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Difference Between Fail Fast and Fail Safe Iterator in Java

Knowledge Hut

Imagine you're working on a Java project , and you need to go through a bunch of data stored in lists, sets, or maps. That's where iterators come in – they help you walk through these collections. Iterators are handy tools for lists, sets, and maps, but modifying collections while iterating can lead to trouble.

Java 52
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Using Data To Illuminate The Intentionally Opaque Insurance Industry

Data Engineering Podcast

In this episode he shares his journey of data collection and analysis and the challenges of automating an intentionally manual industry. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles.

Insurance 162
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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

In addition to Python support, there is typically support for other programming languages, including JavaScript for web integration and Java for platform integration—though oftentimes with fewer features and less maturity. The Java developer imports it in Java for production deployment.

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Data News — Week 23.37

Christophe Blefari

— Hugo propose 7 hacks to optimise data warehouse cost. Scrape & analyse football data — Benoit nicely put in perspective how to use Kestra, Malloy and DuckDB to analyse data. Factory Patterns in Python — It remembers me Java design patterns classes at the engineering school.

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Building Data Flows In Apache NiFi With Kevin Doran and Andy LoPresto - Episode 39

Data Engineering Podcast

How do you manage versioning and backup of data flows, as well as promoting them between environments? One of the advertised features is tracking provenance for data flows that are managed by NiFi. How is that data collected and managed? How is that data collected and managed?

Building 100
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Apache Kafka Vs Apache Spark: Know the Differences

Knowledge Hut

Spark Streaming Kafka Streams 1 Data received from live input data streams is Divided into Micro-batched for processing. processes per data stream(real real-time) 2 A separate processing Cluster is required No separate processing cluster is required. 7 Kafka stores data in Topic i.e., in a buffer memory.

Kafka 98
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Future of Data Scientists: Career Outlook

Knowledge Hut

We are at the very cusp of the data collection explosion in such a case. There is currently a shortage of Data Science engineers. The world is data-driven, and the need for qualified data scientists will only increase in the future. Your watch history is a rich data bank for these companies.