I am trying to import data into a table in Oracle from a CSV file using SQL Loader. However, I want to add two additional attributes namely date of upload and the file path from which the data is being imported. I can add the date using SYSDATE, Is there a similar method of obtaining the file path?
The trouble with using SYSDATE is that it will not be the same for all rows. This can make it difficult if you do more than one load in a day and need to back out a particular load. Consider using a batch_id also using the method in this post: Insert rows with batch id using sqlldr
I suspect it could be adapted to use the SYSDATE as well so it would be the same for all rows. Give it a try and let us know. At any rate, using a batch_id from a sequence would make working with problems much easier should you need to delete based on a batch_id.
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The column contains dates in the following format:
dd/mm/yyyy
I've tried DATE, TIMESTAMP etc but whatever I do, I can't seem to upload the file.
In the classic UI you can click on the Load Tablebutton and follow the dialogs to upload your file. It is a bit hard to find. Click on Databases right to the big snowflake icon. Then select a database and a table. Then you should the the button. In the wizard there will be a step for defining the 'File Format'. There, you have to scroll down to define the date format. (see Classic snowflake UI)
Without the classic UI you have to install SnowSQL on your device first (https://docs.snowflake.com/en/user-guide/snowsql-install-config.html).
Start SnowSQL and apply the following steps:
Use the database where to upload the file to. You need various privileges for creating a stage, a fileformat, and a table. E.g. USE TEST_DB
Create the fileformat you want to use for uploading your csv file. E.g.
CREATE FILE FORMAT "TEST_DB"."PUBLIC".MY_FILE_FORMAT TYPE = 'CSV' DATE_FORMAT = 'dd/mm/yyyy';
Create a stage using this fileformat
CREATE STAGE MY_STAGE file_format = "TEST_DB"."PUBLIC".MY_FILE_FORMAT;
Now you can put your file to this stage
PUT file://<file_path>/file.csv #MY_STAGE;
You can check the upload with
SELECT d.$1, ..., d.$N FROM #MY_STAGE/file.csv d;
Then, create your table.
Copy the content from your stage to your table. If you want to transform your data at this point, you have to use an inner select. If not then the following command is enough.
COPY INTO mycsvtable from #MY_STAGE/file.csv;
You can find documentation for configuring the fileupload at https://docs.snowflake.com/en/sql-reference/sql/create-file-format.html
You can find documentation for configuring the stage at https://docs.snowflake.com/en/sql-reference/sql/create-stage.html
You can find documentation for copying the staged file into a table https://docs.snowflake.com/en/sql-reference/sql/copy-into-table.html
I recommend that you upload your file with disabled automatically date detection OR that your initial table has a string column instead of a date column. IMHO, it is easier to transform your upload afterwards using the try_to_date function. Using this function it is much easier to handle possible parsing errors.
e.g. SELECT try_to_date(date_column, 'dd/mm/yyyy') as MY_DATE, IFNULL(MY_DATE, date_column) as MY_DATE_NOT_PARSABLE FROM upload;
You see that it is pretty much to do for loading a simple CSV file to Snowflake. It becomes even more complicated when you take into account that every step can cause some specific failures and that your file might contain erroneous lines. This is why my team and I are working at Datameer to make these types of tasks easier. We aim for a simple drag and drop solution that does most of the work for you. We would be happy if you would try it out here: https://www.datameer.com/upload-csv-to-snowflake/
I have developed a mapping in informatica.Source is file .I need to write a post sql that will delete the already existing data if the file with same name comes again.File comes once in every month and naming is like jass_naming_yyyymm.csv .I have written like delete from tab where load_date = sysdate but its not working.laod date is a column in target table taht stores yyyymm from the file.So query shoud be like if file with existing yyyymm comes again the existing data should get deleted and new file will be loaded.
Please give soluntion.
Post SQL will not help here. You need two pipelines.
Pipeline 1 - Src->exp->tgt.
Use indirect file read method, get file name to fetch yyyy_mm part from file name.
You need to use 'update override' option in the target to delete the data. Use this logic -
DELETE FROM target_table WHERE target_yyyy_mm= :TU.source_yyyy_mm
Pipeline 2 - your mapping.
HTH
I Googled for a solution to create a table, using Databticks and Azure SQL Server, and load data into this same table. I found some sample code online, which seems pretty straightforward, but apparently there is an issue somewhere. Here is my code.
