Tableau can be used by Data Analysts, scientists, statisticians, and others to visualize data and draw clear conclusions from Data Analysis. Tableau is well-known for its ability to handle large volumes of data quickly and produce the necessary Data Visualization results.
In this article, you are going to learn about Tableau Hive Connection and how to establish it in two easy steps.
Table of Contents
What is Tableau?
Tableau is a powerful and quickly growing Data Visualization solution. It assists in the conversion of raw data into an understandable format. Tableau aids in the development of data that can be understood by professionals at all levels of a company. Dashboards can also be created by non-technical people. Tableau facilitates Data Analysis and graphic creation in the form of dashboards and workbooks.
Data Visualization is critical because humans understand things that are visually well descriptive and interesting. Working with Data Visualization tools like Tableau can help anyone understand data better since they provide access to a big amount of data in easily digestible visuals. Furthermore, well-designed images are frequently the simplest and most efficient means of communicating any information.
Key Features of Tableau
- Usability: Tableau is simple to use and requires no technical or programming knowledge. When it comes to creating a dashboard, it works quickly. Tableau is a Data Visualisation programme that can be downloaded to mobile devices and desktop computers to make Data Access and Analysis simple. Multilingual Data Representation and Real-time Data Exploration are enabled.
- Connection and Sharing: Tableau has several advanced features, including Data Dissemination and Collaboration.
- Security: Several Data Sources are connected in a very secure manner. Importing and exporting large amounts of data is simple.
- Advanced Visualization: Tableau can produce a wide range of visualisations, from simple Pie Charts and Bar Graphs to more complicated Histograms and Gantt Charts.
What is Hortonworks Hadoop Hive?
The Hortonworks Data Platform (HDP) is an open-source system for storing and processing massive, multi-source data sets in a distributed manner. HDP helps you develop new revenue streams, improve customer experience, and minimize expenses by modernizing your IT infrastructure and keeping your data secure—in the cloud or on-premises.
Key Features of Hive
Time to Deployment and Total Cost of Ownership (TOC)
Building and deploying apps in minutes is achievable with a container-based service. Containerization allows you to run many versions of an application at the same time, allowing you to quickly add new features and develop and test new service versions without interrupting existing ones. Third-party applications are also supported by HDP in Docker containers and native YARN containers. Erasure coding improves storage efficiency by 50%, allowing for more effective data replication and a cheaper total cost of ownership.
Reduces Extraction Time for Insights
It is feasible to design and deploy a container-based service. HDP lays the groundwork for integrating GPUs (Graphics processing Unit) into Apache Hadoop clusters, boosting the speed of computations for data science and AI applications. It allows GPU pooling, which allows GPU resources to be shared among additional workloads for cost savings. It also enables GPU isolation, which dedicates a GPU to a single program and prevents other apps from using it.
Quickest Path to Insights
Without vendor lock-in to a specific cloud architecture, HDP allows you to deploy Big Data workloads in hybrid and multi-cloud settings. Customers may establish and manage Big Data clusters in any cloud environment with ease. HDP is cloud-agnostic and automates provisioning to make Big Data deployments easier while maximizing cloud resource utilization.
Single SQL Interface
To emphasize speedier queries, HDP features better query performance. The fastest Apache Hive engine, Hive LLAP, can run in a multi-tenant environment without generating resource contention. Join and aggregate queries, which are often used in Business Intelligence applications, benefit greatly from this integration. Hive provides the construction of resource pools for fine-grained resource allocations in addition to query optimization.
Security and Governance
HDP remains committed to providing comprehensive security and governance solutions. Layers of security are integrated into HDP, including authentication, authorization, accountability, and data protection. Security experts can construct classification-based security policies using security and governance integration. Furthermore, Data Governance tools allow companies to apply a consistent data classification across their whole data ecosystem.
Before beginning Tableau Hive Connection, gather the following information:
- Name of the database server to which you want to connect.
- Authentication method:
- No Authentication
- User Name
- User Name and Password
- Microsoft Azure HDInsight Service
- The following transport choices are available depending on the authentication method you select:
- The following are examples of sign-in credentials, which vary depending on the authentication type you use:
- Host FQDN
- Service Name
- HTTP Path
- Check if you are using an SSL connection.
