why
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why [2016/03/01 09:59] dmtolpeko [4. Readability and Maintainability] |
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| Compared with Python, Java or Linux shell scripting, HPL/SQL enables Hadoop for a wider audience of BI analysts and developers. | Compared with Python, Java or Linux shell scripting, HPL/SQL enables Hadoop for a wider audience of BI analysts and developers. | ||
| + | ===== 4. ETL Framework ===== | ||
| + | HPL/SQL offers functions and statements to make your typical ETL development much more productive. | ||
| - | + | ===== 5. Readability and Maintainability ===== | |
| - | ===== 4. Readability and Maintainability ===== | + | |
| HPL/SQL is much more concise, readbale and maintainable for BI/SQL developers especially compared with Bash scripts, Java, Python or Scala programs. | HPL/SQL is much more concise, readbale and maintainable for BI/SQL developers especially compared with Bash scripts, Java, Python or Scala programs. | ||
| - | ===== 5. Integration and Polyglot Persistence ===== | + | ===== 6. Integration and Polyglot Persistence ===== |
| Hadoop extends a traditional data warehouse built using a RDBMS product. This means you have to integrate multiple systems including Hadoop, RDBMS, NoSQL and others. | Hadoop extends a traditional data warehouse built using a RDBMS product. This means you have to integrate multiple systems including Hadoop, RDBMS, NoSQL and others. | ||
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| HPL/SQL allows you to work with multiple systems in a single script, so you can take the best of all worlds for different types of workloads and easily integrate them. | HPL/SQL allows you to work with multiple systems in a single script, so you can take the best of all worlds for different types of workloads and easily integrate them. | ||
| - | ===== 6. Compatibility and Migration ===== | + | ===== 7. Compatibility and Migration ===== |
| HPL/SQL tries to support syntaxes of all widely used procedural languages as much as possible. You do not need to learn a new procedural language from scratch. This facilitates the development of new code as well as migration of the existing code base to Hadoop. | HPL/SQL tries to support syntaxes of all widely used procedural languages as much as possible. You do not need to learn a new procedural language from scratch. This facilitates the development of new code as well as migration of the existing code base to Hadoop. | ||
| - | ===== 7. Hadoop Quick Start ===== | + | ===== 8. Hadoop Quick Start ===== |
| HPL/SQL offers the fastest way to start working with Hadoop. Later you can re-design and implement advanced data processing workflows using Spark, Tez, Storm, Flink and other frameworks, but right now you can use your current skills and existing code to run your business logic on Hadoop. | HPL/SQL offers the fastest way to start working with Hadoop. Later you can re-design and implement advanced data processing workflows using Spark, Tez, Storm, Flink and other frameworks, but right now you can use your current skills and existing code to run your business logic on Hadoop. | ||
| ~~NOTOC~~ | ~~NOTOC~~ | ||
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