![]() "What if a design could bring the ML to the data, eliminating the need for ETL processes and enabling faster and close to real-time ML usage? That’s what the MySQL HeatWave team has achieved." By bringing ML to the data with HeatWave ML in a cost-efficient, automated way, HeatWave accelerates ML adoption." " HeatWave does machine learning the right way. For developers, HeatWave ML is a time saver, accelerating their app development velocity, increasing model accuracy." The result is faster, and cheaper ML compared to other platforms. But that’s just the start, HeatWave ML fully automates model training, inference, and explanation without data or models leaving the database. Once again, with this innovation, Oracle eliminates the need for multiple service offerings and tools for users to integrate machine learning into their applications-plus costly and time-consuming ETL. After introducing MySQL HeatWave, a single unified platform for both OLTP and OLAP, and automating management processes with Autopilot, Oracle now adds machine learning to MySQL HeatWave. "Oracle continues to show the industry what’s possible in MySQL. "MySQL HeatWave is priced less than all comparable cloud database services, so talk about value for your money-HeatWave is off the charts…the addition of MySQL Autopilot to MySQL HeatWave has made an already attractive offering even more attractive." Leading Cloud Analyst Holger Mueller of Constellation Research published his take on MySQL Autopilot and concluded that "Customers using MySQL or MySQL-compatible databases should evaluate MySQL Database Service with HeatWave now." With machine learning-based automation in Autopilot and scaling in memory, nodes, and storage, Oracle sets developers free to develop next generation applications running on the much faster and cheaper MySQL HeatWave compared to any platform they may try.” Now Oracle brings out new innovations which are set to likely disrupt the market, significantly lifting the expectations for what open source cloud databases should be. Oracle previously provided a single unified platform for both OLTP and OLAP, eliminating the need for multiple databases and tools to ETL across databases. “The evolution of MySQL continues as Oracle accelerates developer velocity. Holger Mueller, VP and Principal Analyst, Constellation Research The query is as follows − mysql> select *from INDemo where Id IN(112,116,100) Īs you can see in the above output, we are getting the same result."The resulting architecture is elegant, allowing the prioritization of queries to enable the Holy Grail of insight to action for enterprise decision-making." Now, let us check it with the help of IN(). The query is as follows − mysql> select *from INDemo where Id regexp '112|116|100' You can apply the above syntax which I have discussed in the beginning. The query is as follows − mysql> select *from INDemo ![]() ![]() Now we can display all the records with the help of SELECT statement. Mysql> insert into INDemo values(120,'Sam') Mysql> insert into INDemo values(116,'Johnson') Mysql> insert into INDemo values(112,'Smith') Mysql> insert into INDemo values(108,'David') Mysql> insert into INDemo values(104,'Carol') The query is as follows − mysql> insert into INDemo values(100,'John') Let us first create a table − mysql> create table INDemo To understand the above logic, you need to create a table. The syntax is as follows − select *from yourTableName where yourColumName regexp ‘value1|value2|value3……|valueN’ ![]() You can implement MySQL Like IN() with the help of Regular Expression (regexp) as well.
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