In this article, we will discuss SQL Server 2019 new feature—Java Language Extensions. With the advent of SQL Server 2019, Microsoft always strives to expand its footprint on the capabilities of MLS (Machine Learning Services). It builds a deeper integration between the data-platform and data science under the data science umbrella. The Microsoft SQL Server 2019 MLS extensibility framework provides a solid base for allowing extensions in R, Python, and now Java.
In this article, we will discuss the following:
Understand Machine Language Service
Discuss JAVA SDK installation and configuration
Configure Java Language Extension API
Prepare the sample JAVA code using Eclipse IDE
Deploy JAR file in SQL Server
Run the JAVA program
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SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:
1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.
2. Every database seller needs an approach to separate its item from others.
Right now, contrasts are noted where fitting.
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When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.
When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,
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This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,
In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.
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Since the release of SQL Server 2017 for Linux, Microsoft has pretty much changed the entire game. It enabled a whole new world of possibilities for their famous relational database, offering what was only available in the Windows space until then.
I know that a purist DBA would tell me right away that the out of the box SQL Server 2019 Linux version has several differences, in terms of features, in regards to its Windows counterpart, such as:
However, I got curious enough to think “what if they can be compared, at least to some extent, against things that both can do?” So, I pulled the trigger on a couple of VMs, prepared some simple tests, and collected data to present to you. Let’s see how things turn out!
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OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE). It contains the virtual machine, the Java Class Library, and the Java compiler. The difference between the Oracle OpenJDK and Oracle JDK is that OpenJDK is a source code reference point for the open-source model. Simultaneously, the Oracle JDK is a continuation or advanced model of the OpenJDK, which is not open source and requires a license to use.
In this article, we will be installing OpenJDK on Centos 8.
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