In our previous article, we saw SSIS Amazon S3 Storage Task examples. Now let’s look at how to Download the Latest File from Amazon S3 Storage using SSIS. Microsoft SSIS includes the Amazon S3 Storage Task that allows us to upload files to Amazon S3 Storage, download files, creating local and remote directories an more. In this article, we will show how to use the SSIS Amazon S3 Storage task included in ZappySys SSIS PowerPack.

In nutshell, this post will focus on how to Download the Latest File from Amazon S3 Storage.

What is Amazon S3 Storage

Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. Amazon S3 provides easy-to-use management features so you can organize your data and configure finely-tuned access controls to meet your specific business, organizational, and compliance requirements. Amazon S3 is designed for 99.999999999% (11 9’s) of durability, and stores data for millions of applications for companies all around the world.

Getting Started

In order to start, we will show several examples. ZappySys includes an SSIS Amazon S3 Storage Task that will allow you to access files/folders from Amazon S3 Storage to the Local machine, Upload files(s) to Amazon S3 Storage. It will also support Delete, Rename, List, Get Property, Copy, Move, Create, Set Permission … and many more operations. Here we are showing you is, How to Download the Latest File from Amazon S3 Storage.

Step-By-Step to Download the Latest File from Amazon S3 Storage

Let´s start with an example. In this SSIS Amazon S3 Storage Task File task example, we will download the latest file using Amazon S3 Storage Task.

1. First of All, Drag and Drop Amazon S3 Storage Task from SSIS Toolbox and double click it to edit
   

   Drag and Drop Amazon S3 Storage Task

2. The following options are available in Amazon S3 Storage Task:
   

   Options to upload, download files in SSIS

3. You can also overwrite files and folder, skip all, overwrite if the source is older, overwrite if the file size is different, rename files and more:
   

   Overwrite files in SSIS

4. Let’s select the Download Amazon file(s) to local directory. Now select/add The Source path, Check Recursive Scan(*Optional) to get all the sub-files and subfolders and files, after that add Target Path if you want to, This option will download files. In Path AccessMode we can use Direct to write the path directly or to use an SSIS variable.
   

   SSIS Amazon S3 Storage Task – Download files from Amazon S3 Storage

5. Now go to Advanced Filter & Sorting and configure it like below screen to download the latest file only.
   

   Storage Task configuration to download the latest file only using sorting

6. That’s it now execute the package and it will download the latest file from the Amazon S3 Storage Task to Local File Machine.
7. Sometimes you may need to make advanced filtering on file path, file date, size, etc. for that refer to this article for more details.

Conclusion

To conclude, we can say that working with Amazon S3 Storage is now very simple. In this article, we looked at how to Download the Latest File from Amazon S3 Storage using SSIS. We used Adnavced Filtering & sorting option. If you liked the tasks you can start using them by downloading SSIS PowerPack from our web site here.

Thanks for your time.

References

• About SSIS PowerPack
• Integration Services (SSIS) Expressions
• Help File: Amazon Storage Task

The post Download the Latest File from Amazon S3 Storage using SSIS appeared first on ZappySys Blog.

In this article, we will show SSIS Amazon S3 Storage task examples. Uploading files using Amazon S3 Storage Task or downloading files are common requirements in SSIS. In order to work with Amazon S3 Storage, Microsoft SSIS includes the Amazon S3 Storage Task that allows to upload files to Amazon S3 Storage, download files, creating local and remote directories an more. In this article, we will show how to use the SSIS Amazon S3 Storage task included in ZappySys SSIS PowerPack.

Amazon S3 Storage Task can be used to perform various operations with Amazon S3 Storage objects (files and containers) (e.g. Download, Upload, Copy, Move, Rename, Delete, etc). You can also get single property of any Amazon file or get a list of Amazon files as ADO.net Table and which can be easily looped through using ForEachLoop Task. Most of the operations in this task support recursive search using wild card pattern (e.g. Myfile*.txt).

Prerequisite

1. First, you will need to have SSIS installed
2. Secondly, make sure to have SSDT
3. You have obtained Amazon S3 account access key / secret key.
4. Finally, do not forget to install ZappySys SSIS PowerPack

What is Amazon S3 Storage

Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. Amazon S3 provides easy-to-use management features so you can organize your data and configure finely-tuned access controls to meet your specific business, organizational, and compliance requirements. Amazon S3 is designed for 99.999999999% (11 9’s) of durability, and stores data for millions of applications for companies all around the world.

Getting Started

In order to start, we will show several examples. ZappySys includes an SSIS Amazon S3 Storage Task that will allow you to access files / folders from Amazon S3 Storage to the Local machine, Upload files(s) to Amazon S3 Storage. It will also support Delete, Rename, List, Get Property, Copy, Move, Create, Set Permission … and many more operations. Here we are showing you is, How to upload, download, move and delete files / folders from Amazon S3 Storage.

SSIS Amazon S3 Storage Task Examples

Let´s start with an example. In this SSIS Amazon S3 Storage Task File task example, we will upload, download, move and delete files / folders from Amazon S3 Storage.

1. First of All, Drag and Drop Amazon S3 Storage Task from SSIS Toolbox and double click it to edit
   

   Drag and Drop Amazon S3 Storage Task

2. The following options are available in Amazon S3 Storage Task:
   

   Options to upload, download files in SSIS

3. You can also overwrite files and folder, skip all, overwrite if source is older, overwrite if the file size is different, rename files and more:
   

   Overwrite files in SSIS

4. Let’s select the Download Amazon file(s) to local directory. Now select/add The Source path, Check Recursive Scan to get all the sub files and sub folders and it’s files and add Target Path, This option will download files. In Path AccessMode we can use Direct to write the path directly or to use an SSIS variable.
   

   SSIS Amazon S3 Storage Task – Download files from Amazon S3 Storage

5. That’s it now execute the package and it will download all the files and sub folders from the Amazon S3 Storage Task to Local File Machine.
6. Now Let’s configure the task to upload the local directory files and folder to Amazon S3 Storage like below and execute the package. And also in this example i created the variable and stored target folder path in it and used that variable Target Path Variable.
   

   SSIS Amazon S3 Storage Task – Upload files from Amazon S3 Storage

7. Let’s configure the task to delete Amazon S3 Storage files like below and execute the package.
   

   SSIS Amazon S3 Storage Task – Delete files from Amazon S3 Storage

8. Let’s configure the task to move Amazon S3 Storage files to another directory like below and execute the package.
   

   SSIS Amazon S3 Storage Task – Move files from Amazon S3 Storage

9. That’s it like upper examples you can configure Amazon S3 Storage Task to use it’s other options also.
10. Let’s see other SSIS Amazon S3 Storage Task examples in below sections

Working with advanced filters

In order to understand filters, we will create an example for you. This time we will create SSIS Amazon S3 Storage task example to show how to exclude some files from the downloading process.

1. In addition, it is also possible to add advanced filters to the SSIS Amazon S3 Storage task to exclude or include files and folders. The following example shows how to use the Advanced filters. In the Amazon S3 Storage Task, go to the Advanced Filter page and in Exclude RegX we will write \.exe$ to exclude the file with exe extension to be downloaded. You can use RegX (regular expressions) in the advanced filter:
   

   Advanced filters

Working with wildcards in SSIS Amazon S3 Storage task (Multiple files only)

In order to understand wildcards, the new example will show how to work with Wildcards will help you to work with multiple files or folder with common characteristics.

1. The following example shows how to copy all the files will all the extensions in the source folder. We use the *.*, which means that any file name with any extension will be downloaded:
   

   Working with Wildcards

2. If we want to download all the files with extension txt, use the following Path:
   

   /source/*.txt;

3. Another example would be to download all the files with the following names: file1.txt, file2.txt and file3.txt.  We could use the following Path:
   

   /source/file?.txt

Working with SSIS expressions and variables in Amazon S3 Storage Task

In order to understand expressions, the following example will show how to work with SSIS expressions combined with variables in the SSIS Amazon S3 Storage task. In this example we will delete files in Amazon S3 Storage using variables and expressions.

1.  First, we will first create a variable in SSIS. In this example the file name is MyFile and the Value file1.
   

   Create an SSIS variable

2. As a second step, we will write in path the value \destination\{{User.MyFile}}.txt. This will concatenate the folder destination with the variable MyFile. The task will delete the file1.txt from the Amazon S3 Storage folder.
   

   Using SSIS expressions

3. The next example will show how to create a Amazon S3 Storage file using expressions and variables in SSIS:
   

   Create file

4. Content to write is the content of the file. In Target, go to path and write the following: For more information on placeholders check this post and also check this post.
   

   /destination/{{User::FileName,MM-dd-yyyy}}

5. We are using a variable in SSIS named FileName of type DateTime. We are concatenating the Amazon S3 Storage folder destination with the variable. As you can see, the expressions with ZappySys are very simple.

Example to verify if file exists in SSIS Amazon S3 Storage task

Finally, we will verify if a file in Amazon S3 Storage exists or not using the SSIS Amazon S3 Storage task.

1. In order to start, we will use the SSIS variables, create a variable of Boolean type named FileExists. In Storage Action, select Get Amazon file exist status. In path, select the path of the file to verify if it exists or not.
   

   SSIS Amazon S3 Storage Task – Check File Exist in Amazon S3 Storage

2. Secondly, we will use the ZS Logging Task to check the value of the variable File Exists. This task will show the value of the variable in the log. Drag and drop the task and join it with the ZS Amazon S3 Storage Task:
   

   The SSIS Log task

3. In order to get the value, we will insert it in the Logging Task. To do that, insert the Variable and select the FileExists variable:
   

   Add the variable in the task logging

4. Finally, run the package and verify the Output (you can use View and Output to see the output) and check the value of the Logging Task. If the file exists, the value will be true. If it does not exist, the value will be false.
   

