Apache Spark Standalone vs Apache Hadoop YARN
Developers should use Apache Spark Standalone when they need a quick and easy way to set up a Spark cluster without the complexity of external cluster managers, such as for prototyping, small-scale production workloads, or educational purposes meets developers should learn and use yarn when building or operating large-scale, distributed data processing systems on hadoop clusters, as it provides centralized resource management for improved cluster utilization and flexibility. Here's our take.
Apache Spark Standalone
Developers should use Apache Spark Standalone when they need a quick and easy way to set up a Spark cluster without the complexity of external cluster managers, such as for prototyping, small-scale production workloads, or educational purposes
Apache Spark Standalone
Nice PickDevelopers should use Apache Spark Standalone when they need a quick and easy way to set up a Spark cluster without the complexity of external cluster managers, such as for prototyping, small-scale production workloads, or educational purposes
Pros
- +It is particularly useful in scenarios where you want to avoid dependencies on Hadoop ecosystems or when deploying Spark on-premises or in cloud environments with simple infrastructure
- +Related to: apache-spark, distributed-computing
Cons
- -Specific tradeoffs depend on your use case
Apache Hadoop YARN
Developers should learn and use YARN when building or operating large-scale, distributed data processing systems on Hadoop clusters, as it provides centralized resource management for improved cluster utilization and flexibility
Pros
- +It is essential for running diverse workloads (e
- +Related to: apache-hadoop, apache-spark
Cons
- -Specific tradeoffs depend on your use case
The Verdict
Use Apache Spark Standalone if: You want it is particularly useful in scenarios where you want to avoid dependencies on hadoop ecosystems or when deploying spark on-premises or in cloud environments with simple infrastructure and can live with specific tradeoffs depend on your use case.
Use Apache Hadoop YARN if: You prioritize it is essential for running diverse workloads (e over what Apache Spark Standalone offers.
Developers should use Apache Spark Standalone when they need a quick and easy way to set up a Spark cluster without the complexity of external cluster managers, such as for prototyping, small-scale production workloads, or educational purposes
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