Kategorie: flink
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Revisiting Big Data Formats: Apache Iceberg, Delta Lake and Apache Hudi
Novel Big Data formats, such as Apache Parquet, Apache ORC or Apache Avro have been years ago the game changer for processing massive amounts of data efficiently as I wrote in a previous blog post (aside of the Big Data platforms leveraging them). Nowadays we see the emergence of new Big Data formats, such as…
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Big Data Analytics on Excel files using Hadoop/Hive/Flink/Spark
Today we have released HadoopOffice v1.1.0 with major enhancements: Based on the latest Apache POI 3.17 Apache Hive: Query Excel files and write tables to Excel files using the Hive Serde Apache Flink support for Flink Table API and Flink DataSource/DataSink Signing and verification of signatures of Excel files Example to use the HadoopOffice library…
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HadoopOffice – A Vision for the coming Years
HadoopOffice is already since more than a year available (first commit: 16.10.2016). Currently it supports Excel formats based on the Apache POI parsers/writers. Meanwhile a lot of functionality has been added, such as: Support for .xlsx and .xls formats – reading and writing Encryption/Decryption Support Support for Hadoop mapred.* and mapreduce.* APIs Support for Spark…
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HadoopCryptoLedger library a vision for the coming Years
The first commit of the HadoopCryptoLedger has been on 26th March of 2016. Since then a lot of new functionality has been added, such as support for major Big Data platforms including Hive / Flink / Spark. Furthermore, besides Bitcoin, Altcoins based on Bitcoin (e.g. Namecoin, Litecoin or Bitcoin Cash) and Ethereum (including Altcoins) have…
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Mapred vs MapReduce – The API question of Hadoop and impact on the Ecosystem
I will describe in this blog post the difference between the mapred.* and mapreduce.* API in Hadoop with respect to the custom InputFormats and OutputFormats. Additionally I will write on the impact of having both APIs on the Hadoop Ecosystem and related Big Data platforms, such as Apache Flink, Apache Hive and Apache Spark. Finally,…
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Big Data Analytics on Bitcoin‘s first Altcoin: NameCoin
This blog post is about analyzing the Namecoin Blockchain using different Big Data technologies based on the HadoopCryptoLedger library. Currently, this library enables you to analyze the Bitcoin blockchain and Altcoins based on Bitcoin (incl. segregated witness), such as Namecoin, Litecoin, Zcash etc., on Big Data platforms, such as Hadoop, Hive, Flink and Spark. A…
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Leverage the Power of Apache Flink to analyze the Bitcoin Blockchain
The hadoopcryptoledger library has been enhanced with a datasource for Apache Flink. This means you can use the Big Data processing framework Apache Flink to analyze the Bitcoin Blockchain. It also includes an example that counts the total number of transactions in the Bitcoin blockchain. Of course given the power of Apache Flink you can think…