I am not sure how to ask this question so please direct me in the right direction if I am not using the appropriate terminology, etc. but I can explain what I am currently doing. I would like to know if there is an easier way to update content in the database than the method I'm currently using.
(I'm using SQL Server 2008 BTW.)
I have a bunch of CSV files that I use to give to my client as a means to update content which gets imported into the DB (because the content is LARGE). The import works by running a python script that I wrote that makes use of a Jinja2 template that generates the SQL file needed to insert the CSV content into the database (if it is a from-scratch scenario). This is working fine.
Now when it comes to data migration (I need to migrate the data that exists in the DB to a new version thereof) I have a lot of manual work (I hand code it in the template, there is no SQL command or auto-generated code that I can run to do this for me) to do.
So lets say I have a list of Hospitals in a CSV file and I already have a set of hospitals in the database (which is imported from the previous version of the CSV file). I create a copy of the Hospitals table (without the data) and call it HospitalsTemp. The new CSV hospitals are inserted into the HospitalsTemp table (at least that part is generated via the template).
The Hospitals table now gets detached from all its foreign-keys and constraints. Now I go through all the tables surrounding the Hospitals (again manually!) and replace the hospitalId which pointed to the old hospitalId with the new hospitalId (as I can do a lookup from the Hospitals to the HospitalsTemp based on the hospital code to ensure that referential integrity is retained).
Then I delete the Hospitals table and rename the HospitalsTemp to Hospitals and put back the foreign-keys and constraints on the new Hospitals table.
I hope I explained it well enough for everyone to understand. I'm really hoping for a simpler way to do this.
How do you know which hospital becomes which, do the names stay the same? Is there an Id that stays the same?
Have you looked at SSIS, and the Slowly Changing Dimension component? You can use it to update existing rows and add new rows: http://blogs.msdn.com/b/karang/archive/2010/09/29/slowly-changing-dimension-using-ssis.aspx
Also SSIS would be a good tool for the import, as it handles reading CSV files well.
You could replace the current logic with simple SSIS package that's just a flat-file data source and the output of the SCD wizard by the sounds of it?
Related
Problem:
I need to get data sets from CSV files into SQL Server Express (SSMS v17.6) as efficiently as possible. The data sets update daily into the same CSV files on my local hard drive. Currently using MS Access 2010 (v14.0) as a middleman to aggregate the CSV files into linked tables.
Using the solutions below, the data transfers perfectly into SQL Server and does exactly what I want. But I cannot figure out how to refresh/update/sync the data at the end of each day with the newly added CSV data without having to re-import the entire data set each time.
Solutions:
Upsizing Wizard in MS Access - This works best in transferring all the tables perfectly to SQL Server databases. I cannot figure out how to update the tables though without deleting and repeating the same steps each day. None of the solutions or links that I have tried have panned out.
SQL Server Import/Export Wizard - This works fine also in getting the data over to SSMS one time. But I also cannot figure out how to update/sync this data with the new tables. Another issue is that choosing Microsoft Access as the data source through this method requires a .mdb file. The latest MS Access file formats are .accdb files so I have to save the database in an older .mdb version in order to export it to SQL Server.
Constraints:
I have no loyalty towards MS Access. I really am just looking for the most efficient way to get these CSV files consistently into a format where I can perform SQL queries on them. From all I have read, MS Access seems like the best way to do that.
I also have limited coding knowledge so more advanced VBA/C++ solutions will probably go over my head.
TLDR:
Trying to get several different daily updating local CSV files into a program where I can run SQL queries on them without having to do a full delete and re-import each day. Currently using MS Access 2010 to SQL Server Express (SSMS v17.6) which fulfills my needs, but does not update daily with the new data without re-importing everything.
Thank you!
You can use a staging table strategy to solve this problem.
When it's time to perform the daily update, import all of the data into one or more staging tables. Execute SQL statement to insert rows that exist in the imported data but not in the base data into the base data; similarly, delete rows from the base data that don't exist in the imported data; similarly, update base data rows that have changed values in the imported data.
Use your data dependencies to determine in which order tables should be modified.
I would run all deletes first, then inserts, and finally all updates.
This should be a fun challenge!
EDIT
You said:
I need to get data sets from CSV files into SQL Server Express (SSMS
v17.6) as efficiently as possible.
The most efficient way to put data into SQL Server tables is using SQL Bulk Copy. This can be implemented from the command line, an SSIS job, or through ADO.Net via any .Net language.