CREATE TABLE MyTable
USING org.apache.spark.sql.jdbc
OPTIONS (
url "jdbc:sqlserver://server_name_here.database.windows.net:1433;database = db_name_here",
user "u_name",
password "p_wd",
dbtable "MyTable"
);
Now, here is my error.
Error in SQL statement: SQLServerException: Invalid object name 'MyTable'.
My password, unfortunately, has spaces in it. That could be the problem, perhaps, but I don't think so.
Basically, I would like to get this to recursively loop through files in a folder and sub-folders, and load data from files with a string pattern, like 'ABC*', and load recursively all these files into a table. The blocker, here, is that I need the file name loaded into a field as well. So, I want to load data from MANY files, into 4 fields of actual data, and 1 field that captures the file name. The only way I can distinguish the different data sets is with the file name. Is this possible? Or, is this an exercise in futility?
my suggestion is to use the Azure SQL Spark library, as also mentioned in documentation:
https://docs.databricks.com/spark/latest/data-sources/sql-databases-azure.html#connect-to-spark-using-this-library
The 'Bulk Copy' is what you want to use to have good performances. Just load your file into a DataFrame and bulk copy it to Azure SQL
https://docs.databricks.com/data/data-sources/sql-databases-azure.html#bulk-copy-to-azure-sql-database-or-sql-server
To read files from subfolders, answer is here:
How to import multiple csv files in a single load?
I finally, finally, finally got this working.
val myDFCsv = spark.read.format("csv")
.option("sep","|")
.option("inferSchema","true")
.option("header","false")
.load("mnt/rawdata/2019/01/01/client/ABC*.gz")
myDFCsv.show()
myDFCsv.count()
Thanks for a point in the right direction mauridb!!
We want some of our customers to be able to export some data into a file and then we have a job that imports that into a blank copy of a database at our location. Note: a DBA would not be involved. This would be a function within our application.
We can ignore table schema differences - they will match. We have different tables to deal with.
So on the customer side the function would ran somethiug like:
insert into myspecialstoragetable select * from source_table
insert into myspecialstoragetable select * from source_table_2
insert into myspecialstoragetable select * from source_table_3
I then run a select * from myspecialstoragetable and get a .sql file they can then ship to me which we can then use some job/sql script to import into our copy of the db.
I'm thinking we can use XML somehow, but I'm a little lost.
Thanks
Have you looked at the bulk copy utility bcp? You can wrap it with your own program to make it easier for less sophisticated users.
Since it is a function within your application, in what language is the application front-end written ? If it is .NET, you can use Data Transformation Services in SQL Server to do a sample export. In the last step, you could save the steps into a VB/.NET module. If necessary, modify this file to change table names etc. Integrate this DTS module into your application. While doing the sample export, export it to a suitable format such as .CSV, .Excel etc, whichever format from which you will be able to import into a blank database.
Every time the user wants do an export, he will have to click on a button that would invoke the DTS module integrated into your application, that will dump the data to the desired format. He can mail such file to you.
If your application is not written in .NET, in whichever language it is written, it will have options to read data from SQL Server and dump them to a .CSV or text file with delimiters. If it is a primitive language, you may have to do it by concatenating the fields of every record, by looping through the records and writing to a file.
XML would be too far-fetched for this, though it's not impossible. At your end, you should have the ability to parse the XML file and import it into your location. Also, XML is not really suited if the no. of records are too large.
You probably think of a .sql file, as in MySql. In SQL Server, .sql files, that are generated by the 'Generate Scripts' function of SQL Server's interface, are used for table structures/DDL rather than the generation of the insert statements for each of the record's hard values.
I have a very large data set in GPDB from which I need to extract close to 3.5 million records. I use this for a flatfile which is then used to load to different tables. I use Talend, and do a select * from table using the tgreenpluminput component and feed that to a tfileoutputdelimited. However due to the very large volume of the file, I run out of memory while executing it on the Talend server.
I lack the permissions of a super user and unable to do a \copy to output it to a csv file. I think something like a do while or a tloop with more limited number of rows might work for me. But my table doesnt have any row_id or uid to distinguish the rows.
Please help me with suggestions how to solve this. Appreciate any ideas. Thanks!
If your requirement is to load data into different tables from one table, then you do not need to go for load into file and then from file to table.
There is a component named tGreenplumRow which allows you to write direct sql queries (DDL and DML queries) in it.
Below is a sample job,
If you notice, there are three insert statements inside this component. It will be executed one by one separated by semicolon.