sql files that can be scripted from within SQL Server Management Studio:
Your company or school may have a preferred source control system already in use, in which case you should use that. If they don't, or if you are learning at home, then Git and Subversion are popular open source choices.
There are many courses available on learning platforms like Coursera that will teach you how to learn how to use those systems.
I had similar problem as you.
We ended up writing the queries in SQL Editor SQL Work bench (https://www.sql-workbench.eu/), then managed the code history and performed code peer-review (logic, error check, etc) in team shared space (like confluence).
The reasons we did that is
1) SQL queries are much easy to write on Work Bench
2) Code review is a must! You will find through implementing a review process more mistakes than you could ever think about
3) The shared space is just really convenient as it is accessible by everyone, and all errors are documented. After sometimes you get a lot of visible knowledge accumulated.
I also totally agree with Nick as this is one step to a reporting solution. But developing a whole reporting server is heavy, costly and takes time. Unless management are really convinced of the importance of developing a reporting solution, you may have to get a workaround with queries and Tableau (at least that was the case for us)
A little late to the party, but I would suggest you simply version the tableau workbook. The contents of the workbook are XML, so perfect for versioning using file based tools (Dropbox, One Drive, etc.) or source control (git, etc.). The workbooks themselves are usually quite small, so just make sure to keep the extract data separate if you use it.
Is it possible to use Npgsql in a way that basically mimics pg_dumpall to a single output file without having to iterate through each table in the database? Conversely, I'd also like to be able to take such output and use Npgsql to restore an entire database if possible.
I know that with more recent versions of Npgsql I can use the BeginBinaryExport, BeginTextExport, or BeginRawBinaryCopy methods to export from the database to STDOUT or to a file. On the other side of the process, I can use the BeginBinaryImport, BeginTextImport, or BeginRawBinaryCopy methods to import from STDIN or an existing file. However, from what I've been able to find so far, these methods use the COPY SQL syntax, which (AFAIK) is limited to a single table at a time.
Why am I asking this question? I currently have an old batch file that I use to export my production database to a file (using pg_dumpall.exe) before importing it back into my testing environment (using psql.exe with the < operation). This has been working pretty much flawlessly for quite a while now, but we've recently moved the server to an off-site hosted environment, which is causing a delay that prevents the batch file from completing successfully. Because of the potential for other connectivity/timeout issues, I'm thinking of moving the batch file's functionality to a .NET application, but this part has got me a bit stumped.
Thanks for your help and let me know if you need any further clarification.
This has been asked for in https://github.com/npgsql/npgsql/issues/1397.
Long story short, Npgsql doesn't have any sort of support for dumping/restoring entire databases. Implementing that would be a pretty significant effort that would pretty much duplicate all the pg_dump logic, and the danger for subtle omissions and bugs would be considerable.
If you just need to dump data for some tables, then as you mentioned, the COPY API is pretty good for that. If, however, you need to also save the schema itself as well as other, non-table entities (sequence state, extensions...), then the only current option AFAIK is to execute pg_dump as an external process (or use one of the other backup/restore options).
Most of my day is spent on writing SQL queries to perform small tasks, mainly to get information from the database and manipulate it somehow for data visualization building reports for others.
At the end of the day i try to have a nice folder scheme to help me reusing code and so on, but it's becoming harder to handle so many files and keep
track of everything I've done so far.
Don't want to have huge SQL files because I might want to
the end It's hard to avoid a war zone in my desktop and on this folders. It's also a mess to handle so many folders/codes.
For version control we're using a GIT server, but there is plenty of code that is not in production that we would like to keep track and reuse somehow.
We're using iPython notebook, R studio and SSMS to build our codes, I'm wonder if there is some efficient ways to work.
There must be an efficient way to work out there. What do you use to keep track of your (SQL) codes? and more importantly reuse it.
Thanks in advance,
Rafael
I just use a folder system. And I keep the shell-scripts so to speak as the first file (like the generic code to do X). Whereas the specific codes where I take X and apply dates and other conditions in the bottom half of the folder.
What do you use to keep track of your (SQL) codes? and more importantly reuse it.
For ease of reuse, I have all my running SQL code backed up on an SQL server through routine INFORMATION SCHEMA dumps. For all development code that I need to reuse with others, I have a GIT server that gets automatic updates throughout the day. For reuse on my laptop itself, I have a local backup through time machine.
As for directory or folder structure, all code starts as project based and eventually I migrate the best and most useful code to a personal folder structure that is topic based (date arithmetic, indexing, etc.). No matter how they are stored, all these folders are indexed using local and remote indexing features so I can search and retrieve them with just a few keystrokes when needed. Ultimately what's needed for optimum reuse is ease of retrieval. The quicker I can retrieve, the more reuse I get.