   Verify the variable in Output

How to loop through Amazon S3 Storage files in SSIS

You can also loop through files to perform custom action file by by. Amazon S3 Storage Task support Action to get File List as ADO.net Recordset

To get File list from Amazon S3 Storage Server perform the following steps.

1. From Storage Action select Get Amazon files as ADO.net DataTable
   
   

   Get files as ADO.net DataTable

    

2. Create new Amazon S3 Storage Connection by clicking New next to connection dropdown.
3. Select Source Path (e.g  \myroot\folder\*.txt  )
4. Select or create new SSIS Variable (e.g. varFiles ) which will hold file list result (Must be Object datatype variable).
5. Click OK to close.
6. Create 3 more SSIS variables to hold File Path (String), Name (String) and Size (Int32). We will use in the next step.
7. Now drag SSIS ForEach Loop Container Task from SSIS Toolbox
8. Edit Loop Task and Select Foreach ADO Enumerator from the Enumerator dropdown
9. Select variable (e.g. varFiles)
   
   

   Loop through files in SSIS using ForEach Loop Task (use ADO.net Recordset variable)

10. Click on Variable Mappings Tab and configure like below.
    

    Variable Mappings for ForEach Loop Task – Loop through files in a folder using SSIS

11. Drag ZS Logging Task and place inside Loop and Display variables
12. That’s it

For more information to loop through files on local machine using SSIS check this article.

Conclusion

To conclude, we can say that working with Amazon S3 Storage is now very simple. In this article, we looked at SSIS Amazon S3 Storage Task examples on how to upload, download, delete files and folders. We used variables, wildcards and expressions. If you liked the tasks you can start using them by downloading SSIS PowerPack from our web site here. We saw different SSIS Amazon S3 Storage Task examples to understand how to use the task in different scenarios.

Thanks for your time.

References

• About SSIS PowerPack
• Integration Services (SSIS) Expressions
• Help File : Amazon Storage Task

The post SSIS Amazon S3 Storage Task examples (Download, Upload, Delete Files / Folders) appeared first on ZappySys Blog.

In this post we will see how to set Metadata key/value in Azure Blob Storage Task and Amazon Storage Task (S3 Task). We will also see how to set them dynamically at runtime (Use SSIS Expression).

Set Amazon S3 Task Metadata (Key / Value Pairs)

Here is how you can set Metadata in Amazon S3 Task.

Setting Amazon S3 Metadata (Key/Value Pairs) in SSIS Amazon Storage Task

Set Azure Blob Storage Task Metadata (Key / Value Pairs)

Just like S3 Task you can use same UI in Azure blob storage task too.

Set Metadata Key/Value Dynamically (SSIS Expression)

So far you have set metadata using static value. What if you have to set Dynamically at runtime?

Basically Metadata is passed as XML Format in the task like below.

<?xml version="1.0" encoding="utf-8"?>
<ArrayOfStringKeyValue xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema">
	<StringKeyValue>
		<Key>x-amz-key1</Key>
		<Value>AAAAAAA</Value>
	</StringKeyValue>
	<StringKeyValue>
		<Key>x-amz-key2</Key>
		<Value>BBBBBBB</Value>
	</StringKeyValue>	
</ArrayOfStringKeyValue>

Whate we will do is take above format and make it dynamic using SSIS Expression.

Perform the following steps for that.

1. Select your Amazon Storage Task or Azure Storage Task and right click > Select Properties.
2. In the Properties Grid check Property name MetadataKeyValue. Copy XML Value from there (We will use it in expression)
3. Now double click Amazon Storage Task or Azure Storage Task
4. Click on Expression Button
5. Select MetadataKeyValue property and for Value enter below expression… Use previously copied XML text  and change Value part with your own SSIS variable. In below example we are passing Just one Metadata Key/Value pair ( Name=x-amz-meta-filename  , Value=Coming from @[User::MyFileNameVariable] )
   Note that we have escaped double quote with

   \"

     and replaced static value with

   <Value>" + @[User::MyFileNameVariable] + "</Value>

    .
   

   "<?xml version=\"1.0\" encoding=\"utf-8\"?>"
   + "<ArrayOfStringKeyValue xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\" xmlns:xsd=\"http://www.w3.org/2001/XMLSchema\">"
   + "	<StringKeyValue>"
   + "		<Key>x-amz-meta-file-name</Key>"
   + "		<Value>" + @[User::MyFileNameVariable] + "</Value>"
   + "	</StringKeyValue>"
   + "	<StringKeyValue>"
   + "		<Key>x-amz-meta-something</Key>"
   + "		<Value>BBBBBBB</Value>"
   + "	</StringKeyValue>"	
   + "</ArrayOfStringKeyValue>"

   

   Set Amazon S3 File Metadata Key/Value dynamically

6.  Click OK and that’s it.

The post Setting Metadata key / value in SSIS Amazon S3 / Azure Storage Task appeared first on ZappySys Blog.

In our previous blog we saw how to upload data to Amazon S3 now let’s look at how to Copy Amazon Files from one AWS account to another AWS account (Server Side Copy) using SSIS Amazon Storage Task. (Must be version v2.7.9 or higher)

If you are doing file copy within same account then there is no issue. Just use Copy File feature. However if you want to copy between multiple AWS Accounts (e.g. Your Company AWS account to Vendor AWS Account) then you have to perform extra steps.

Amazon S3 File Copy Scenario

Now let’s think about a scenario where you have to copy some files from Account-A to Account-B. Account-B can be owned by totally different company (may be your Vendor) and you don’t have security control of it.

Before we can copy from Account-A to Account-B we first have to Configure permissions in Account-B. Basically when you use SSIS S3 Task for Copy operation it uses Source account (i.e. Account-A) to push files to destination account (Account-B). So you have Allow write permission for Source Account-A in Destination AWS Bucket (i.e. Account-B).

Find Canonical ID of Source Account

1. First login to Account-A and findout Canonical ID (Usually 64-digit long)
2. To get Canonical ID click on Your Account Name > My Security Credentials
3. When prompted click Continue to Security Credentials option.
4. Expand Account Identifier and copy Canonical ID
   

   How to find AWS Account ID and Canonical User ID

Configure Target S3 Bucket Permissions to allow Source Account (Write Access)

Now once you have Source account Canonical User ID, you can proceed to next step.

1. Log in to Target account (i.e. Account B). Where you like to copy files.
2. Go to S3 Area and Click on the target bucket where you like to copy files
3. Go to Security Tab
4. Add Source Account Canonical ID and Check Write Permission (List is Optional for most).
   

   Give Write permission in Target AWS S3 Bucket (Enter Amazon Source Account Canonical User ID)

Copy Amazon S3 Files from one Account Bucket to Another

Now once you configure permission on target bucket. We are ready to execute Amazon S3 File Copy Operation in SSIS

1. Open SSIS Package in Visual Studio
2. Drag ZS Amazon Storage Task from SSIS Toolbox
3. Double click it to configure
4. Select Copy File Operation from Action Dropdown
5. Click New for Source Connection (Enter Source Account Credentials). Click Test and OK to save.
6. Now Click Browse to Select Source Files you like to Copy. You can use Wild card pattern for multiple file copy.
   Example:  mysourcebucket/subfolder/localsubfile*.csv
7. Click New for Target Connection (Enter Target Account Credentials). Click Test and OK to save.
8. Now Click Browse to Select Target Folder Location where you like to Save Copied files.
   Example:  mytargetbucket/somefolder/
9. Click OK to Save
10. Execute SSIS Package to test

Copy Amazon S3 Files using SSIS (Copy Files between multiple Amazon Accounts / S3 Buckets)

Conclusion

In this post you have seen how easy it is to copy S3 Files between multiple AWS accounts in few clicks. Try SSIS PowerPack for free and find out yourself how easy it is to Automate Amazon S3 related operations in SSIS.

The post Copy Amazon S3 Files in SSIS to different AWS Account appeared first on ZappySys Blog.

In our previous posts we looked at how to use SSIS Amazon Storage Task (Amazon S3 Task) to automate some Amazon S3 related tasks in SSIS. In this blog post will continue discovering more use cases. Let’s learn how to delete Amazon S3 File, delete Amazon S3 Folder and delete Amazon S3 Bucket.

Deleting S3 Files are straight forward using SSIS Amazon Storage Task (Amazon S3 Task but deleting Bucket or Folders require some additional checks and steps, so let’s look at that in depth.

Requirements

Before we look into Step-By-Step section to call Amazon S3 related operations in SSIS let’s make sure you met the following requirements.

1. SSIS designer installed. Sometimes it is referred as BIDS or SSDT (download it from Microsoft site).
2. Basic knowledge of SSIS package development using Microsoft SQL Server Integration Services.
3. ZappySys SSIS PowerPack installed. Click on the link to download a FREE trial.
4. You have obtained Amazon S3 account access key / secret key.

Configure SSIS Amazon S3 Connection

Before we perform any S3 related action, you must configure Amazon Storage Connection. This connection manager support connectivity to not only S3 Storage but also other AWS Storage such as DynamoDB, Redshift

There are two ways you can create Amazon Storage Connection Manager in SSIS designer. You can right click in Connection Manager Panel and create new ZS-AMAZON-STORAGE connection type or use Task UI and click New connection.

