Apache Arrow defines a language-independent columnar memory format for in-memory analytics. It contains a set of technologies that enable big data systems to process and move data fast. Before going through the performance improvements provided by Apache Arrow, let’s quickly go through the usual process happening in PySpark and Pandas…

Introduction Ever since the introduction of Hadoop, computing power and storage are seen as two different entities (unlike OLTP databases where computing and storage are tightly coupled). For example, Map Reduce, Spark, Flink, Storm are frameworks to process big data in distributed environment, whereas HDFS, Cloud storage (S3, Azure Blob, Google…

Windows plays a major role and also defined as a core part in processing infinite streams. Windows split the incoming stream into buckets of finite size, over which required transformations can be applied. Though there are many components in windows that includes trigger, evictor, allowedLateness, sideOutputLateData…etc, this post focusses on…

Let’s begin with some issues faced in data engineering projects, followed by usage of Delta Lake clones and let’s take a final step by resolving issues. What’s clone in Delta Lake? It’s just a replica of a source table at a given point in time. In other database terminology, we…

Consider a common scenario of data engineering pipeline where raw data needs to be cleansed, transformed or aggregated before writing to a target system. For this case, usually we create 3-4 tables to store raw data, cleansed data, transformed data and aggregated data respectively. In order to implement, this needs…

So, what’s Bloom filter? Bloom filter index is a space-efficient probabilistic data structure that is used to test whether an element is a member of set. It skips the values of chosen columns, particularly for fields containing arbitrary text. A Bloom filter can tell you if a key is in a set and with…

Introduction: Before we start deep diving on AutoLoader, let us focus on the existing data engineering issues in ingestion process that fits into one of the below categories: High Latency due to batch processing: Though data is landing at regular intervals for every few minutes, most of the cases a batch…

Though big data platform has introduced lot of new frameworks like Spark, Druid, Delta Lake, Hudi, Governed tables, Snowflake..etc and covered a huge distance, explored various issues after introduction of Hadoop, but still there are lot of data stores of project set up using Hadoop. So, even nowadays there are…

Apologies, if the heading is misleading, because we all know that Databricks and AWS are competing on Data Engineering and Machine Learning space. So, you might be wondering how a Databricks product can get installed on AWS EMR. …