Author: Yuli Vasiliev

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Getting Started With Oracle R Technologies

By Yuli Vasiliev Oracle R technologies bring R, an open source statistical programming language and software environment, into an Oracle Database engine, allowing for better scalability, performance, and production deployment. Through this integration, data analysts can leverage the database computing environment for sophisticated data analysis, without having to move data to separate analytic servers. Before you can start testing Oracle...

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Programmatic Access to JSON in Oracle Database 12.2

By Yuli Vasiliev Starting with Oracle Database 12c Release 2, PL/SQL supports JSON, thus enabling programmatic access to JSON data within the database. In particular, SQL/JSON functions and conditions, such as json_object, json_query, and json_exists have been included to PL/SQL as built-in functions. Also, you can take advantage of the PL/SQL object types for JSON, such as JSON_ELEMENT_T, JSON_OBJECT_T, and...

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Oracle R Enterprise for Big Data Analysis

By Yuli Vasiliev In R, the issue of efficient data access becomes extremely important as data volumes to be processed increase, largely due to the fact that R loads an entire data set into memory at once. So, working in Big Data environments on large data sets requires a smart approach to make your work efficient. When using Oracle R...

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Building Machine Learning Models With Oracle R Enterprise 1.5

Building Machine Learning Models With Oracle R Enterprise 1.5 By Yuli Vasiliev Oracle R Enterprise 1.5 came with multiple enhancements and new features, including: new parallel algorithms, improved datastore and R script repository management, performance and capability enhancements. Whether you are a machine learning practitioner or a data analyst specializing in another field of data science, you may find these...

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Machine Learning with R within Oracle Database

Machine Learning with R within Oracle Database By Yuli Vasiliev Using R – an open source statistical programming language and environment – within Oracle Database for statistical computing and machine learning is enabled with Oracle R Enterprise, a component of Oracle Advanced Analytics database option. R integrated with the database leverages database compute engine, taking advantage of query optimization and...

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Setting Up an Environment for Machine Learning Tasks in Oracle Database

Setting Up an Environment for Machine Learning Tasks in Oracle Database By Yuli Vasiliev Machine Learning is a growing subfield of artificial intelligence, gaining immense popularity in recent years in both academia and the industry. Providing the ability to work with large volumes of data, machine learning algorithms are best suited for Big Data. This article discusses how you can...

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12.2’s JSON_OBJECT to Construct JSON in the Database

12.2’s JSON_OBJECT to Construct JSON in the Database Now with new release of Oracle Database (12.2), you can construct JSON data in the database from non-JSON data, using new SQL/JSON functions, such as: JSON_OBJECT, JSON_ARRAY, JSON_ARRAYAGG, and JSON_OBJECTAGG. This article takes a look at JSON_OBJECT, which you can use to generate JSON objects from name–value pairs. The examples in this...

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JSON Support Enhancements in Oracle Database 12c Release 2 (12.2)

JSON Support Enhancements in Oracle Database 12c Release 2 (12.2) By Yuli Vasiliev New release of Oracle Database (12.2) for the first time comes with Database JSON Developer’s Guide as a standalone book within Oracle Database Online Documentation Library. In the preceding release, JSON support in Oracle Database was covered in the JSON in Oracle Database chapter within XML DB...

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Using Invisible Columns in Oracle Database 12c

Using Invisible Columns in Oracle Database 12c By Yuli Vasiliev Oracle Database 12c Release 1 (12.1) introduced the Invisible Columns feature that provides a convenient way to change a table’s structure without having to edit existing applications using that table. Invisible columns will not be seen in the SELECT list nor will be considered for insertion in an INSERT statement […]

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Count, Distinct, and Nulls

Count, Distinct, and Nulls By Yuli Vasiliev Counting distinct values in a dataset that may include nulls is a fairly common operation when it comes to data analysis. Sometimes, you need to count only not-null distinct values, while next time you may need to include nulls in your count. The examples in this article cover both situations, querying the ext_json […]