Is DataStax any good?

Is DataStax any good?

DataStax has an overall rating of 4 out of 5, based on over 395 reviews left anonymously by employees. 77% of employees would recommend working at DataStax to a friend and 72% have a positive outlook for the business. This rating has been stable over the past 12 months.

What is DSE Spark?

DSE includes Spark Jobserver, a REST interface for submitting and managing Spark jobs. Spark examples. DataStax Enterprise includes Spark example applications that demonstrate different Spark features.

Is Spark SQL useful?

Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data.

Is Spark SQL faster than SQL?

Extrapolating the average I/O rate across the duration of the tests (Big SQL is 3.2x faster than Spark SQL), then Spark SQL actually reads almost 12x more data than Big SQL, and writes 30x more data.

Is DataStax a good company to work for?

DataStax has a great product and platform. They provide catered lunches and a fully stocked snack kitchen. Great place to work if you can be self motivated. Lots of hard work but a great place to get started in your tech career.

What is spark Cassandra?

The fundamental idea is quite simple: Spark and Cassandra clusters are deployed to the same set of machines. Cassandra stores the data; Spark worker nodes are co-located with Cassandra and do the data processing. Spark is a batch-processing system, designed to deal with large amounts of data.

How does spark read data from Cassandra?

1. import org.apache.spark.sql.cassandra._ //Spark connector import com.datastax.spark.connector._ import com.datastax.spark.connector.cql.
2. val readBooksDF = sqlContext .read .format(“org.apache.spark.sql.cassandra”) .options(Map( “table” -> “books”, “keyspace” -> “books_ks”)) .load readBooksDF.explain readBooksDF.show.

How is Spark SQL different from MySQL?

MySQL can only use one CPU core per query, whereas Spark can use all cores on all cluster nodes. In my examples below, MySQL queries are executed inside Spark and run 5-10 times faster (on top of the same MySQL data). In addition, Spark can add “cluster” level parallelism.

What flavor of SQL does Spark use?

Cassandra has SQL-like CQL, Spark has SparkSQL, even JIRA has JQL which resembles basic SQL clauses like WHERE , IN , BETWEEN , etc.

Is Spark SQL different from MySQL?

Why is Spark SQL so fast?

Spark SQL relies on a sophisticated pipeline to optimize the jobs that it needs to execute, and it uses Catalyst, its optimizer, in all of the steps of this process. This optimization mechanism is one of the main reasons for Spark’s astronomical performance and its effectiveness.