Category Archives: Scala

Knoldus Blogs In our previous blogs: Structured Streaming: What is it? &Structured Streaming: How it works? We got to know 2 major points about Structured Streaming – It is a fast, scalable, fault-tolerant, end-to-end, exactly-once stream processing API that helps users … Continue reading →

Knoldus Blogs With the advent of streaming frameworks like Spark Streaming, Flink, Storm etc. developers stopped worrying about issues related to a streaming application, like – Fault Tolerance, i.e., zero data loss, Real-time processing of data, etc. and started focussing only on … Continue reading →

Knoldus Blogs Hello everyone, Knoldus organized a session on 05th January 2018. The topic was “Understanding Spark Structured Streaming”. Many people attended and enjoyed the session. In this blog post, I am going to share the slides & video of the session. Slides: … Continue reading →

Knoldus Blogs How to deploy a Lagom Service without ConductR? This question has been asked and answered by many, on different forums. For example, take a look at this question on StackOverflow – Lagom without ConductR? Here the user is trying to … Continue reading →

Knoldus Blogs “Structured Streaming”, nowadays we are hearing this term in Apache Spark ecosystem quite a lot, as it is being preached as next big thing in scalable big data world. Although, we all know that Structured Streaming means a … Continue reading →

Knoldus Blogs Apache Spark, whenever we hear these two words, the first thing that comes to our mind is RDDs, i.e., Resilient Distributed Datasets. Now, it has been more than 5 years since Apache Spark came into existence and after its arrival … Continue reading →

Knoldus Blogs Data loading, in Spark SQL, means loading data in memory/cache of Spark worker nodes. For which we use to write following code: val connectionProperties = new Properties() connectionProperties.put(“user”, “username”) connectionProperties.put(“password”, “password”) val jdbcDF = spark.read .jdbc(“jdbc:postgresql:dbserver”, “schema.table”, connectionProperties) In … Continue reading →