You state:
But I cannot figure out how to refresh/update/sync the data at the end
of each day with the newly added CSV data without having to re-import
the entire data set each time.
It seems you have two choices:
Toss the old data and replace it with the new data
Modify the old data so that it comes into alignment with the new data
In order to do number 1 above, you'd simply replace all the existing data with the new data, which you've already said you don't want to do, or at least you don't think you can do this efficiently. In order to do number 2 above, you have to compare the old data with the new data. In order to compare two sets of data, both sets of data have to be accessible wherever the comparison is to take place. So, you could perform the comparison in SQL Server, but the new data will need to be loaded into the database for comparison purposes. You can then purge the staging table after the process completes.
In thinking further about your issue, it seems the underlying issue is:
I really am just looking for the most efficient way to get these CSV
files consistently into a format where I can perform SQL queries on
them.
There exist applications built specifically to allow you to query this type of data.
You may want to have a look at Log Parser Lizard or Splunk. These are great tools for querying and digging into data hidden inside flat data files.
An Append Query is able to incrementally add additional new records to an existing table. However the question is whether your starting point data set (CSV) is just new records or whether that data set includes records already in the table.
This is a classic dilemma that needs to be managed in the Append Query set up.
If the CSV includes prior records - then you have to establish the 'new records' data sub set inside the CSV and append just those. For instance if you have a sequencing field then you can use a > logic from the existing table max. If that is not there then one would need to do a NOT compare of the table data with the csv data to identify which csv records are not already in the table.
You state you seek something 'more efficient' - but in truth there is nothing more efficient than a wholesale delete of all records and write of all records. Most of the time one can't do that - but if you can I would just stick with it.
We're developing a Doctrine backed website using YAML to define our schema. Our schema changes regularly (including fk relations) so we need to do a lot of:
Doctrine::generateModelsFromYaml(APPPATH . 'models/yaml', APPPATH . 'models', array('generateTableClasses' => true));
Doctrine::dropDatabases();
Doctrine::createDatabases();
Doctrine::createTablesFromModels();
We would like to keep existing data and store it back in the re-created database. So I copy the data into a temporary database before the main db is dropped.
How do I get the data from the "old-scheme DB copy" to the "new-scheme DB"? (the new scheme only contains NEW columns, NO COLUMNS ARE REMOVED)
NOTE:
This obviously doesn't work because the column count doesn't match.
SELECT * FROM copy.Table INTO newscheme.Table
This obviously does work, however this is consuming too much time to write for every table:
SELECT old.col, old.col2, old.col3,'somenewdefaultvalue' FROM copy.Table as old INTO newscheme.Table
Have you looked into Migrations? They allow you to alter your database schema in programmatical way. WIthout losing data (unless you remove colums, of course)
How about writing a script (using the Doctrine classes for example) which parses the yaml schema files (both the previous version and the "next" version) and generates the sql scripts to run? It would be a one-time job and not require that much work. The benefit of generating manual migration scripts is that you can easily store them in the version control system and replay version steps later on. If that's not something you need, you can just gather up changes in the code and do it directly through the database driver.
Of course, the more fancy your schema changes becomes, the harder the maintenance will get i.e. column name changes, null to not null etc.
I have got a backup of a live database (A copy of an ACCDB format Access database) in which I've worked, added new fields to existing tables and whole new tables.
How do I get these changes and apply that fast in the running database?
In MS SQL Server, I'd right-click > Script Table As > Alter To, save the query and run it wherever I desire, is there an as easy way as that to do it in an Access Database ?
Details:
It's an ACCDB MS-Access database created on Access 2007, copied and edited in Access 2007, in which I need to get some "alter" scripts to run on the other database so that it has all the new columns and tables I've created on my copy.
For new tables, just import them from one database into the other. In the "External Data" section of the ribbon, choose the Access icon above "Import". That choice starts an import wizard to allow you to select which objects you want imported. You will have a choice to import just the table structure, or both structure and data.
Remou is right that you can use DDL ALTER TABLE statements to add new columns. However, DDL might not support every feature you want for your new columns. And if you want not just the empty columns added, but also also any data from those new columns, you will probably need to run UPDATE statements to get it into your new columns.
As far as "Script Table As", see if OmBelt's Export Table to SQL tool for MS Access can do what you want.
Edit: Allen Browne has sample ALTER TABLE statements. See CreateFieldDDL and the following one, CreateFieldDDL2.