- Install A Driver:
- To communicate with the database, this connection requires a driver. Your machine may already have the appropriate driver installed. Tableau displays a notification in the connection dialogue box if the driver is not installed on your computer, with a link to the Driver Download(Link opens in a new window) website, where you can obtain driver links and installation instructions.
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How to Establish Tableau Hive Connection?
Here are the steps to successfully establish tableau Hive Connection:
Tableau Hive Connection Process: Making the Connection
Select Hortonworks Hadoop Hive under Connect in Tableau. Select More under To a Server for a comprehensive list of data connections. Then take the following steps:
- Step 1: Enter the name of the database’s hosting server.
- Step 2: Select the authentication method to use from the Authentication drop-down list.
- Step 3: Fill in the blanks with the information you’re asked for. Depending on the authentication method you select, you will be asked for different information.
- Step 4: (Optional) Choose Initial SQL to perform a SQL statement at the start of each connection, such as when you open the workbook, refresh an extract, sign in to Tableau Server, or publish to Tableau Server. See Run Initial SQL for further information.
- Step 5: Sign In is the option to choose.
- Step 6: When connecting to an SSL server, select the Require SSL option.
- Step 7: If Tableau is unable to connect, ensure your credentials are accurate. If you’re still having problems connecting, it’s because your computer is having trouble finding the server. Please contact your network or database administrator.
Tableau Hive Connection Process: Setting Up the Data Source
The next step for Tableau Hive Connection is to go on the Data Source page and do the following:
- Step 1: (Optional) At the top of the screen, select the default data source name and then provide a unique data source name for Tableau to use. Use a data source name standard, for example, to assist other data source users in determining which data source to connect to.
- Step 2: Click the search icon from the Schema drop-down list, or type the schema name into the text field and select the search icon, then select the schema.
- Step 3: Pick the search icon in the Table text box, or type the table name and select the search icon, then select the table.
- Step 4: To begin your analysis, drag the table to the canvas and then pick the sheet tab.
Instead of connecting to the entire data source, use custom SQL to connect to a specific query. See Connect to a Custom SQL Query for further details.
Note that only equal (=) join operations are supported by this database type.
Signing in on a Mac
When connecting to a server using Tableau Desktop on a Mac, use a fully qualified domain name, such as mydb.test.ourdomain.lan, rather than a relative domain name, such as mydb or mydb.test.
Alternatively, you can add the domain to Mac’s Search Domains list so that you only have to supply the server name when connecting. Go to System Preferences > Network > Advanced, then click the DNS tab to alter the list of Search Domains.
Working with Hadoop Hive Data in Tableau Hive Connection
Tableau Hive Connection: Working with Date/Time
Tableau has built-in support for the TIMESTAMP and DATE data types. If you’re storing date/time data in Hive as a string, make sure it’s in ISO format (YYYY-MM-DD). You can make a calculated field that converts a string to a date/time format using the DATEPARSE or DATE functions. When working with an extract, use DATEPARSE(); otherwise, use DATE ().
Tableau Hive Connection: Null Value Returned
When you access a workbook produced in an older version that has date/time data stored as a string in a format that Hive doesn’t allow in Tableau 9.0.1 and later and 8.3.5 and subsequent 8.3.x releases, a NULL value is returned. To fix this, change the field type back to String and use DATEPARSE() or DATE() to convert the date in a computed field. When working with an extract, use DATEPARSE(); otherwise, use DATE().
Tableau Hive Connection: High Latency Limitation
Hive is a batch-oriented system that is not yet capable of responding to simple queries in a timely manner. This constraint can make it difficult to experiment with computed fields or explore a new data collection. Some of the more recent SQL-on-Hadoop technologies (such as Cloudera’s Impala and Hortonworks’ Stringer project) are intended to address this issue.
Tableau Hive Connection: Truncated Columns in Tableau
Hortonworks Hadoop Hive’s default string column length is 255 characters. For additional information on Hortonworks Hive ODBC driver configuration settings, including DefaultStringColumnLength, see the documentation.
You have successfully finished setting up the Tableau Hive Connection in two simple steps. You have also learned how to work with data in Hortonworks Hadoop Hive.
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