What is fine grained and coarse-grained in Spark?

The coarse-grained operation means to apply operations on all the objects at once. Fine-grained operations mean to apply operations on a smaller set. We generally apply coarse-grained operation, as it works on entire cluster simultaneously. We can also create RDDs by its cache and divide it manually.

What is the difference between fine grained and coarse-grained?

Coarse-grained materials or systems have fewer, larger discrete components than fine-grained materials or systems. A coarse-grained description of a system regards large subcomponents. A fine-grained description regards smaller components of which the larger ones are composed.

What are the key differences between RDD and DSM?

The main difference between RDDs and DSM is that RDDs can only be created (“written”) through coarse- grained transformations, while DSM allows reads and writes to each memory location. 3 This restricts RDDs to applications that perform bulk writes, but allows for more efficient fault tolerance.

What is RDD explain about transformations and actions in the context of RDDs state and explain RDD operations in brief?

RDD Action. Transformations create RDDs from each other, but when we want to work with the actual dataset, at that point action is performed. When the action is triggered after the result, new RDD is not formed like transformation. Thus, Actions are Spark RDD operations that give non-RDD values.

What is coarse grained transformation?

Coarse-grained transformations are those that are applied over an entire dataset. On the other hand, a fine grained transaction is one applied on smaller set, may be a single row. But with fine grained transactions you have to save the updates which can be costlier but it is flexible than a coarse grained one.

Which type of processing can Apache Spark handle?

Apache Spark is an open source parallel processing framework for running large-scale data analytics applications across clustered computers. It can handle both batch and real-time analytics and data processing workloads.

Why is a fine grained structure harder than a coarse grained structure?

The movement of dislocations is hindered by grain boundaries. The more grain boundaries there are the more difficult it is for the dislocations to move and for the metal to change shape. A fine grained metal is therefore stronger than a coarse grained metal.

What is RDD lineage in Spark?

RDD lineage is nothing but the graph of all the parent RDDs of an RDD. We also call it an RDD operator graph or RDD dependency graph. To be very specific, it is an output of applying transformations to the spark. Then, it creates a logical execution plan.

What is the difference between a transformation and an action on an RDD?

Spark rdd functions are transformations and actions both. Transformation is function that changes rdd data and Action is a function that doesn’t change the data but gives an output.

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