Streaming
Streaming is the continuous transmission of data over a network. Data streams are a continuous flow of data records, the end of which can usually not be foreseen in advance. The data records are processed continuously as soon as a new data record is received. The amount of data records per unit of time (data rate) can vary and possibly become so large that the limited resources are insufficient for further processing and the recipient has to react accordingly (e.g. discarding data records). In contrast to other data sources, data streams can only be processed continuously record by record - in particular, in contrast to data structures with random access (such as arrays), only sequential access to the individual data records is usually possible.
Data streams are often used for interprocess communication (communication between processes on a computer) and for the transmission of data over networks, especially IoT and for streaming media. They can be used in many ways within the framework of the Pipes and Filters programming paradigm. Pipe is a common functionnality of Unix shells. Examples of data streams are weather data, system metrics, factory devices information, as well as audio and video streams (streaming media).
- Related tags
- Internet of Things (IOT)
Related articles
Operating Kafka in Kubernetes with Strimzi
Categories: Big Data, Containers Orchestration, Infrastructure | Tags: Kafka, Big Data, Kubernetes, Open source, Streaming
Kubernetes is not the first platform that comes to mind to run Apache Kafka clusters. Indeed, Kafkaās strong dependency on storage might be a pain point regarding Kubernetesā way of doing things whenā¦
Mar 7, 2023
Databricks logs collection with Azure Monitor at a Workspace Scale
Categories: Cloud Computing, Data Engineering, Adaltas Summit 2021 | Tags: Metrics, Monitoring, Spark, Azure, Databricks, Log4j
Databricks is an optimized data analytics platform based on Apache Spark. Monitoring Databricks plateform is crucial to ensure data quality, job performance, and security issues by limiting access toā¦
By Claire PLAYE
May 10, 2022
Internship in Data Engineering
Categories: Front End, Learning | Tags: Metrics, Monitoring, Hive, Kafka, Delta Lake, Elasticsearch, IaC, Internship, Kubernetes, Streaming
Job Description Data is a valuable business asset. Some call it the new oil. The data engineer collects, transform and refine āāraw data into information that can be used by business analysts and dataā¦
By David WORMS
Oct 25, 2021
Spark Streaming part 4: clustering with Spark MLlib
Categories: Data Engineering, Data Science, Learning | Tags: Spark, Apache Spark Streaming, Big Data, Clustering, Machine Learning, Scala, Streaming
Spark MLlib is an Apacheās Spark library offering scalable implementations of various supervised and unsupervised Machine Learning algorithms. Thus, Spark framework can serve as a platform forā¦
Jun 27, 2019
Spark Streaming part 3: DevOps, tools and tests for Spark applications
Categories: Big Data, Data Engineering, DevOps & SRE | Tags: DevOps, Learning and tutorial, Spark, Apache Spark Streaming
Whenever services are unavailable, businesses experience large financial losses. Spark Streaming applications can break, like any other software application. A streaming application operates on dataā¦
May 31, 2019
Spark Streaming part 2: run Spark Structured Streaming pipelines in Hadoop
Categories: Data Engineering, Learning | Tags: Spark, Apache Spark Streaming, Python, Streaming
Spark can process streaming data on a multi-node Hadoop cluster relying on HDFS for the storage and YARN for the scheduling of jobs. Thus, Spark Structured Streaming integrates well with Big Dataā¦
May 28, 2019
Spark Streaming part 1: build data pipelines with Spark Structured Streaming
Categories: Data Engineering, Learning | Tags: Kafka, Spark, Apache Spark Streaming, Big Data, Streaming
Spark Structured Streaming is a new engine introduced with Apache Spark 2 used for processing streaming data. It is built on top of the existing Spark SQL engine and the Spark DataFrame. Theā¦
Apr 18, 2019
Apache Flink: past, present and future
Categories: Data Engineering | Tags: Pipeline, Flink, Kubernetes, Machine Learning, SQL, Streaming
Apache Flink is a little gem which deserves a lot more attention. Letās dive into Flinkās past, its current state and the future it is heading to by following the keynotes and presentations at Flinkā¦
Nov 5, 2018
Apache Beam: a unified programming model for data processing pipelines
Categories: Data Engineering, DataWorks Summit 2018 | Tags: Apex, Beam, Pipeline, Flink, Spark
In this article, we will review the concepts, the history and the future of Apache Beam, that may well become the new standard for data processing pipelines definition. At Dataworks Summit 2018 inā¦
May 24, 2018
What's new in Apache Spark 2.3?
Categories: Data Engineering, DataWorks Summit 2018 | Tags: Arrow, PySpark, Tuning, ORC, Spark, Spark MLlib, Data Science, Docker, Kubernetes, pandas, Streaming
Letās dive into the new features offered by the 2.3 distribution of Apache Spark. This article is a composition of the following talks seen at the DataWorks Summit 2018 and additional research: Apacheā¦
May 23, 2018
Node CSV version 0.2.1
Categories: Node.js | Tags: CoffeeScript, CSV, Release and features, Streaming
After the announcement of the version 0.2.0 of the Node.js CSV parser at the beginning of october, we are releasing today a new version 0.2.1. This is mostly a bug fix release with enhancedā¦
By David WORMS
Jul 24, 2012
Node CSV version 0.1 and future developments
Categories: Node.js | Tags: CoffeeScript, CSV, Markdown, Release and features, Streaming
The Node CSV parser has just reach version 0.1 which close the 0.0.x releases. Started almost 2 years ago, the project has received a tremendous amount of participation in the form of bug reportsā¦
By David WORMS
Jul 21, 2012
Node CSV version 0.2 with streaming API
Categories: Node.js | Tags: Data Engineering, CSV, Markdown, Node.js, Streaming
The Node CSV parser in its version 0.2 has just been released. This version is a major enhancement as it aligned the parser with the best Node.js practice in respect of streams. The CSV parser behaveā¦
By David WORMS
Jul 2, 2012