Ability to work with compressed data in a data-warehouse is well understood. It becomes even more pronounced when warehouse size runs in hundreds of terabytes and petabytes. Hodaap provides a way to interact with compressed files natively. Tools like Hive and Pig can read these compressed files and process them, thereby reducing storage requirements to a great extent.

In this post, I am going to describe how easily a hive query can be executed against a compressed data file. All screen shots are from my HDInsight cluster.

I am also using the new Windows Azure Powershell tool to interact with my HDInsight cluster. This is pretty straight forward and simple to interact.

(1) I first used the following commands to connect to my HDInsight cluster

# Provide Windows Azure subscription name, and the Azure Storage
  account and container that is used for the default HDInsight file system.

$subscriptionName = "Windows Azure MSDN - Visual Studio
  Ultimate"

$storageAccountName = "mydemocluster"

$containerName = "sample"

 

# Provide HDInsight cluster name Where you want to run the Hive job

$clusterName = "mydemocluster"

Add-AzureAccount

Select-AzureSubscription -SubscriptionName $subscriptionName

Use-AzureHDInsightCluster $clusterName

 

Although I have used "Add-AzureAccount" to authenticate myself on the interactive console. The same can also be scripted using certificates.

(2) Next, I created a sample table by invoking Hive for the PowerShell

$queryString = "CREATE EXTERNAL TABLE Sample_Data
  (Exchange STRING,Stock   
  STRING,Date     STRING,
  High     STRING,Low      STRING,Open     STRING,Close    STRING,Field1   STRING,Field2   STRING) ROW FORMAT DELIMITED FIELDS
  TERMINATED BY ',' STORED AS TEXTFILE LOCATION '/Data/HiveExternal';"

Invoke-Hive -Query $queryString

 

Notice that I have created an external table in hive as I am not doing any aggregation in this example.

(3) Now I will move compressed file in this location so that I can run hive query on this data. I am using Cloud Explorer to move file. Cloud Explorer also has a free version and presents a windows explorer like interface to interact with azure blob storage.

SampleZipFile.zip contains a bunch of CSV files all compressed together. The files are copied to the same location where the external hive table is point to.

(4) Now that data is in there, I can simple query this data using hive query. Hive will automatically run map/reduce jobs on the data nodes which hold a chunk of this compressed file!!

$queryString = "select count(*) from sample_data;"

Invoke-Hive -Query $queryString

 

That's it !!!