For now, we will use easier method which is Create S3 Connection from S3 Storage Task UI.

1. Open SSIS Package
2. Drag ZS Amazon S3 Storage Task from the toolbox
3. Double click it to edit. You can now click on New Connection like below.
   

   Create New Amazon S3 Connection from Task UI

4. On the connection Manager UI. Select S3 as service type. Enter your Access Key, Secret Key and Select Region. We also support IAM Role for EC2 instances (For this package must run inside EC2 VM). Check this article.
   

   Configure SSIS Amazon S3 Connection – Select Region, Enter Access Key / Secret Key

5. Click Test connection to confirm its working. Click OK to Save Connection Manager UI.
6. Back to Task UI click OK to close save (We will configure task in later sections.

Using SSIS Amazon S3 Task for common actions

Before we deep dive in delete scenarios let’s first look at what is  SSIS Amazon Storage Task (Amazon S3 Task). This task is developed to achieve many S3 related operations. See below screenshot to get idea about many actions you can perform using just one task. In this post we will focus only on delete actions (for file, folder and bucket). In other posts we will cover different operations in depth.

SSIS Amazon S3 Task Operations – Upload, Download, Delete, Create, List, Rename Files, Folders, Buckets

Delete Amazon S3 Files

Once you have configured SSIS S3 Connection Manager, we can perform different S3 related operations using many different Amazon S3 related tasks / components. For now let’s just look at how to delete files from S3 bucket.

Delete Multiple S3 files – Using Simple Pattern Search (wildcard)

Here is how to delete amazon s3 file / files using wildcard pattern search. Using * or ? allowed. (Example  SalesOrder_*.??? )

Delete Amazon S3 File (Multiple) using Wildcard pattern

Delete Multiple S3 files – Using Advanced Search – Regex / SQL Expression

Sometimes it’s necessary to filter file based on advanced attributes such as file Age (How old), File Size, Multiple File Patterns (e.g. Delete *.zip, *.gz, *.rar in one action)

You can use Advanced Tab to filter further. First supply primary filter on Source Tab (e.g. mybucket/*.* ) and then supply your advanced filter (e.g. you can exclude *.exe and *.msi file from your delete list as below screenshot, also only delete files between 1000 and 50000 bytes in file size).

Advanced Search in SSIS Amazon S3 Task – Use Regular Expression Patterns, SQL like expression for Sort / Filter

//////////////////////////////
Examples:
//////////////////////////////
AgeInDays < 5  //Get files created in last 5 days
LastEditInDays > 3 //Get files modified before 3 days
AgeInDays > 10 AND LastEditInDays < 3  //Get files created before 10 days and modified in last 3 days
Size < 1024  //Get files where File size is less than 1024 bytes
CreationDate BETWEEN #2015-01-01# AND #2015-01-01#   
Name IN ('File1.txt', 'Download.msi')
FullPath LIKE 'mybucket\somefolder\month_*')
Extension IN ('.txt','.csv')
LastModifiedDate > #2013-01-01T16:00:00#
IsReadOnly = True
/////////////////////////////////////////
//Supported Columns for expression:
/////////////////////////////////////////
Name, FullPath, Extension, FolderPath, AgeInDays, LastEditInDays, Size, CreationDate, CreationDateUtc, LastModifiedDate, LastModifiedDateUtc, IsReadOnly

Delete Amazon S3 files older than X days

If you like to delete files older than certain days then use below technique.

1. First Specify primary search criteria on Source tab
2. Go to Advanced Filter Tab and specify Following Pattern in Where Textbox (For example delete Files older than 10 days )
   

   AgeInDays > 10

Delete Amazon S3 Bucket

Now let’s look at how to delete Amazon S3 Bucket including all its content. There is an option to delete Bucket but it wont delete files and empty folders. So you have to first clear all its content before calling Delete bucket action.

Here is high level steps to delete bucket in SSIS using ZappySys S3 Task.

1. First call Delete S3 Files Action using Source Path = mybucket/*. Delete file action won’t delete any real folders (i.e. name ends with slash).
2. Once files are deleted from bucket you can get list of empty folders
   1. Select Action = Get Amazon folder list as ADO.net Table
   2. In the path enter Path = mybucket/*
   3. In the Result Variable Create or Select variable (e.g. User::FolderList)
3. Use ForEachLoop Task to Delete empty folders (Use Delete File Action because there is no folder concept in S3. File name ends with slash is treated as folder)
   1. In the ForEachLoop Task select enumerator as  Foreach ADO enumerator
   2. In the variable select a variable which holds list of folders (obtained in previous step)
   3. On the Variable Mappings Tab. Select Some variable (e.g. User::FolderPath) to map to Index =0
   4. Drag new S3 Task inside ForEachLoop and Select Delete File Action
   5. In the File Path enter variable as {{User::FolderPath}}  (or whatever name you given which holds iteration FolderPath in previous step)
4. Call Delete Bucket Action once bucket is totally empty.

Delete Amazon S3 Bucket (including files and folders)

Delete Amazon S3 Folders

There is no real folder concept in Amazon S3 file system. S3 File System is just key / value system. Key is basically file name (e.g. somefolder/subfolder/myfile.txt). You can use slash in name to indicate hierarchy which can be used by some client apps like ZappySys S3 File Picker to Mimic Treeview like structure so user feel like real file system but there are no rules if you have to use slash or not.

Most client tools for S3 treats any file name ends with slash as real folder.  See below step to delete amazon s3 folder (real folder which was created explicitly – mentioned in next section).

1. Open S3 Task and select action = Delete Amazon File(s)
2. In the path enter your Folder Path (e.g. mybucketname/output/sub2/ )

Create Amazon S3 Folder

Some time you may want to create real S3 folder which is not treated as file. In that case use this technique to create s3 folder.

Conclusion

In this post we saw how easy it is to use SSIS Amazon Storage Task (Amazon S3 Task) to delete Amazon S3 file, folder and bucket. You can also perform other common amazon storage related actions (e.g. Upload / Download / Create / List ). Download SSIS PowerPack to try this component and 70+ other tasks / components which are not covered in this article.

The post How to delete Amazon S3 File / Folder / Bucket in SSIS appeared first on ZappySys Blog.

If you are looking around to find connectivity options to get Amazon AWS data in Power BI (e.g. Read from Amazon S3 files (CSV, JSON, XML) or get AWS API data such as Billing Data by calling REST API) then unfortunately as of now Power BI doesn’t support it natively.

In this article, you will learn  How to read Amazon S3 data in Power BI (Using S3 CSV Driver) and in later section we will also learn How to import data from AWS API Calls (e.g. Billing, EC2, S3, DynamoDB). We will use ZappySys REST / JSON Driver to access AWS data without any ETL or Programming.

In our previous article, we discussed how to access REST API data in Power BI (Read JSON / XML Web API). Now let’s learn how to connect to AWS in Power BI.

In this article, We will explore interesting scenarios such as below. It will help you to connect Amazon AWS in Power BI and import data from AWS without doing any ETL or programming.

• Import JSON file from S3 bucket in Power BI (Using Amazon S3 Driver for JSON Files).
• Read CSV file from S3 bucket in Power BI (Using Amazon S3 Driver for CSV Files).
• Read XML file from S3 bucket in Power BI (Using Amazon S3 Driver for XML Files).
• Call Amazon AWS REST API (JSON or XML) and get data in Power BI. Some examples of API calls.
  • Get EC2 VM count and their Status in Power BI Dashboard
  • Read data from AWS Athena Service
  • Use AWS Cost / Billing API to display monthly Cost by Service
  • Display summary of Redshift Clusters
  • Extract response from Lambda function and display in Power BI

So let’s get started…

Requirements

1. First, you will need to have Power BI Desktop (FREE) installed
2. Make sure you have AWS Access Key and Secret Key to access AWS data or call API for the desired service
3. On third place, our ZappySys ODBC Power Pack

Import Amazon S3 data in Power BI (CSV, JSON or XML Files)

In this section we will look at step by step approach to load Amazon S3 data in Power BI. Your file can be compressed  (GZip, Zip) or un-compressed. We will use ZappySys Amazon S3 driver for CSV Files for demo but you can also use Amazon S3 JSON Driver or Amazon S3 Driver for XML Files same way for reading different file formats.

Configure ODBC DSN for Amazon S3 Files ( JSON / XML / CSV )

1. Type odbcad32.exe in your search box and launch the DSN Config utility.
2. you want access for yourself then stay of User DSN Tab. If you want grant access other users then go to System DSN tab. For SQL Server Integration go to System Tab and add new System DSN rather than User DSN. Click New button.
   
3. From the Driver list Select ZappySys ODBC Driver. For this example select [ZappySys Amazon S3 CSV Driver].
   
4. Now, we need Amazon S3 Storage Connection. Lets create it.
   
5. Now, When you see DSN Config Editor with zappysys logo first thing you need to do is change default DSN Name at the top and Select your bucket and file from it.
   
6. Here, in the Compression (Zip/GZip) tab set suitable file format.
   
7. Click on Preview Tab, Select Table from Tables Dropdown and select [value] and click Preview.
   
8. If you are using DSN method then Click OK to save our DSN Configuration.

Load Amazon S3 Data in Power BI – using ODBC Driver Connection

In the previous section, we configured ODBC DSN for AWS API call and added the ZappySys drivers in the ODBC Driver Administrator with information to connect to AWS S3 Files. We queried S3 File using ZappySys Amazon S3 Driver for CSV Files. Now we will open Power BI and import the information from ODBC  DSN we defined earlier.

