Python
Python is a dynamic, interpretive and scripted programming language. It was developed at the beginning of the 1990s by Guido van Rossum. Today, this language is being developed as an open-source project by many developers worldwide, led by Guido through the Python Software Foundation (PSF). The goal of the language is to develop an easy-to-learn programming language producing an intuitive and readable code while remaining as powerful as other established programming languages.
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Categories: Data Engineering, Data Science, Learning | Tags: Spark, Deep Learning, Databricks, Delta Lake, Machine Learning, MLflow, Notebook, Python, Scikit-learn
Introduction to Databricks Community Edition and MLflow Every day the number of tools helping Data Scientists to build models faster increases. Consequently, the need to manage the results and the…
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Importing data to Databricks: external tables and Delta Lake
Categories: Data Engineering, Data Science, Learning | Tags: Parquet, AWS, Amazon S3, Azure Data Lake Storage (ADLS), Databricks, Delta Lake, Python
During a Machine Learning project we need to keep track of the training data we are using. This is important for audit purposes and for assessing the performance of the models, developed at a later…
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Introducing Apache Airflow on AWS
Categories: Big Data, Cloud Computing, Containers Orchestration | Tags: Airflow, Oozie, Spark, PySpark, Docker, Learning and tutorial, AWS, Python
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May 5, 2020
Optimisation of Spark applications in Hadoop YARN
Categories: Data Engineering, Learning | Tags: Spark, Tuning, Hadoop, Python
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Mar 30, 2020
MLflow tutorial: an open source Machine Learning (ML) platform
Categories: Data Engineering, Data Science, Learning | Tags: Deep Learning, AWS, Databricks, Deployment, Machine Learning, Azure, MLflow, MLOps, Python, Scikit-learn
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Mar 23, 2020
Introduction to Ludwig and how to deploy a Deep Learning model via Flask
Categories: Data Science, Tech Radar | Tags: Deep Learning, Learning and tutorial, Ludwig Deep Learning Toolbox, Machine Learning, Python
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Categories: Data Engineering, Data Science | Tags: Flink, Kafka, Spark, DevOps, Hadoop, HBase, Kubernetes, Python
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By David WORMS
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Categories: Big Data, Data Engineering, Data Science, DevOps & SRE | Tags: DevOps, Operation, Schema, AI, Cloud, Machine Learning, MLOps, On-premises
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TensorFlow installation on Docker
Categories: Containers Orchestration, Data Science, Learning | Tags: CPU, Deep Learning, Docker, Jupyter, Linux, AI, TensorFlow
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Categories: Big Data, Business Intelligence, DataWorks Summit 2019 | Tags: Druid, Hive, Kafka, JDBC, LLAP, Release and features, Hadoop
Apache Hive 3 brings a bunch of new and nice features to the data warehouse. Unfortunately, like many major FOSS releases, it comes with a few bugs and not much documentation. It is available since…
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Jul 16, 2019
Spark Streaming part 3: DevOps, tools and tests for Spark applications
Categories: Big Data, Data Engineering, DevOps & SRE | Tags: Spark, Apache Spark Streaming, DevOps, Learning and tutorial
Whenever services are unavailable, businesses experience large financial losses. Spark Streaming applications can break, like any other software application. A streaming application operates on data…
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Spark Streaming part 2: run Spark Structured Streaming pipelines in Hadoop
Categories: Data Engineering, Learning | Tags: Spark, Apache Spark Streaming, Streaming, Python
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 Data…
May 28, 2019
First Class Functions in Python
Categories: Hack, Learning | Tags: Programming, Python
I recently watched a talk by Dave Cheney about first class functions in Go. Python supports first class functions too, so can we use them in the same ways? Absolutely. I have been using Python for a…
Apr 15, 2019
Publish Spark SQL DataFrame and RDD with Spark Thrift Server
Categories: Data Engineering | Tags: Hive, Spark, Thrift, JDBC, Hadoop, SQL
The distributed and in-memory nature of the Spark engine makes it an excellent candidate to expose data to clients which expect low latencies. Dashboards, notebooks, BI studios, KPIs-based reports…
Mar 25, 2019
Applying Deep Reinforcement Learning to Poker