Lastly, it's not just SQL code, but all the supporting documents that led to that code solution. Sometimes this collection may include code from other languages, code from other servers, emails, text documents, images, workflows, etc. Keeping them all together enhances the value of reuse.
I'm working on an ASP.net web application that uses SQL as a database back-end. One issue that I have is that it sometimes takes a while to get my DBA to create or modify tables in the database which under no circumstance am I allowed to modify on my own.
Here is something that I do is when I expect users to upload files with their data.
Suppose the user uploads a new record for a table called Student_Records. The user uploads a record with fname Bob and lname Smith. The record is assigned primary key 123 The user also uploads two files: attendance_record.pdf and homework_record.pdf. Let's suppose that I have a network share: \\foo\bar where the files are saved.
One way of handling this situtation would be to have a table Student_Records_Files that associates the key 123 with Bob Smith. However, since I have trouble getting tables created, I've gone and done something different: When I save the files on the server, I call them 123_attendance_record.pdf and 123_homework_record.pdf. That way, I can easily identify what table record each file is associated with without having to create a new SQL table. I am, in essence, using the file system itself as a join table (Obviously, the file system is a type of database).
In my code for retrieving the files, I scan the directory \\foo\bar and look for files that begin with each primary key number from Student_Records.
It seems to work very well, but is it good practice?
There is nothing wrong with using the file system to store files. It's what it is used for.
There are a few things to keep in mind though.
I would consider a better method of storing the files - perhaps a directory for each user, rather than simply appending the user id to the filename.
Ensure that the file store is resilient and backed up with the same regularity as your database. If your database is configured to give you a backup every 10 minutes, but your file store only does a backup every day (or worse week) then you might be in for a world of pain.
Also consider what would happen if the user uploads two documents that are the same name.
First of all, I think it's a bad practice, in general, to design your architecture based on how responsive your DBA is. Any given compromise based on this approach may or may not be a big deal, but over time it will result in a poorly designed system.
Second, making the file name this critical seems dangerous to me; there's no protection against a person or application modifying the filename without realizing its importance.
Third, one of the advantages of having a table to maintain the join between the person and the file is that you can add additional data, such as: when was the file uploaded, what is the MIME type, has the file been read by anyone through the system, is this file a newer version of a previous file, etc. etc. Metadata can be very powerful, and the filesystem offers only limited ways to store it.
There are really two questions here. One is, given that for administrative reasons you cannot get changes made to the database schema, is it acceptable to devise some workaround. To that I'd have to say yes. What else can you do? In theory, if it takes two weeks to get the DBA to make a schema change for you, then this two weeks should be added to any deadline that you are given. In practice, this almost never happens. I've often worked places where some paperwork or whatever required two weeks before I could even begin work, and then I'd be given two weeks and one day to do the project. Sometimes you just have to put it together with rubber bands and bandaids.
Two is, is it a good idea to build a naming convention into file names and use this to identify files and their relationship to other data. I've done this at times and it's generally worked for me, though I have a perhaps irrational emotional feeling that it's not a good idea.
On the plus side, (a) By building information into a file name, you make it easy for both the computer and a human being to identify file associations. (Human readable as long as the naming convention is straightforward enough, anyway.) (b) By eliminating the separate storage of a link, you eliminate the possibility of a bad link. A file with the appropriate name may not exist, of course, but a database record with appropriate keys may not exist, or the file reference in such a record may be null or invalid. So it seems to solve one problem there without creating any new problems.
Potential minuses are: (a) You may have characters in the key that are not legal in file names. You may be able to just strip such characters out, or this may cause duplicates. The only safe thing to do is to escape them in some way, which is a pain. (b) You may exceed the legal length of a file name. Not as much of an issue as it was in the bad old 8.3 days. (c) You can't share files. If a database record points to a file, then two db records could point to the same file. If you must make two copies of a file, not only does this waste disk space, but it also means that if the file is updated, you must be sure to update all copies. If in your application it would make no sense to share files, than this isn't an issue.
You have to manage the files in some way, but you had to do that anyway.
I really can't think of any over-riding minuses. As I say, I've done this on occassion and didn't run into any particular problems. I'm interested in seeing others' responses.
I think it is not good practice because you are making your working application very dependent on specific implementation details and it would make it pretty hard to work with in the future to maintain, or if other people later needed access to your code/api.
Now weather you should do this or not is a whole different question. If you are really taking that much of a performance hit and it is significantly easier to work with how you have it, then I would say go ahead and break the rules. Ideally its good to follow best practice methods, but sometimes you have to bend the rules a little to make things work.
First, why is this a table change as opposed to a data change? Once you have the tables set up you should only need to update rows in that table every time that a user adds new files. If you have to put up with this one-time, two-week delay then bite the bullet and just get it done right.