1. Open Power BI Desktop and select the option Get data
   

   Get data in power bi

2. Get Data will allow adding the ZappySys ODBC driver. Go to Other and select ODBC.
   

   Select odbc in Power BI

3. Select ODBC DSN name from the DSN dropdown
4. Now its time to import data. Basically, there are two modes to import data. Table Mode and Query Mode. We will Import using Power BI Query Mode
5. Select your DSN and click Advanced Option to enter custom SQL Query to Import your REST API data. You can use ODBC DSN Data sources Preview tool to generate SQL Query. For example, you can enter a query like below. WITH clause is optional but you can supply many options to override DSN UI settings (e.g. Path, Credentials ).
   

   /*--------- Amazon S3 Driver - Read CSV File Example - Override UI credentials in WITH clause ----------*/  
   SELECT * FROM $  
   WITH (  
     Src='Northwind-Bucket/Orders*.csv' --use wildcard * for pattern search
     -- ,AccessKey='AKIAxxxx' --not needed if you set in DSN connection
     -- ,SecretKey='a1wxxxxxxxxxxxxxx' --not needed if you set in DSN connection
     -- ,RegionName='us-west-1'
     -- ,ColumnDelimiter='|'
     -- ,HasColumnHeaderRow='False'
   )

   
6. On the next screen select Windows Authentication to continue (No userid and password).
   

   Select Windows Credentials to connect to zappysys driver

7. Click OK to import data in Power BI
8. Now you can create custom Dashboard from imported Dataset.

AWS API Example –  Call Amazon S3 API in Power BI

In our previous section we saw how to read Amazon S3 data using native ZappySys S3 Drivers (For CSV , JSON and XML Files), this approach is preferred way to read S3 Files for sure because it gives you UI to browse files, it gives you ability to read from multiple files and many more S3 specific features.

However in some cases you have to call REST API in a manual way using REST API driver rather than S3 Driver. In next section we will see more interesting use case of calling AWS API (e.g. Billing / Cost API).

Now lets look at steps – How to import Amazon S3 data Power BI by calling REST API manually. Steps listed below are almost identical for XML or JSON data format except for selecting Driver Type (i.e. JSON, XML, CSV).

Configure ODBC DSN for REST API ( JSON / XML / CSV )

To consume S3 data in Power BI, first we have to create ODBC DSN using ZappySys Driver (XML or JSON). Perform the following steps.

1. To do this, we will first open the ODBC Data Source (32 bit):
   

   Open odbc data source

2. Use the User DSN page and press Add
   

   Add new data source

3. Add the ZappySys XML Driver if you are accessing XML files from S3 Bucket or calling any AWS API which returns data in XML format. Select JSON driver for JSON data (or API Access in JSON Format)
   

   Create DSN using ZappySys ODBC Driver for XML / SOAP API

4. It is time to connect with Amazon S3 File and read data. In Data Source (URL or File Path), we will use XML file URL as below. Notice that S3 URL has 3 parts (zs-dump1 is bucket name, s3.us-east-1.amazonaws.com is service endpoint for S3 (some service doesn’t require region) and store_001.xml is our file name. After you specify URL select Connection as per the screenshot.Syntax for URL :  BucketName + ServiceURL + FilePath.If you are not sure what can be your service endpoint then check this table.
   

   https://zs-dump1.s3.amazonaws.com/store_001.xml
   --OR--
   https://zs-dump1.s3.amazonaws.com/mysubfolder/store_001.xml
   --OR--
   https://zs-dump1.s3.us-east-1.amazonaws.com/mysubfolder/store_001.xml

   

   Configure Amazon S3 Connection – Read from XML File or JSON File

   NOTE: If a filename contains a space, e.g. “store abc.xml“, make sure to replace space with “%20” (“+” will not work). So “store abc.xml” should become “store%20abc.xml“.
5. Once you specify the URL and Credentials, Next select Filter (This helps to flatten the nested hierarchy of your Data). If you don’t have nested Hierarchy then skip this step.
   

   Select Filter (Flatten the hierarchy to extract data from nested structure)

    

6. Now go to Preview Tab and click Preview button in the toolbar. You can remove attributes in the query to use default attributes from Previous Tab. You can always override DSN level setting inside WITH clause of SQL.
   

   Preview data from AWS S3 File (XML Data) – Use ZappySys XML Driver to Connect to AWS API

7. To learn more about query language click on View Examples
8. Click OK to save your ODBC DSN settings.

Import AWS S3 File or AWS API data in Power BI dataset

Now let’s look at how to import Amazon S3 data in Power BI using ZappySys XML driver.

In the previous section, we configured ODBC DSN for AWS API call and added the ZappySys drivers in the ODBC Driver Administrator with information to connect to AWS REST API. We queried S3 File using ZappySys XML Driver. Now we will open Power BI and import the information from ZappySys JSON Driver via ODBC connectivity option in Power BI.

1. Open Power BI Desktop and select the option Get data
   

   Get data in power bi

2. Get Data will allow adding the ZappySys ODBC driver. Go to Other and select ODBC.
   

   Select odbc in Power BI

3. Select ODBC DSN name from the DSN dropdown
4. Now its time to import data. Basically, there are two modes to import data. Table Mode and Query Mode. We will Import using Power BI Query Mode
5. Select your DSN and click Advanced Option to enter custom SQL Query to Import your REST API data. You can use ODBC DSN Data sources Preview tool to generate SQL Query. For example, you can enter a query like below.
   

   SELECT "author", "title",  "genre", "price",  "publish_date", "description", "tag"
   FROM $
   WITH(
   	 Src='https://zs-dump1.s3.amazonaws.com/store_001.xml'
   	,Filter='$.store.book[*]'
   	,ElementsToTreatAsArray='book'
   )

   

   Import JSON / REST API data in Power BI using SQL Query Mode

    

6. On the next screen select Windows Authentication to continue (No userid and password).
   

   Select Windows Credentials to connect to zappysys driver

7. Click OK to import data in Power BI
8. Now you can create custom Dashboard from imported Dataset.

AWS API Example – Import Amazon AWS Cost / Billing data in Power BI

So far you have seen how to connect to S3 File. Now let’s look at another interesting example to call AWS API and display information in Power BI dashboard. For example purpose, we are going to call this AWS Billing and Cost Analysis API. Perform following steps.

1. Create new DSN using Zappysys JSON Driver
2. Configure ODBC DSN as below
3. Enter URL as we discussed in previous section. For example to call Billing API Service for East-1 Region we need to enter following way.
   

   https://ce.us-east-1.amazonaws.com

4. Select Connection Type as OAuth and click Configure Link.
5. Select Provider as AWS API v4 and enter AWS Key and Secret. Click OK to save the connection.
6. Select Method as POST
7. Enter HTTP Request Headers as below (Note each Billing Cost API action will have different Header value for X-Amz-Target so refer API documentation
   

   Configure AWS API Connection for Cost / Billing API Data – Use ZappySys JSON Driver

8. Enter Request Body (Modify your report parameters). As you see in below request we are requesting billing data for 3 services for Jan-1-2018 till Jun-15-2018. If you dont know service name then simply refer to your Bill and copy Service Name in Values array.
   

   {
     "TimePeriod": {
       "Start":"2018-01-01",
       "End": "2018-06-15"
     },
     "Granularity": "MONTHLY",
     "Filter": {      
       "Dimensions": {
         "Key": "SERVICE",
         "Values": [
           "Amazon Simple Storage Service",
           "Amazon DynamoDB",
           "Amazon Redshift",
           "AWS Key Management Service"
         ]
       }
     },
     "GroupBy":[
       {
         "Type":"DIMENSION",
         "Key":"SERVICE"
       },
       {
         "Type":"TAG",
         "Key":"Environment"
       }
     ],
      "Metrics":["BlendedCost", "UnblendedCost", "UsageQuantity"]
   }

    
9. Select Filter as $.ResultsByTime[*].Groups[*]
10. Click Test Connection button see it shows OK.
11. If the connection is OK then switch to Preview Tab to test query.
12. You can select Table name from the drop-down or type query as below
    Simple-Query to Extract AWS Billing / Cost Information
    

    SELECT  
     "p_ResultsByTime_TimePeriod_Start" as BillStartDate,
     "p_ResultsByTime_TimePeriod_End" as BillEndDate,
     json_array_first("Keys") as ServiceName,
     "Metrics_BlendedCost_Amount" as BillAmount,
     "Metrics_UsageQuantity_Amount" as Quantity
    FROM [ResultsByTime_x_Groups] 
    ORDER BY p_ResultsByTime_TimePeriod_Start

13. You can also override attributes in your query using below syntax
    Custom-Query to Extract AWS Billing / Cost Information (WITH clause)
    

    SELECT 
     "p_ResultsByTime_TimePeriod_Start" as BillStartDate,
     "p_ResultsByTime_TimePeriod_End" as BillEndDate,
     json_array_first("Keys") as ServiceName,
     "Metrics_BlendedCost_Amount" as BillAmount,
     "Metrics_UsageQuantity_Amount" as Quantity
    FROM $
    ORDER BY p_ResultsByTime_TimePeriod_Start
    WITH(
    	 Src='https://ce.us-east-1.amazonaws.com'
    	,DataConnectionType='OAuth'
    	,ScopeSeparator='{space}'
    	,ServiceProvider='AmazonAWS'
    	--,ClientId='AKIAxxxxxxxxxxxxxxx'
    	--,ClientSecret='lPi+XQxxxxxxxxxxxxxxxx'
    	,UseCustomApp='True'
    	,Filter='$.ResultsByTime[*].Groups[*]'
    	,RequestData='{
      "TimePeriod": {
        "Start":"2018-01-01",
        "End": "2018-06-15"
      },
      "Granularity": "MONTHLY",
      "Filter": {      
        "Dimensions": {
          "Key": "SERVICE",
          "Values": [
            "Amazon Simple Storage Service",
            "Amazon DynamoDB",
            "Amazon Redshift",
            "AWS Key Management Service"
          ]
        }
      },
      "GroupBy":[
        {
          "Type":"DIMENSION",
          "Key":"SERVICE"
        },
        {
          "Type":"TAG",
          "Key":"Environment"
        }
      ],
       "Metrics":["BlendedCost", "UnblendedCost", "UsageQuantity"]
    }'
    	,Header='X-Amz-Target: AWSInsightsIndexService.GetCostAndUsage || Content-Type: application/x-amz-json-1.1'
    	,RequestMethod='POST'
    )

