To count number of COLUMNs in a table

Say if out table is EMP and If we want to count number of column present in EMP table, then following query can be used.

select COUNT(*) from INFORMATION_SCHEMA.COLUMNS where table_name='emp'

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Zip/Unzip multiple files and also include password for zipped file using SSIS

We have many scenario that we need to Zip many files which we come across and then so some operations like either sending it as a email or just moving zipped file to some other destinations etc. But we were using manual method to zip multiple files. In this post, I tried to create a package which will zip multiple files using SSIS. Here for Zipping files purpose, I'm using 7-ZIP which is free software available in google sites. Download files and install onto your system. First let me show how to Zip on file and later I will show how to zip multiple files using SSIS and 7Zip tool. Compressing Single file. Here I'm trying to Zip one single flat file which is of 40MB size. I kept this file in C:\Documents and Settings\\Desktop\test\source folder. Now to compress this file, I will open my SSIS and I'm dragging and dropping EXECUTE PROCESS TASK from Control Flow. Now right click on Execute Process task and go for edit and select Process option. In process tab,

SSIS: The Value Was Too Large To Fit In The Output Column

I had a SSIS package where I was calling a stored procedure in OLEDB Source and it was returning a “The Value Was Too Large to Fit in the Output Column” error. Well, My Datatype in OLEDB source was matching with my OLEDB Destination table. However, when I googled, we got solutions like to increase the output of OLEDB Source using Advanced Editor option . I was not at all comfortable with their solution as my source, destination and my intermediate transformation all are having same length and data type and I don’t want to change. Then I found that I was missing SET NOCOUNT ON option was missing in Stored Procedure. Once I added it, my data flow task ran successfully.

BIG Data, Hadoop – Chapter 2 - Data Life Cycle

Data Life Cycle The data life cycle is pictorial defined as show below: As we see, in our current system, we capture/ Extract our data, then we store it and later we process for reporting and analytics. But in case of big data, the problem lies in storing and then processing it faster. Hence Hadoop takes this portion, where it stores the data in effective format (Hadoop distributed File System) and also process using its engine (Map Reduce Engine). Since Map Reduce engine or Hadoop engine need data on HDFS format to process, We have favorable tools available in market to do this operation. As an example, Scoop is a tool which converts RDBMS to HDFS. Likewise we have SAP BOD to convert sap system data to HDFS.

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