You can run DDL in Access. I think it would be easiest to run the SQL with VBA, in this case.
There is a product called DbWeigher that can compare Access database schemas and synchronize them. You can get a free trial (30 days). DbWeigher will write a script of all schema differences and write it out as DDL. The script is thorough and includes relationships, indexes, validation rules, allow zero length, etc.
A free tool from the same developer, DBWConsole, will let you execute a DDL script against any Access database. If you wrote your own DDL scripts this would be an easy way to apply the changes to your live database. It even handles some DDL that I don't know how to process in VBA (so it must be magic). DBWConsole is included if you downloaded the trial version of DBWeigher. Be aware that you can't make schema changes to a table in a shared Access database if anyone has the table open.
DbWeigher creates a script of all differences between the two files. It can be a lot to manually parse through if you just want a few of the changes. I built a parser for DbWeigher script files so they could be filtered by table, to extract just the parts I wanted. I contacted the DbWeigher author about it but never heard back. It's safe to say that I have no affiliation with this developer.
I've been writing a Library management Java app lately, and, up until now, the main Library database is stored in a .txt file which was later converted to ArrayList in Java for creating and editing the database and saving the alterations back to the .txt file again. A very primitive method indeed. Hence, having heard on SQL later on, I'm considering to port my preexisting .txt database to mySQL. Since I've absolutely no idea how SQL and specifically mySQL works, except for the fact that it can interact with Java code. Can you suggest me any books/websites to visit/buy? Will the book Head First with SQL ever help? especially when using Java code to interact with the SQL database? It should be mentioned that I'm already comfortable with using 3rd Party APIs.
View from 30,000 feet:
First, you'll need to figure out how to represent the text file data using the appropriate SQL tables and fields. Here is a good overview of the different SQL data types. If your data represents a single Library record, then you'll only need to create 1 table. This is definitely the simplest way to do it, as conversion will be able to work line-by-line. If the records contain a LOT of data duplication, the most appropriate approach is to create multiple tables so that your database doesn't duplicate data. You would then link these tables together using IDs.
When you've decided how to split up the data, you create a MySQL database, and within that database, you create the tables (a database is just something that holds multiple tables). Connecting to your MySQL server with the console and creating a database and tables is described in this MySQL tutorial.
Once you've got the database created, you'll need to write the code to access the database. The link from OMG Ponies shows how to use JDBC in the simplest way to connect to your database. You then use that connection to create Statement object, execute a query to insert, update, select or delete data. If you're selecting data, you get a ResultSet back and can view the data. Here's a tutorial for using JDBC to select and use data from a ResultSet.
Your first code should probably be a Java utility that reads the text file and inserts all the data into the database. Once you have the data in place, you'll be able to update the main program to read from the database instead of the file.
Know that the connection between a program and a SQL database is through a 'connection program'. You write an instruction in an SQL statement, say
Select * from Customer order by name;
and then set up to retrieve data one record at a time. Or in the other direction, you write
Insert into Customer (name, addr, ...) values (x, y, ...);
and either replace x, y, ... with actual values or bind them to the connection according to the interface.
With this understanding you should be able to read pretty much any book or JDBC API description and get started.
I have an Excel spreadsheet with a few thousand entries in it. I want to import the table into a MySQL 4 database (that's what I'm given). I am using SQuirrel for GUI access to the database, which is being hosted remotely.
Is there a way to load the columns from the spreadsheet (which I can name according to the column names in the database table) to the database without copying the contents of a generated CSV file from that table? That is, can I run the LOAD command on a local file instructing it to load the contents into a remote database, and what are the possible performance implications of doing so?
Note, there is a auto-generated field in the table for assigning ids to new values, and I want to make sure that I don't override that id, since it is the primary key on the table (as well as other compound keys).
If you only have a few thousand entries in the spreadsheet then you shouldn't have performance problems (unless each row is very large of course).
You may have problems with some of the Excel data, e.g. currencies, best to try it and see what happens.
Re-reading your question, you will have to export the Excel into a text file which is stored locally. But there shouldn't be any problems loading a local file into a remote MySQL database. Not sure whether you can do this with Squirrel, you would need access to the MySQL command line to run the LOAD command.
The best way to do this would be to use Navicat if you have the budget to make a purchase?
I made this tool where you can paste in the contents of an Excel file and it generates the create table, and insert statements which you can then just run. (I'm assuming squirrel lets you run a SQL script?)
If you try it, let me know if it works for you.