High-Performance SQL with Cloudera and Apache Impala
Today's business leaders understand the value of leveraging data to make real-time business decisions. What’s not always so clear is how to get from point A to point B. They’re dealing with overwhelming volumes of data stored across data centers and clouds and need to access, analyze, and derive meaningful insight from it securely, accurately, and efficiently.
Speed is another factor for organizations trying to query and analyze huge volumes of data. As datasets grow to a massive scale, the higher latency and processing time of batch-processing frameworks can keep an organization from achieving real-time insights. One technology that helps enable faster insights is Apache Impala, an open-source SQL query engine designed for high-performance analytics on big data. With Impala, there are several factors that work to reduce query run time, as there’s an online cluster with coordinators and a lot of executors. The user just provides the SQL query, and Impala can start work on it right away.
In contrast with batch processing systems, Apache Impala leverages caching technology to catalog data and metadata, allowing it to be used for interactive analytic workloads and offering a step in the right direction toward real-time data-driven decision-making.
The Apache Impala Difference
As mentioned, Apache Impala is a distributed, massively parallel processing (MPP)-style database engine. It provides high-performance and low latency SQL queries and the ability to query high volumes of data in Apache Hadoop.
Key benefits of Apache Impala include:
Reduced complexity: Apache Impala offers a single system for big data processing and analytics. That means organizations can avoid complex and costly modeling and ETL for their analytics.
Positive user experience: Impala uses the same unified storage platform, metadata, SQL syntax, ODBC driver, and user interface (UI) as Apache Hive. This means that data scientists and analysts will be familiar with the SQL interface, simplifying the query process and making integrations easier.
Cost effective: Given the amount of data at hand—often well into the terabytes—cost effectiveness is a major business consideration. Apache Impala delivers SQL queries in a cluster environment, making scaling simple and convenient, while reducing overall costs.
Through these elements, users gain a unified and familiar platform to handle both real-time and batch-oriented queries. With all that said, what does something like Impala look like in practice? A recent bit of competition offers a glimpse into just how powerful the tool can be in the real world.
Exploring the Impact of Impala
Recently, Apache Impala’s capabilities were put to the test in a “Trillion Lines of Code” challenge, where the tool was evaluated for its file scanning and aggregation performance against a massive dataset: one trillion records containing temperature measurement data spread across 100,000 files, totaling around 2.4 TB.
Impala handled the challenge with ease—all it took was a simple SQL query. The challenge proved that using Apache Impala to run queries on vast datasets can result in critical savings in both cost as well as time.
High-Performance SQL with Cloudera and Apache Impala
At a time when data volumes are soaring and the ability to deliver real-time data insights is critical to success, it’s important for business leaders to choose the right tool for the job. Cloudera’s platform gives organizations a powerful means to manage and analyze data in real time and at rapidly increasing scale.
With support for Apache Impala, integration of a powerful open table format like Apache Iceberg, and the flexibility of an open data lakehouse, Cloudera ensures data can be managed easily, remain secure and compliant, and still be accessed and queried quickly.
To learn more about how your organization can take advantage of Apache Impala with Cloudera, here are a few next steps you can take:
Review the technical documentation of Cloudera and Apache Impala
Contact us to speak directly with a member of our sales team
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