I am considering HDInsight with Hive and data loaded on Azure Blob Storage.
There is a combination of both historic and changing data.
Does the solution mentioned in Update , SET option in Hive work with blob storage too?
The below Hive statement change the data in blob storage which is my requirement too?
INSERT OVERWRITE TABLE _tableName_ PARTITION ...
INSERT OVERWRITE will write new file(s) into the cluster file system. In HDInsight the file system is backed by Azure blobs, the wasb://... and wasb:///... names. Everything Hive does to the cluster file system, like overwriting them, will accordingly be reflected in the Azure storage BLOBs. See Use Hive with HDInsight for more details.
Related
I was following the tutorial about data transformation with azure databricks, and it says before loading data into azure synapse analytics, the data transformed by azure databricks would be saved on temp storage in azure blob storage first before loading into azure synapse analytics. Why the need to save it to a temp storage before loading into azure synapse analytics?
The Azure storage container acts as an intermediary to store bulk data when reading from or writing to Azure Synapse. Spark connects to the storage container using one of the built-in connectors: Azure Blob storage or Azure Data Lake Storage (ADLS) Gen2.
The following architecture diagram shows how this is achieved with each HDFS bridge of the Data Movement Service (DMS) service on every Compute node connecting to an external resource such as Azure Blob Storage. PolyBase then bidirectionally transfers data between SQL Data Warehouse and the external resource providing the fast load performance.
Using PolyBase to extract, load and transform data
The steps for implementing a PolyBase ELT for SQL Data Warehouse are:
Extract the source data into text files.
Load the data into Azure Blob storage, Hadoop, or Azure Data Lake Store.
Import the data into
SQL Data Warehouse staging tables using PolyBase.
Transform the data(optional).
Insert the data into production tables.
I am confused about how azure data lake store in different from HDFS. Can anyone pls explain it in simple terms ?
HDFS is a file system. HDFS stands for Hadoop Distributed File system. It is part of Apache Hadoop eco system. Read more on HDFS
ADLS is a Azure storage offering from Microsoft. ADLS stands for Azure Data Lake Storage. It provides distributed storage file format for bulk data processing needs.
ADLS is having internal distributed file system format called Azure Blob File System(ABFS). In addition, it also provides similar file system interface API like Hadoop to address files and directories inside ADLS using URI scheme. This way, it is easier for applications using HDFS to migrate to ADLS without code changes. For clients, accessing HDFS using HDFS driver, similar experience is got by accessing ADLS using ABFS driver.
Azure Data Lake Storage Gen2 URI
The Hadoop Filesystem driver that is compatible with Azure Data Lake
Storage Gen2 is known by its scheme identifier abfs (Azure Blob File
System). Consistent with other Hadoop Filesystem drivers, the ABFS
driver employs a URI format to address files and directories within a
Data Lake Storage Gen2 capable account.
More on Azure Data Lake Storage
Hadoop compatible access: Data Lake Storage Gen2 allows you to manage
and access data just as you would with a Hadoop Distributed File
System (HDFS). The new ABFS driver is available within all Apache
Hadoop environments, including Azure HDInsight, Azure Databricks, and
Azure Synapse Analytics to access data stored in Data Lake Storage
Gen2.
UPDATE
also, read about Hadoop Compliant File System(HCFS) which ensures that distributed file system (like Azure Blob Storage) API meets set of requirements to satisfy working with Apache Hadoop ecosystem, similar to HDFS. More on HCFS
ADLS can be thought of as Microsoft managed HDFS. So essentially, instead of setting up your own HDFS on Azure you can use their managed service (without modifying any of your analytics or downstream code)
I am able to access azure storage blobs from hadoop by using the folowing command
wasb[s]://#.blob.core.windows.net/
But i am not able to access Azure file. Can anyone suggest how to access azure storage files from Hadoop just like blobs ?
HDInsight can use a blob container in Azure Storage as the default
file system for the cluster. Through a Hadoop distributed file system
(HDFS) interface, the full set of components in HDInsight can operate
directly on structured or unstructured data stored as blobs.
From the official document , HDinsight only supports Azure Blob Storage.
File Storage is not supported currently.
I am new to hdinsight. On a normal in-house cluster I could create a new table and place it in an existing schema or create a new schema to retrieve it later. I can do similar methods if I create an hbase table.
If I create a table in Hive or a table in base in Hdinsight, what do I have to do before I shut down to be able to query the table I just created.
I've searched the docs, but have missed the location of the details for this procedure. I don't want to create a sql database.
In HDInsight data is stored in Azure/Blob or Azure Data lake store and Metastore is in Azure SQL DB. If you choose your own Metastore , your hive schemas could persist beyond the lifecycle of the cluster. More here https://blogs.msdn.microsoft.com/azuredatalake/2017/03/24/hive-metastore-in-hdinsight-tips-tricks-best-practices/
what command to use on hdinsight hive editor to connect to a particular storage?by b.lodefault the hive editor is connecting to the wrong storage what command should i give for it to use the right storage blob?How do i configure hive using the hive editor?
Thanks
Ajay
If your cluster was configured with multiple storage accounts, you just need to use the URI format:
wasb[s]://<containername>#<accountname>.blob.core.windows.net/<path>
Reference: http://azure.microsoft.com/en-us/documentation/articles/hdinsight-hadoop-use-blob-storage/
For example, you if you want to list the contents of 'mycontainer' in 'mystorageaccount', you can run the following through the Hive Editor:
dfs -ls wasb://mycontainer#mystorageaccount.blob.core.windows.net/;
If you haven't already configured the storage account with your cluster, you can set the required access key in the hive session like:
set fs.azure.account.key.mystorageaccount.blob.core.windows.net=LONG_KEY_GOES_HERE;
Note: The account keys are per-Storage Account, not per-Container. If you are using multiple Containers in one Storage Account, the key only has to be set once.