I am using hibernate to map my classes to oracle database. But when I try to insert something ,get:
java.sql.BatchUpdateException: ORA-12899: value too large for column
I used hibernate tool to generate this table, is there anyway I can manually change the setting of the column size?
I tried to set the length="1000" in hbm.xml file and #Column(length=1000) in object class, but those are not working.
Thank you.
How large is your actual value? You might consider using a Lob as the max size in oracle for something like a varchar is 4000. You could use the #Lob annotation on the field/setter if you wanted to go this right.
Related
Here is the db table.
Here are the project and pallette tables to show the format of the files and variables
Here is the list of variables
Now,for variable int timeTaken, it updates every time step. I want each time step's timeTakenin its own DB. Now, in the db table, I place in default value: wholesaler.timeTaken into the default value. How do I place each timeTaken into a database?
Error I got when I put wholesaler.TimeTaken
You have to add it by writing a database query. You can use both SQL and QueryDSL syntax. More info: https://anylogic.help/anylogic/connectivity/querying.html
For example, if using queryDSL syntax, you should make it look like this:
insertInto(db_table)
.columns(db_column)
.values(wholesaler.timeTaken)
.execute();
Put it in a function and you can simply call it.
Please make sure datatypes of your variable and assigned column are the same. Error probably occured because of different datatypes. You can leave the default value blank.
The easiest way building a query is by using the wizard: icon query wizard
Good luck!
I want to use a spark job to pull data from a hive table and then insert it into an existing SQL Server table, flush-and-fill style.
I was planning on using df.write.jdbc(), however it seems this method has no way to pass in a SaveMode.Overwrite parameter. At the moment, the SaveMode is ErrorIfExists.
How can I get around this?
You can try by this
df.write.mode("overwrite").jdbc()
There is a way to truncate the target table but it's not supported by all SQL Server JDBCs (from my experience). As you can see on the code below, you can set the mode as "overwrite" and later the option "truncate" as true (where prop are the additional properties to set
spark.range(10).write.mode("overwrite").option("truncate", true).jdbc(url, "table", prop)
Another format for the same is
df.write.option("truncate", "true").jdbc(url=DATABASE_URL, table=DATABASE_TABLE, mode="overwrite", properties=DATABASE_PROPERTIES)
I'm trying to add a new custom field to the Customer page. The field is a "comment" field with formatted text in it. I know I'll have to use the PXRichTextEdit in my page and I need to add a SQL column of type TEXT, not VARCHAR.
My problem is that when I try to add a custom column in the table, the list of data types is this :
By the way, I tried selecting "string" but this creates a column with the type VARCHAR and I get errors about truncating data when trying to save something in my column.
I successfully did it by creating manually the column in my SQL Server database (with SSMS), but I really don't want to do that when deploying in the production environment. I would prefer to have it in my personalisation package.
Is there a way to have it in the project ? Am I missing something obvious ?
The limitation I have comes from the PXRichTextEdit. It needs an SQL column with a maximum size limit. The solution I found is to create a string column in the customization screen. Although the size is limited to 4000 characters, I created a database script to change the column size to max. With this, I don't have the error about truncating data and the SQL column is of type varchar.
It seems that the answer to this question should already be out there, but after some hours of experimentation I have yet to find a solution that works. What I'm looking to do is insert into an MSSQL database a record that includes a VARBINARY(MAX) column. The source of the data is a BLOB column from an SQLite database, also ready using SQLAlchemy and which appears to be rendered as a Python string. Whatever I try I still seem to received the following message:
'Implicit conversion from data type varchar to varbinary(max) is not
allowed. Use the CONVERT function to run this query.
I can see that what is required (or at least what seems to work if I try it manually) at the SQL level is to wrap the bound column in CONVERT(VARBINARY(MAX), ...) but making SQLALchemy do this has so far frustrated me.
Thanks in advance as always.
In SQL Server 2008, I have a strongly typed data set with a table:
TABLE
ID (Guid)
Value (varchar(50))
This this table, Value actually represents an encrypted value on the database, which becomes decrypted after reading from this table on my server.
In Visual Studio; I have a Dataset with my table, which looks like:
TABLE
ID (Guid)
Value (float)
I want to know if there is a way, in a DataSet, to call my decryption methods on Value when I am calling my Fill Query on the TableAdapter for this Table.
Is there anyway to extend the DataSet XSD to support this sort of data massaging when reading data?
In addition to this, is there a way when inserting/updating records in this table to write strings to encrypted values?
NOTE:
All Encrypt/Decryption code is being performed on the client to the database, not on the database itself.
The Fill() method is going to execute whatever SQL is in the SelectCommand property of the DataAdapter. It's certainly possible to customize the SQL to "massage" data as it comes in.
Your issue is made more complex by the need to execute some .NET decryption. If you really want to do this and it is of high value to you, you could install a .NET assembly in the SQL Server database. Once this was done, you should be able to specify a custom SelectCommand that calls the code in your ,NET assembly to decrypt the data at select-time.
But that seems like an awful lot of work for very little reward. It's probably easier and more efficient to simply post-process the dataset and decrypt there. :)