14. Click Preview button to see the result.
    

    Query AWS Cost / Billing Data using API in Power BI (Use ZappySys JSON Driver)

15. Click OK to save Your DSN
16. Now you can Import Billing / Cost data in Power BI using same steps as previous section (Except use custom Query and DSN we just created for AWS API call)
    

    Import AWS Billing / Cost Data in Power BI (Call AWS REST API)

17. Repeat steps to import more datasets using different queries

AWS API Example – Import Data From AWS Lambda in Power BI

Now let’s look at another scenario. Assume that someone from other team has written a Lambda Function which exposes certain data in JSON format which you want to display that in your Dashboard. Refer to this Lambda API documentation to learn more about API syntax.

Here is an example query to Call Lambda Function (submit input data in JSON and receive data in JSON format)

SELECT * FROM $
WITH(
	 Src='https://lambda.us-east-1.amazonaws.com/2015-03-31/functions/HelloWorld/invocations'
	,RequestMethod='POST'
	,RequestData='{"id":1}'
	,RequestContentTypeCode='ApplicationJson'
	
	/*** Uncomment to override DSN settings	  
	,DataConnectionType='OAuth'
	,ScopeSeparator='{space}'
	,ServiceProvider='AmazonAWS'
	--,ClientId='AKxxxxxxxxxxx'
	--,ClientSecret='lPi+Xxxxxxxxxxxxxxxxxxxxxxx'
	,UseCustomApp='True'
	***/
)

AWS API Example – Get EC2 VM information in Power BI

Now let’s look at AWS EC2 Service API (Virtual Machine Service). This API is in XML format so you have to use ZappySys XML Driver.  Below query calls this EC2 API to get list of all instances.

SELECT * FROM $
WITH(
	 ElementsToTreatAsArray='item'
	,Src='https://ec2.us-east-1.amazonaws.com/'
	,Filter='$.DescribeInstancesResponse.reservationSet.item[*].instancesSet.item[*]'
	,RequestData='Action=DescribeInstances&Version=2016-11-15'
	,RequestMethod='POST'
	/*
	,DataConnectionType='OAuth'
	,ScopeSeparator='{space}'
	,ServiceProvider='AmazonAWS'
	,ClientId='AKIAxxxxxxxxxxxxxxxxxxx'
	,ClientSecret='lPi+XQvxxxxxxxxxxxxxxxxxxxxxxxxx'
	,UseCustomApp='True'
	*/
)

Get EC2 Instance List in Power BI (Use ZappySys XML Driver)

AWS API Example – Get AWS S3 Buckets and Files Count / Size in Power BI

Now let’s look at how to Query S3 File System in Power BI. For example if you have to prepare dashboard to show Total Data Size and File count in a given Bucket then you can write following Query. For more information check Bucket List API Help

Get File Size and Count for a given S3 Bucket

SELECT count(*) as TotalFiles,sum(Size)/1024/1024 as TotalMB  FROM $
WITH(
	 ElementsToTreatAsArray='Contents'
	,Src='https://zs-dump1.s3.amazonaws.com/?list-type=2&prefix=&max-keys=1000'
	,Filter='$.ListBucketResult.Contents[*]'
	,NextUrlAttributeOrExpr='$.ListBucketResult.NextContinuationToken'
	,NextUrlSuffix='&continuation-token=<%nextlink_encoded%>'
	
	/**** Uncomment below to use override DSN values
	,DataConnectionType='OAuth'
	,ScopeSeparator='{space}'
	,ServiceProvider='AmazonAWS'
	,ClientId='AKIAxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'
	,ClientSecret='lPi+Xcxxxxxxxxxxxxxxxxxxxxxxxx'
	,UseCustomApp='True'	
	,RequestMethod='GET'
	***/
)

To list buckets you can use following query

List S3 Buckets

SELECT *  FROM $
WITH(	 
	 Src='https://s3.amazonaws.com'
	,Filter='$.ListAllMyBucketsResult.Buckets.Bucket[*]'
	,ElementsToTreatAsArray='Buckets'

	/**** Uncomment below to use override DSN values
	,DataConnectionType='OAuth'
	,ScopeSeparator='{space}'
	,ServiceProvider='AmazonAWS'
	,ClientId='AKIAxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'
	,ClientSecret='lPi+Xcxxxxxxxxxxxxxxxxxxxxxxxx'
	,UseCustomApp='True'	
	,RequestMethod='GET'
	***/
)

Debugging / Crafting AWS API Call Request

Check below article to learn various techniques to debug and craft AWS API Request Body / Headers and URL.

How to call Amazon AWS API using SSIS (EC2, Lambda, API Gateway, SQS)

Understanding AWS REST API Pagination in Power BI

SELECT * FROM $
WITH(
SRC=@'https://zappysys.com/downloads/files/test/pagination_nextlink_inarray_1.json'
,NextUrlAttributeOrExpr = '$.nextlink'  --keep reading until this attribute is missing. If attribute name contains dot then use brackets like this $.['my.attr.name']
)

SELECT * FROM $
WITH (
SRC=@'https://zappysys.com/downloads/files/test/page-xml.aspx?page=1&mode=DetectBasedOnResponseStatusCode'
,PagingMode='ByUrlParameter'
,PagingByUrlAttributeName='page'
,PagingByUrlEndStrategy='DetectBasedOnResponseStatusCode'
,PagingByUrlCheckResponseStatusCode=401
,IncrementBy=1
)

SELECT * FROM $
WITH (
SRC=@'https://zappysys.com/downloads/files/test/cust-<%page%>.xml'
,PagingMode='ByUrlPath'
,PagingByUrlAttributeName='<%page%>'
,PagingByUrlEndStrategy='DetectBasedOnRecordCount'
,IncrementBy=1
)

SELECT * FROM $
LIMIT 25
WITH(
	 Src='https://wordpress.org/news/wp-json/wp/v2/categories?per_page=10'
	,PagingMode='ByResponseHeaderRfc5988'
	,WaitTimeMs='200' --//wait 200 ms after each request
)

Handling AWS Web API Error in Power BI

Sometimes errors occur... they just do and there is nothing you can do! Or can you? Actually, in ODBC PowerPack you can handle them in two ways.

METHOD 1 - Using Error Handling Options

When to use?

You may want to use them when your source is a resource located on the Internet; e.g. a file on a website, a file on an FTP server or just a plain API HTTP response. By default, when a remote server returns an error, data retrieval is stopped, an error is raised and no data is given back to you. This might not be always desirable.

Scenario 1

Imagine a scenario, that there is a web server which each day at 12 AM releases a new JSON file with that day's date as filename, e.g. http://www.some-server.com/data/2018-06-20.json. And, of course, you want to download it and use it daily in your Power BI report. But you have a problem: Power BI report data sources are refreshed each hour and you may get HTTP 404 status code (no file was found) when a file is not released yet. Which consequentially means other data sources won't be updated as well and you will see old and cached data on the report. That's where you could use Continue on any error or Continue when Url is invalid or missing (404 Errors) to avoid an error being raised and let other data sources to be updated.

Scenario 2

Another scenario is when you expect a web server to raise some kind of HTTP error when accessing a URL. You don't want ODBC Data Source to raise an error but instead, you want to get response data. That's where you can use Continue on any error or alike together with  Get response data on error to continue on an error and get the data:

METHOD 2 - Using Connection [Retry Settings]

Another scenario you may run into is a buggy web server. You ask it to give you some file or data and it, like a snotty kid, just doesn't give it to you! You have to ask twice or thrice before it does its job. If that's the case, you have to retry HTTP requests using Connection:

Other Considerations for Calling AWS API in Power BI

Conclusion

In this article, we show how to connect to AWS API and S3 File data in Power BI. We configured ODBC DSN for AWS S3 / REST API connection and finally imported data in Power BI.  We used ZappySys driver for JSON that can be used to extract data from any REST API or a JSON file.  Download ODBC PowerPack to try yourself see how easy it is to consume XML / JSON / REST API and AWS data in Power BI and Say goodbye to ETL or Coding.  If you need any help with your API integration feel free to contact zappysys support you will be amazed for sure how quickly your issue is resolved.

The post Read Amazon S3 data in Power BI or Call AWS REST API (JSON / XML) appeared first on ZappySys Blog.

In our previous post we explored unlimited possibilities to call Amazon AWS API using SSIS. Now in this post we will learn how to import / export data from Amazon Athena using SSIS. Amazon Athena is very similar service like Google BigQuery which we documented already.  To read data from Amazon Athena we will use ZappySys JSON / REST API Source which supports excellent JSON parsing capability like this.

Prerequisites

Before we do hello world demo for calling Amazon AWS API, you will need to make sure following prerequisites are met.