Categories: Data Science | Tags: Algorithm, Deep Learning, Gaming, Q-learning, Machine Learning, Neural Network, Python
We will cover the subject of Deep Reinforcement Learning, more specifically the Deep Q Learning algorithm introduced by DeepMind, and then we’ll apply a version of this algorithm to the game of Poker…
Jan 9, 2019
Monitoring a production Hadoop cluster with Kubernetes
Categories: DevOps & SRE | Tags: Thrift, Docker, Elasticsearch, Graphana, Node.js, Prometheus, Shinken, Hadoop, Knox, Cluster, Kubernetes, Node, Python
Monitoring a production grade Hadoop cluster is a real challenge and needs to be constantly evolving. The software we use today is based on Nagios. Very efficient when it comes to the simplest…
Dec 21, 2018
CodaLab – Data Science competitions
Categories: Data Science, Adaltas Summit 2018, Learning | Tags: Database, Infrastructure, MySQL, Node.js, Machine Learning, Python
CodaLab Competition is a platform for code execution in the field of Data Science. It is a web interface on which a user can submit code or results and compare themselves to others. Let’s see how it…
Dec 17, 2018
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Categories: Infrastructure | Tags: Ansible, Ambari, Automation, HDP, REST, Cluster, Vagrant
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Categories: Data Science, Learning | Tags: Deep Learning, Micro Services, Node.js, Open API, Kubernetes, Neural Network
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TensorFlow on Spark 2.3: The Best of Both Worlds
Categories: Data Science, DataWorks Summit 2018 | Tags: Mesos, Spark, YARN, C++, CPU, GPU, JavaScript, Tuning, Keras, Kubernetes, Machine Learning, Python, TensorFlow
The integration of TensorFlow With Spark has a lot of potential and creates new opportunities. This article is based on a conference seen at the DataWorks Summit 2018 in Berlin. It was about the new…
By Yliess HATI
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Apache Beam: a unified programming model for data processing pipelines
Categories: Data Engineering, DataWorks Summit 2018 | Tags: Apex, Beam, Flink, Spark, Pipeline
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Present and future of Hadoop workflow scheduling: Oozie 5.x
Categories: Big Data, DataWorks Summit 2018 | Tags: Hive, Oozie, Sqoop, HDP, REST, Hadoop, CDH
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May 23, 2018
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Categories: Data Engineering, DataWorks Summit 2018 | Tags: Arrow, ORC, Spark, PySpark, Docker, Streaming, Tuning, Spark MLlib, Kubernetes, pandas
Let’s 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: Apache…
May 23, 2018
Execute Python in an Oozie workflow
Categories: Data Engineering | Tags: Oozie, Elasticsearch, REST, Python
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Categories: Containers Orchestration, DevOps & SRE, Open Source Summit Europe 2017 | Tags: Ansible, Docker, Docker Compose, pip, Shell, YAML
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Categories: Big Data, Events | Tags: EC2, Cloudera, Altus, CDSW, SDX, PaaS, CDH, Azure
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Categories: Big Data, DevOps & SRE, Infrastructure | Tags: Alert, Ambari, HDP, Metrics, Monitoring, REST
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Get in control of your workflows with Apache Airflow
Categories: Big Data, Tech Radar | Tags: Airflow, DevOps, Cloud, Python
Below is a compilation of my notes taken during the presentation of Apache Airflow by Christian Trebing from BlueYonder. Introduction Use case: how to handle data coming in regularly from customers…
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Categories: Data Engineering | Tags: Flume, HDFS, Hive, Oozie, Pig, SQL
I am going to show how to split a CSV file stored inside HDFS as multiple Hive tables based on the content of each record. The context is simple. We are using Flume to collect logs from all over our…
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Categories: Tech Radar | Tags: HTML, Java, Node.js
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By David WORMS
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Node.js is now integrated to the Microsoft Azure platform
Categories: Cloud Computing, Tech Radar | Tags: Linux, Node.js, Cloud, Azure
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By David WORMS
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Node.js, JavaScript on the server side
Categories: Front End, Node.js | Tags: HTTP, JavaScript, Node.js, Server
Waiting for the Next Big Language (NBL for Next Big Language), this is now 3 years or more since I predict to my customers a bright future for JavaScript as a programming language for server…
By David WORMS
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