Second, instead of trying to work around the problem why don't you try to fix the problem? Why is the process of implementing table changes so slow? Are you at least able to work on a development database (in which you have control to test and try out these changes)? Even if it's your own laptop you can at least continue on with development. Work with your manager, the DBA, and whoever else you need to, in order to improve the process. Would it help to speed things up if your scripts went through a formal testing process before you handed them off to the DBA so that he doesn't need to test the scripts, etc. himself?
Third, if this is a production database then you should probably be building in this two-week delay into your development cycle. You know that it takes two weeks for the DBA to review and implement changes in production, so make sure that if you have a deadline for releasing functionality that you have enough lead time for it.
Building this kind of "data" into a filename has inherent problems as others have pointed out. You have no relational integrity guarantees and the "data" can be changed without knowledge of the rest of the application/database.
It's best to keep everything in the database.
Network file I/O is spotty at best. In addition, its slower than the DB I/O.
If the DBA is difficult in getting small changes into the database, you
may be dealing with:
A political control issue. Maybe he just knows DB stuff and is threatened
when he perceives others moving in on his turf. Whatever his reasons, you need
to GET WORK DONE. Period. Document all the extra time / communication / work
you need to do for each small change and take that up with the management.
If the first level of management is unwilling to see things your way,
(it does not matter what their reasons are), escalate the issue
to the next level of management. In the past, I've gotten results this way.
It was more of a political territory problem than a technical problem.
The DBA eventually gave up and gave me full access to the TEST system BUT
he also stipulated that I would need to learn his testing process,
naming convention, his DB standards and practices, his way of testing, etc.
I was game.
I would also need to fix any database problems arising from changes I introduced.
This was fair and I got to wear the DBA hat in addition to the developer hat.
I got the freedom I needed and he got one less thing to worry about.
A process issue. Maybe the DBA needs to put every small DB change you submit
through a gauntlet of testing and performance analysis. Maybe he has a highly
normalized DB schema and because he has the big picture, he needs to normalize or
denormalize your requested DB changes to fit into the existing schema.
Ask to work with him. Ask him for a full DB design diagram.
Get a good sense of his DB design philosophy. Implement your DB changes with
his DB design philosophy in mind. Show that you understand that he's trying
to keep the DB in good order (understand normalization, relational constraints,
check constraints) Give him less to worry about. He needs to trust that you
will not muck up his database.
Accumulate all the small changes into a lengthy script and submit them to the DBA.
This way, you won't have to wait for each small change to go through all of his
process / testing. In addition, you're giving him a bigger picture view of your
development planning (that is in step with his DB design philosophy) instead of
just the play by play.
For most database-backed projects I've worked on, there is a need to get "startup" or test data into the database before deploying the project. Examples of startup data: a table that lists all the countries in the world or a table that lists a bunch of colors that will be used to populate a color palette.
I've been using a system where I store all my startup data in an Excel spreadsheet (with one table per worksheet), then I have a utility script in SQL that (1) creates the database, (2) creates the schemas, (3) creates the tables (including primary and foreign keys), (4) connects to the spreadsheet as a linked server, and (5) inserts all the data into the tables.
I mostly like this system. I find it very easy to lay out columns in Excel, verify foreign key relationships using simple lookup functions, perform concatenation operations, copy in data from web tables or other spreadsheets, etc. One major disadvantage of this system is the need to sync up the columns in my worksheets any time I change a table definition.
I've been going through some tutorials to learn new .NET technologies or design patterns, and I've noticed that these typically involve using Visual Studio to create the database and add tables (rather than scripts), and the data is typically entered using the built-in designer. This has me wondering if maybe the way I'm doing it is not the most efficient or maintainable.
Questions
In general, do you find it preferable to build your whole database via scripts or a GUI designer, such as SSMSE or Visual Studio?
What method do you recommend for populating your database with startup or test data and why?
Clarification
Judging by the answers so far, I think I should clarify something. Assume that I have a significant amount of data (hundreds or thousands of rows) that needs to find its way into the database. This data could be sourced from various places, such as text files, spreadsheets, web tables, etc. I've received several suggestions to script this process using INSERT statements, but is this really viable when you're talking about a lot of data?
Which leads me to...
New questions
How would you write a SQL script to take the country data on this page and insert it into the database?
With Excel, I could just copy/paste the table into a worksheet and run my utility script, and I'd basically be done.
What if you later realized you needed a new column, CapitalCity?
With Excel, I could take that information from this page, paste it into Excel, and with a quick text-to-column manipulation, I'd have the data in the format I need.
I honestly didn't write this question to defend Excel as the best way or even a good way to get data into a database, but the answers so far don't seem to be addressing my main concern--how to get all this data into your database. Writing a script with hundreds of INSERT statements by hand would be extremely time consuming and error prone. Somehow, this script needs to be machine generated, but how?