1. SSIS designer installed. Sometimes it is referred as BIDS or SSDT (download it from Microsoft site).
2. Basic knowledge of SSIS package development using Microsoft SQL Server Integration Services.
3. Access to valid AWS credentials (Access Key, Secret Key for your IAM User). Click here to learn more about IAM users and Access Key/Secret Key
4. Make sure SSIS PowerPack is installed. Click here to download.

Steps needed to read data from Amazon Athena

To read data from Amazon Athena you need to do atleast 3 steps at very high level. Later on this article we will see each step in depth.

1. Call StartQueryExecution API to send SQL Query (Its Job Style API so this call starts Job)
2. Keep checking Job Status by calling  GetQueryExecution API (In the response check State field for Status – We need to look for word SUCCESS)
3. Once Job is finished it produces CSV file in S3 Bucket (Output Location is supplied in Step-1)

Read Amazon Athena Query output in SSIS (S3 CSV files)

AWS Console – Athena Query Editor / Configure Output Settings

Few things you might have to setup before you can call Athena API in SSIS

1. Make sure your IAM user has correct permission (We used existing policies for ease of use but you can use custom policy for precise permission set)
2. Configure default output location for your Athena queries

Configure IAM user permission to call Amazon Athena API

Set Athena Query Output Location

Testing Athena Query inside Amazon AWS Console (Query Editor)

Creating Connection to call Athena API in SSIS

Any API calls made to Amazon Athena service using ZappySys JSON / REST API Source  or  ZS REST API Task needs OAuth connection.

For REST API Task configure as below (More details about using REST API Task is in the next section).

1. Drag ZS REST API Task from Control Flow Toolbox
2. Double click to edit.
3. Change Request URL Access Mode to [Url from Connection]
4. Now select <<New OAuth Connection>> from connection drop down
5. On OAuth connection select Amazon AWS API v4 as Provider
6. Enter your Access Key and Secret Key

Create SSIS Connection for Amazon AWS API Call (Athena REST API Example)

Creating Table in Amazon Athena using API call

For this demo we assume you have already created sample table in Amazon Athena. If you wish to automate creating amazon athena table using SSIS then you need to call CREATE TABLE DDL command using ZS REST API Task.

1. In the previous ZS REST API Task select OAuth connection (See previous section)
2. Enter Request Url as below
   
   

   https://athena.us-east-1.amazonaws.com/

3. In the HTTP Headers enter below 2 headers
   

   X-Amz-Target: AmazonAthena.StartQueryExecution
   Content-Type: application/x-amz-json-1.1

4. Change Request method to POST
5. In the Body enter below
   

   {
    "ResultConfiguration": {
    "OutputLocation": "s3://my-bucket/output-files/"
    },
    "QueryString": "create external table tbl01 (CustomerID STRING, CompanyName STRING) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' LOCATION 's3://my-bucket/input-files/';",
    "ClientRequestToken": "{{System::ExecutionInstanceGUID}}"
   }

   Notice: Rather than using hard coded  DDL SQL Statement we can use variable placeholder (e.g.

   "QueryString": "{{User::Query,FUN_JSONENCODE}}"

      ). Use 

   FUN_JSONENCODE

    to replace new line with \r\n else JSON becomes invalid.
6. Now click Test Request / Response. This will create a new Athena table which we will query in later section.

Notice that in above Body ClientRequestToken is a unique number each time you have to call StartQueryExecution API to make it simple we used SSIS system variable System::ExecutionInstanceGUID. Its unique for each execution. You can also use newid() function from SQL Server and save result to variable if you like.

Here is the screenshot of above Request

RESt API Task – Create table in Amazon Athena using SSIS (StartQueryExecution API Call)

Uploading data for Amazon Athena (Source files)

Once you have athena table created, we will need some data to query. Loading data to amazon athena table is nothing but upload files to S3. If you noticed we added below line in CREATE TABLE statement in the previous section. This means all source files are located at this S3 location.

LOCATION 's3://my-bucket/input-files/'

We have written blog post to explain this process (Click Here – How to load data from SQL server to S3 files).

Extract data from Amazon Athena using SSIS (Query Athena)

Now its time to read some data by writing SQL query for Athena data (i.e. S3 files). As we mentioned earlier, reading data from Athena can be done using following steps.

1. Call  StartQueryExecution API  using REST API Task to execute your Query (It returns you QueryExecutionID). Use same technique as Create Table example. Replace CREATE Table command in body with your SQL Query (New line must be replaced by \r\n in JSON).
2. Use REST API Task to call GetQueryExecution API and configure periodic status check loop (Task keeps waiting until Success or Failure Value not found in Response)
3. Once data is available read data using S3 CSV File Source
4. At last you can clean up query output files or keep it if some other process wants to read it (You can also clean up S3 files using bucket retention policy automatically at scheduled interval).

Now lets see each step in depth

Step1-Start Amazon Athena Query Execution

Now first thing is to execute Athena Query by calling StartQueryExecution API . Below steps are almost same steps as we saw in section Creating Table in Amazon Athena using API call

Only part is different here is SQL query is SELECT query rather than CREATE TABLE.

1. Drag and drop ZS REST API Task from SSIS toolbox
   
2. Enter Request Url as below
   
   

   https://athena.us-east-1.amazonaws.com/

3. In the HTTP Headers enter below 2 headers
   

   X-Amz-Target: AmazonAthena.StartQueryExecution
   Content-Type: application/x-amz-json-1.1

4. Change Request method to POST
5. In the Body enter below
   

   {
     "ResultConfiguration": {
       "OutputLocation": "s3://my-bucket/output-files/"
     },
     "QueryString": "select * from sampledb.elb_logs\r\nlimit 100000",
     "ClientRequestToken": "{{System::ExecutionInstanceGUID}}"
   }

   Notice: Rather than using hard coded  SQL Query we can use variable placeholder (e.g.

   "QueryString": "{{User::Query,FUN_JSONENCODE}}"

      ). Use 

   FUN_JSONENCODE

    to replace new line with \r\n else JSON becomes invalid.

   

6. Now go to Response Settings Tab and configure below way to extract QueryExecutionId (we will need it later).

   Set Extract Type as Json.
   Enter Expression as

   $.QueryExecutionId

   Check Save output to Variable and create new Variable (we can name as QueryExecutionId )
   

   Call Athena SQL, Save Amazon Athena QueryExecutionId in SSIS Variable

7. That’s it now we can move to next step

Step2 – Wait until Athena Query Execution is done

New version of ZS REST API Task includes Status check feature. This feature avoids complex looping logic. Here is how to configure to check Job Status (Wait until Query execution is finished). Steps are almost same as previous section except three things ( Headers, Body and Status Check Tab)

For Status check we will call GetQueryExecution API .

1. Drag and drop ZS REST API Task from SSIS toolbox
   
2. Enter Request Url as below
   
   

   https://athena.us-east-1.amazonaws.com/

3. In the HTTP Headers enter below 2 headers
   

   X-Amz-Target: AmazonAthena.GetQueryExecution
   Content-Type: application/x-amz-json-1.1

4. Change Request method to POST
5. In the Body enter below
   

   {"QueryExecutionId": "{{User::QueryExecutionId}}"}

   Notice: Here we have used Variable in the body. This variable we extracted in the previous step. It contains QueryExecution ID for the Job we submitted.
   

   SSIS Amazon Athena – Call GetQueryExecution API (Status Check)

6. Now go to Status Check Tab and configure below way to implement Status check loop. We want to stop check once status is SUCCESS or FAILED or CANCELLED. If we find FAILED or CANCELLED in State field then we must fail the step with error.
   1. Check Enable Status Check
   2. Enter Success Value as

      SUCCEEDED

   3. Check Fail Task option and enter this regex in the text box 

      FAILED|CANCELLED

   4. In the Interval enter 5 seconds delay after each iteration.
7. That’s it. Status check Tab will look like below. Now we can move to next step
   

   REST API Status check Loop – Keep checking until JOB is done

Step3-Read data from Athena Query output files (CSV / JSON stored in S3 bucket)

When you create Athena table you have to specify query output folder and data input location and file format (e.g. CSV, JSON, Avro, ORC, Parquet …) they can be GZip, Snappy Compressed. Once you execute query it generates CSV file. Zappysys can read CSV, TSV or JSON files using S3 CSV File Source or S3 JSON File Source connectors. In this section we will use CSV connector to read Athena output files.

Here is how to Athena output data

1. Drag and drop Data flow task from SSIS Toolbox
   
2. Double click data flow and drag and drop  ZS Amazon S3 CSV File Source
   
3. Double click to configure it.
4.  Click New Connection and configure S3 Connection
5. Once connection is created, browse to S3 bucket / folder location where Athena outputs files.
6. Replace file name with variable like below
   

   my-bucket/output-files/{{User::QueryExecutionId}}.csv

    

Reading data from Amazon Athena CSV files (Stored in S3)

Putting all together – Athena Data Extract Example

Here is final package with all pieces we talked.

Conclusion

You have seen that using ZappySys SSIS PowerPack how quickly you can integrate with Amazon Athena and other AWS Cloud Services.  Download SSIS PowerPack and try it out by yourself.

Keywords: Extract data from Amazon Athena | Read from Amazon Athena Query file | Import / Export data from Amazon Athena | Fetch data from Amazon Athena

The post Import / Export data from Amazon Athena using SSIS appeared first on ZappySys Blog.

In this blog post you will learn how to call Amazon AWS API using SSIS (virtually any API) without a single line of code (No more JAVA, C#, Ruby, Python). Yes you heard it right 🙂 . If you are a SSIS / ETL Developer or even coder everyone loves drag & drop interface. SSIS has many advantages over other approaches such as Programming SDKs, Command Lines. Main advantage is ease of use, security and long term maintenance without learning expensive coding approach.

In this post we will use following components to show various possibilities to implement Amazon AWS API integration scenarios inside your ETL workflows.

	JSON / REST API Source (REST API, JSON File or OData Service): Use this dataflow component when you have to fetch data from REST API webservice like a table. This component allows you to extract JSON data from webservice and de-normalize nested structure so you can save to Relational database such as SQL Server or any other target (Oracle, FlatFile, Excel, MySQL). This component also supports reading local JSON files or direct JSON string (Wildcard pattern supported too e.g. c:\data\file*.json).
	Web API Destination (POST data to API URL) : Use this dataflow component when you have to call API inside Dataflow (see POST to URL). Possible Use case: Call Lambda function with various parameters for each input record found in database.
	REST API Task : Use this task when you don’t want to pull REST API data in tabular format but want to call rest API for POST data to server, DELETE data from server or things like download HTML page, extract Authentication tokens etc where you not necessarily dealing data in tabular format. This task also allows you many other options such as saving RAW response into variable or file.
	XML Source (SOAP, File, REST) : Use this dataflow component when you have to fetch data from XML or SOAP webservice and consume data like a table. This component allows you to extract data from webservice and save to SQL Server or any other target (Oracle, FlatFile, Excel, MySQL). This component also supports reading local XML files or direct XML string.

Prerequisites

Before we do hello world demo for calling Amazon AWS API, you will need to make sure following prerequisites are met.

1. SSIS designer installed. Sometimes it is referred as BIDS or SSDT (download it from Microsoft site).
2. Basic knowledge of SSIS package development using Microsoft SQL Server Integration Services.
3. Access to valid AWS credentials (Access Key, Secret Key for your IAM User). Click here to learn more about IAM users and Access Key/Secret Key
4. Make sure SSIS PowerPack is installed. Click here to download.

Step-By-Step Example-1 (Call AWS API)

Now lets call some simple GET API call using SSIS REST API Task.

1. Install  SSIS PowerPack (Skip this step if you already installed SSIS PowerPack.
2. Open Visual Studio and create new Integration Services Project
3. Open SSIS Package and check your SSIS Toolbox you will see many tasks/components starting with ZS
4. From Control flow SSIS Toolbox Drag & drop ZS REST API Task.
5. Double click the REST API task to configure it.
6. On REST API Task change URL Access mode drop down to URL from Connection
7. Now in the connection dropdown click New ZS-OAUTH connection and configure connection as below
   1. Once you see OAuth connection dialog box change Provider Type from Custom to Amazon AWS API (v4)
   2. In the ClientId enter your AWS Access Key
   3. In the ClientSecret enter your AWS Secret Key
   4. Click OK to save connection
      

      Configure SSIS OAuth Connection – Use Amazon AWS API Provider, Enter Access Key, Secret Key

8. On REST API Task change few more settings as below
   1. Enter API URL you like to call (In our case we will use S3 API (Simple Storage Service). We assume you have ListBucket permission to make this call. If you dont have such permission try to get Full path of File (choose small file) . You have to tweak API url to adjust Service Type, Region,Bucket, Path
      

      https://s3.us-east-1.amazonaws.com
      -- OR -- Use below (list files) if you have single bucket permission---
      https://s3.us-east-1.amazonaws.com/YOUR-BUCKET

   2. Click Test Request. If you have valid Permission and setup looks ok then you will see Response window like below. Using this technique you can call any API to execute AWS operations (E.g. start EC2 VM, Create SQS Queue, Call Lambda Function, Drop or Update resource)
      

      Calling Amazon AWS API Using SSIS REST API Task Example. (Call any AWS API without SDK. such as EC2 API, SQS API, Lambda API, Redshift API, DynamoDB API)

Step-By-Step Example-2 (Loading data from AWS API to SQL Server)

Now lets do more interesting scenario. We will call AWS S3 API to get S3 File list from Bucket. After extract we will save that list to SQL Server Table. Since Amazon S3 API is XML based API we will use ZappySys SSIS XML Source. For JSON based API use JSON Source instead. XML Source / JSON Source both can parse API response into Rows and Columns so you can easily store it into SQL Server. Now lets see how to do this.

1. From Control flow SSIS Toolbox Drag & drop Data Flow Task
2. Double click Data Flow Task. From SSIS Toolbox Drag & drop ZS SSIS XML Source.
3. Double click the XML Source to configure it.
4. In the URL text box enter API URL like below to list S3 Files for specified bucket (Change YOUR-BUCKET to your own name)
   

   https://s3.us-east-1.amazonaws.com/YOUR-BUCKET

5. Now check Use Credentials and Select same Amazon API connection we created in previous example.
6. Click on Select Filter (This step allows us to flatten the XML hierarchy. Select the node which is Array icon like below. If prompted to treat selected node as array click Yes.
   

   Configure SSIS XML Source – Get Amazon S3 File List from specific bucket (AWS API)

7. Click Preview to see your data. Click OK to save.
   

   Preview Data in XML Source – Amazon S3 File List (Calling AWS API)

8. Now attach your XML source to target like OLEDB Destination to load data to SQL Server or other Target (e.g. Oracle, MySQL)
9. Execute SSIS Package to load data from Amazon AWS API to SQL Server.
   

   SSIS Package – Read Amazon S3 File List and load into SQL Server Table (Call AWS API Example)

File Upload Example – Low level API – Call PUT request

There will be a time when you want to take total control of your AWS API calls. One example is if you wish to Upload / Write data to S3 then components like ZappySys Amazon S3 CSV Destination or Amazon Storage Task might need additional permission such as HeadObject . If you have only write permission on bucket then this will fail to execute Task. In such case you can use REST API Task like below way.

Basically we exported data from Relation Database to CSV File using Export CSV File Task and then we uploaded file content using REST API Task.

Upload Text File to S3 (i.e. JSON, CSV, XML …)

Your URL Format can be like this. Region codes can be found here

https://YOUR-BUCKET.s3.YOUR-REGION.amazonaws.com/YOUR-FILE
https://YOUR-BUCKET.s3.YOUR-REGION.amazonaws.com/SOME-FOLDER/SOME-SUB-FOLDER/YOUR-FILE

Upload file to Amazon S3 – Call low level API (PUT request)

Upload Binary File to S3 (i.e. Zip, mp3, gzip, png, jpeg…)

Above method only works for Text Files. If you have Binary files (e.g. Zip file, mp3, png, jpeg) then you can use below workaround.

1. Check Is Multi Part / File Upload Option next to the Body editor (Read this Post for more info)
2. In the Body enter file path like below
   

   @c:\folder\some-file.xyz

3. That’s it, now your binary file can be uploaded to S3 same way as Text file we uploaded in earlier section.

NOTE: Binary file option only works in the latest Build Uploaded after 5/21/2020

Debugging AWS API Command Line Requests using Fiddler (Web Proxy)

Before we see more examples of calling AWS API lets first learn how to capture Request data using aws command line (CLI). We will use Fiddler to capture AWS API Requests.

1. Download and Install Fiddler (Free Tool)
2. Install  aws command line
3. Open command prompt and type aws configure command to set credentials.  For more info see configure aws credentials .. see below example.
   

   c:> aws configure
   AWS Access Key ID [None]: AKIAIOSFODNN7EXAMPLE
   AWS Secret Access Key [None]: wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
   Default region name [None]: us-west-2
   Default output format [None]: json

4. Once you set credentials launch Fiddler
5. On the Fiddler Tools menu > Click Fiddler Option > HTTPS > Check Decrypt HTTPS Traffic
6. Once you do that you may be asked to Trust Fiddler Certificate click OK
7. Close and Open Fiddler to apply setting
8. Now any command you type in aws command line will show up in fiddler. This command we can use in SSIS REST API Task or XML Source to call virtually Any API AWS supports.
9. For example to call some lambda function (supply input json data from file) use below command and watch Fiddler Trace. Notice we added –no-verify-ssl option so we can see requests in custom web proxy like fiddler (This option will trust Fiddler certificate).
   

   c:\>aws lambda invoke --function-name HelloWorld c:\temp\outputfile.txt --no-verify-ssl --payload file://c://test/customer.json

    
   

   Capture AWS Commandline (CLI) request using Fiddler

10. Once you have this information you can use it inside ZappySys Components which supports API calls (e.g. REST API Task, JSON Source, XML Source). For this example we will use REST API Task to call same Lambda Function. Things to change to call any API is URL, Method, ContentType, Body. If its GET call then you wont have Body.
    

    Calling Amazon AWS Lambda Function using SSIS REST API Task

     

11. That’s it.. You can now take this same concept and call virtually API AWS API right insight SSIS without any SDK or command line tools.

Call API Gateway Endpoint (Default URL)

If you wish to call API hosted on Amazon API Gateway Service then enter direct URL. You have to use OAuth Connection (AWS v4 Provider) as previous section.

Typical URL may look like as below if you calling API gateway Endpoint.

https://c5hhigf5mh.execute-api.us-east-1.amazonaws.com/prod/pets

Call AWS API with Region and Custom Service Name

There will be a time when you will have to call AWS API URL and it doesnt indicate Region / Service but you have to supply part of signature for Authentication.  In this case just enter AWS Service and Region along with ClientID, Secret Fields (Custom Service and  Region attributes were introduced in v3.0 or higher so if you are not seeing on OAuth Connection UI then you probably running older version).