I think your current process is fine for seeding the database with initial data. It's simple, easy to maintain, and works for you. If you've got a good database design with adequate constraints then it doesn't really matter how you seed the initial data. You could use an intermediate tool to generate scripts but why bother?
SSIS has a steep learning curve, doesn't work well with source control (impossible to tell what changed between versions), and is very finicky about type conversions from Excel. There's also an issue with how many rows it reads ahead to determine the data type -- you're in deep trouble if your first x rows contain numbers stored as text.
1) I prefer to use scripts for several reasons.
• Scripts are easy to modify, and plus when I get ready to deploy my application to a production environment, I already have the scripts written so I'm all set.
• If I need to deploy my database to a different platform (like Oracle or MySQL) then it's easy to make minor modifications to the scripts to work on the target database.
• With scripts, I'm not dependent on a tool like Visual Studio to build and maintain the database.
2) I like good old fashioned insert statements using a script. Again, at deployment time scripts are your best friend. At our shop, when we deploy our applications we have to have scripts ready for the DBA's to run, as that's what they expect.
I just find that scripts are simple, easy to maintain, and the "least common denominator" when it comes to creating a database and loading up data to it. By least common denominator, I mean that the majority of people (i.e. DBA's, other people in your shop that might not have visual studio) will be able to use them without any trouble.
The other thing that's important with scripts is that it forces you to learn SQL and more specfically DDL (data definition language). While the hand-holding GUI tools are nice, there's no substitute for taking the time to learn SQL and DDL inside out. I've found that those skills are invaluable to have in almost any shop.
Frankly, I find the concept of using Excel here a bit scary. It obviously works, but it's creating a dependency on an ad-hoc data source that won't be resolved until much later. Last thing you want is to be in a mad rush to deploy a database and find out that the Excel file is mangled, or worse, missing entirely. I suppose the severity of this would vary from company to company as a function of risk tolerance, but I would be actively seeking to remove Excel from the equation, or at least remove it as a permanent fixture.
I always use scripts to create databases, because scripts are portable and repeatable - you can use (almost) the same script to create a development database, a QA database, a UAT database, and a production database. For this reason it's equally important to use scripts to modify existing databases.
I also always use a script to create bootstrap data (AKA startup data), and there's a very important reason for this: there's usually more scripting to be done afterward. Or at least there should be. Bootstrap data is almost invariably read-only, and as such, you should be placing it on a read-only filegroup to improve performance and prevent accidental changes. So you'll generally need to script the data first, then make the filegroup read-only.
On a more philosophical level, though, if this startup data is required for the database to work properly - and most of the time, it is - then you really ought to consider it part of the data definition itself, the metadata. For that reason, I don't think it's appropriate to have the data defined anywhere but in the same script or set of scripts that you use to create the database itself.
Test data is a little different, but in my experience you're usually trying to auto-generate that data in some fashion, which makes it even more important to use a script. You don't want to have to manually maintain an ad-hoc database of millions of rows for testing purposes.
If your problem is that the test or startup data comes from an external source - a web page, a CSV file, etc. - then I would handle this with an actual "configuration database." This way you don't have to validate references with VLOOKUPS as in Excel, you can actually enforce them.
Use SQL Server Integration Services (formerly DTS) to pull your external data from CSV, Excel, or wherever, into your configuration database - if you need to periodically refresh the data, you can save the SSIS package so it ends up being just a couple of clicks.
If you need to use Excel as an intermediary, i.e. to format or restructure some data from a web page, that's fine, but the important thing IMO is to get it out of Excel as soon as possible, and SSIS with a config database is an excellent repeatable method of doing that.
When you are ready to migrate the data from your configuration database into your application database, you can use SQL Server Management Studio to generate a script for the data (in case you don't already know - when you right click on the database, go to Tasks, Generate Scripts, and turn on "Script Data" in the Script Options). If you're really hardcore, you can actually script the scripting process, but I find that this usually takes less than a minute anyway.
It may sound like a lot of overhead, but in practice the effort is minimal. You set up your configuration database once, create an SSIS package once, and refresh the config data maybe once every few months or maybe never (this is the part you're already doing, and this part will become less work). Once that "setup" is out of the way, it's really just a few minutes to generate the script, which you can then use on all copies of the main database.
Since I use an object-relational mapper (Hibernate, there is also a .NET version), I prefer to generate such data in my programming language. The ORM then takes care of writing things into the database. I don't have to worry about changing column names in the data because I need to fix the mapping anyway. If refactoring is involved, it usually takes care of the startup/test data also.
Excel is an unnecessary component of this process.
Script the current version the database components that you want to reuse, and add the script to your source control system. When you need to make changes in the future, either modify the entities in the database and regenerate the script, or modify the script and regenerate the database.
Avoid mixing Visual Studio's db designer and Excel as they only add complexity. Scripts and SQL Management Studio are your friends.