Call Amazon Athena API

Check this article for detailed instructions

Call AWS EC2 API

Here is an example of calling EC2 API. This is example of listing EC2 instances.

Request:

POST https://ec2.us-east-1.amazonaws.com/
Content-Type: application/x-www-form-urlencoded; charset=utf-8

Action=DescribeInstances&Version=2016-11-15

Call AWS Lambda API

Here is some example of calling Lambda function

Request:

POST https://lambda.YOUR-REGION.amazonaws.com/2015-03-31/functions/YOUR-FUNCTION/invocations

{you-json-input-goes-in-body}

Call AWS ElasticSearch

If you are using AWS Hosted Managed ElasticSearch then also you can use OAuth AWS v4 Provider as below. Assuming you have configured correct Policy to allow your IAM User Account / IP address.

Call AWS Hosted ElasticSearch REST API in SSIS (V4 Request Signing)

Call AWS API using Native Task/Components

ZappySys provides many High quality Tasks / Components for AWS integration. See below list.

Amazon AWS Cloud Integration
Amazon S3 Task	Amazon Redshift Data Transfer Task	Amazon Redshift ExecuteSql Task
Amazon Redshift Cluster Management Task	Amazon DynamoDB Source	Amazon DynamoDB Destination
Amazon Redshift Source	Amazon SQS Queue Source	Amazon SQS Queue Destination

Conclusion

Amazon AWS Cloud integration from SSIS packages becoming more and more common scenario. ZappySys provides easy to use no coding connectors to achieve many time consuming scenarios. Having clean drag and drop approach is not only faster but more secure using inbuilt SSIS framework. Try SSIS PowerPack to explore many other scenarios not discussed in this article.

The post How to call Amazon AWS API using SSIS (EC2, Lambda, API Gateway, SQS) appeared first on ZappySys Blog.

Sometimes if you loading data to Redshift via COPY command or using SSIS Redshift Data Transfer Task to move data to redshift then you will have to make sure your S3 Bucket is in the same region as Redshift Cluster. Many people don’t know how to verify that because its hidden in the console. This post will help you to find it easily.

Find Amazon S3 bucket location (AWS Region endpoint)

Below is step-by-step instructions how to find S3 Bucket region (i.e. location)

1. Open your AWS Console by visiting https://console.aws.amazon.com/
2. From dashboard click on S3 option (or visit https://console.aws.amazon.com/s3/home )
3. You will see all buckets in the left side list
4. Click on desired S3 bucket name
5. Click on Properties Tab at the top
6. Now you will see Region for the selected bucket along with many other properties.

Sometimes You may see US Standard as region name that means your bucket is located in US East (N. Virginia)

If you want to know Region Code rather than name check this link : Region Endpoints for Amazon S3

How to find amazon s3 bucket location (AWS region endpoint)

Download/Upload data to S3 bucket via Command line

If you want to automate S3 file download/upload then check this command line tool

ZappyShell Command line tools for Amazon S3

Upload local files to Amazon S3 from command line

List S3 buckets using command line

List S3 file information using command line

List S3 files using command line

Download/Upload data to S3 bucket from SSIS

Load data to Amazon Redshift using S3 Bucket and COPY command

Below video shows how to use S3 bucket to perform bulk data load into Amazon Redshift using SSIS Redshift Data Transfer Task

Conclusion

Amazon S3 provides most common way to store/load data for various AWS related services (e.g. EMR, Redshift). Zappysys is one of the top leading providers who make tools for AWS, NoSQL and other Cloud connectivity providers. Check SSIS PowerPack (For SSIS) or ZappyShell Command line for AWS if you want command line solution. ZappyShell is just single exe file does all heavy lifting for you 🙂

Cheers!

The post How to check Amazon S3 Bucket location (Region) appeared first on ZappySys Blog.

In our previous article we saw how to load data into Redshift using SSIS or load data into Redshift using ZappyShell Redshift Command Line

In this article we will walk through various steps to Extract/UNLOAD Redshift Data into SQL Server using Amazon S3 Storage Task and ExecuteSQL Task for Amazon Redshift. Below is the screenshot of actual SSIS Package to Extract Redshift Data and Load into SQL Server

Extract/Unload Redshift Data using SSIS and Load into SQL Server

Requirements for Extract Redshift Data using SSIS

Before you UNLOAD data from Redshift, you have to make sure few things.

1. Setup your Redshift cluster (Follow these instructions to setup redshift cluster)
2. Load some sample data to Redshift (Red more here: How to load data to Redshift)
3. Make sure you have correct connection settings to connect to Redshift cluster (Host name, Port, UserId, Password, DB name etc). You can get host name from AWS Console.
4. Make sure you have Access to S3 Bucket where files will be dumped from Redshift. You will need AccessKey and SecretKey to fetch files from S3

Step-1: Execute Redshift UNLOAD Command

Very first step would be to unload redshift data as GZip file using ExecuteSQL Task for Amazon Redshift
Below is SQL Command you can use to extract data from Redshift. Notice how we used variable placeholders in SQL Command. These placeholders are replaced at runtime with actual value stored in specified variable.

unload ('select * from (select * from customerdata limit 1000)')
to 's3://bw-rstest/stage/custdata'
credentials 'aws_access_key_id={{User::S3Accesskey}};aws_secret_access_key={{User::S3SecretKey}}'
ALLOWOVERWRITE

Export as GZip files (Compressed files)

If you exporting data as compressed files to save data transfer cost then use GZIP option as below.

NOTE: Make sure there are no spaces before and after AccessKey and SecretKey otherwise you may get error.

unload ('select * from (select * from customerdata limit 1000)')
to 's3://bw-rstest/stage/custdata_file_'
credentials 'aws_access_key_id={{User::S3Accesskey}};aws_secret_access_key={{User::S3SecretKey}}'
ALLOWOVERWRITE
GZIP

Common Errors / Troubleshooting

UNLOAD command issue with Region mismatch (S3 bucket vs Redshift Cluster)

If your S3 bucket is in different region than Redshift cluster then above command may fail with “301 permanent redirect error” in that case you have to change your S3 bucket region. Region can be changed in AWS console (See S3 bucket properties and change location to match region with Redshift cluster region. Both regions must be same.

ERROR: XX000: S3ServiceException:The bucket you are attempting to access must be addressed using the specified endpoint. Please send all future requests to this endpoint.,Status 301,Error PermanentRedirect

UNLOAD command issue with accesskey and secret key

If you specify invalid accesskey or secretkey –or– you have misspelled keywords related to credentials — or — you have spaces before or after accesskey or secret key then you may get following error.

ERROR: XX000: Invalid credentials. Must be of the format: credentials ‘aws_iam_role=…’ or ‘aws_access_key_id=…;aws_secret_access_key=…[;token=…].

Step-2: Download data files from Amazon S3 Bucket to local machine

Once files are exported to S3 bucket we can download then to local machine using Amazon S3 Storage Task

Step-3: Un-compress downloaded files

If you have exported Redshift data as compressed files (using GZIP option) then you can use ZappySys Zip File task to un-compress multiple files.

Or you can write Script to un-compress those files (see below code). You can skip this step if files are not compressed (not used GZIP option in command).

Here is sample C# code to un-compress GZip files

public void Main()
{
	System.IO.DirectoryInfo directorySelected = new System.IO.DirectoryInfo(@"C:\amazon\archive");

	foreach (System.IO.FileInfo fileToDecompress in directorySelected.GetFiles("custdata*_part_*"))
	{
		Decompress(fileToDecompress);
	}

	Dts.TaskResult = (int)ScriptResults.Success;
}
private static void Decompress(System.IO.FileInfo fileToDecompress)
{
	using (System.IO.FileStream originalFileStream = fileToDecompress.OpenRead())
	{
		string currentFileName = fileToDecompress.FullName;
		string newFileName = currentFileName.Remove(currentFileName.Length - fileToDecompress.Extension.Length);

		using (System.IO.FileStream decompressedFileStream = System.IO.File.Create(newFileName))
		{
			using (System.IO.Compression.GZipStream decompressionStream = new System.IO.Compression.GZipStream(originalFileStream, System.IO.Compression.CompressionMode.Decompress))
			{
				decompressionStream.CopyTo(decompressedFileStream);
				//Console.WriteLine("Decompressed: {0}", fileToDecompress.Name);
			}
		}
	}
}

Step-4: Loop through files using ForEachLoop Container

Once files downloaded from S3 bucket we can now loop through files using SSIS ForEach Loop Task and load into SQL Server (One file in each iteration)

Loop through files downloaded from Amazon S3 (Exported using Redshift UNLOAD Command)

Step-5: Data Flow – Load Redshift Data Files to SQL Server

Inside data flow you can use Flat File source and OLEDB Destination for SQL Server. Just map correct File columns to SQL Server fields and you should be good. If needed convert Unicode/Non-unicode columns using Data Conversion Transform (This is not needed if source is DT_STR and target also DT_STR.. or source is DT_WSTR and target is DT_WSTR i.e. Unicode).

Downloads

To download above SSIS Package click on the below links. In order to test below package you first have to download SSIS PowerPack
Download Demo SSIS Package – SSIS 2008
Download Demo SSIS Package – SSIS 2012/2014

Conclusion

amazon Redshift is great way to start your data warehouse projects with very minimum investment in a very simple pay as you go model but loading or unloading data from redshift can be challenging task. Using SSIS PowerPack you can perform Redshift data load or unload in few clicks.

The post Extract / Unload Redshift data into SQL Server using SSIS appeared first on ZappySys Blog.