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Impala JDBC connection with Kerberos

The idea was to use Java locally (in my case with InteliJ) to connect to Hive metastore through Impala. That was in order to read some data and then be able to use them by some other processes on later stages. Hadoop cluster that I was connecting to was Kerberised, which made the exercise more tricky. Here’s how I managed to establish such a connection.

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Spark AI Summit, Amsterdam 2019

Spark AI Summit Europe, which happened in October, was full of interesting stuff. It was mostly focused on features coming with Spark 3, but not only. Preview release of Spark 3 is already available and can be obtained here. There are a lot of cool features planned, especially when it comes to making Data Science easier on big data and with Spark in particular.

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AI in production

How to put AI projects in production – that’s a topic that since a while occupies heads of many data scientists and plays a key role on many international conferences. Unfortunately there is no one clear answer to that, as the variety of topics that we nowadays name as AI is huge.

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Data forecasting

Data forecasting is a process of estimating the future based on historical values. It is described by time series, which is simply a series of time dependent data points. We usually forecast different costs or sales over time. We can try to predict weather conditions or model stock changes. Basically look at any process that can be described as time dependent with certain time interval (hourly, daily, monthly…).

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Excel formatting with R

Many times there is a demand from end users to deliver results in a form of Excel files. The bigger and more complex the files grow, the more difficult it is to properly interpret them. This is when nice formatting can help you out.

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XGBoost

XGBoost or in long version Extreme Gradient Boosting got recently very popular, especially on Kaggle competitions. It proved to outperform many other algorithms on tasks such as classification and regression. I used it few times as well and that’s why I decided to take a closer look into XGBoost to see how it works.

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Apache Beam JDBC

With Apache Beam we can connect to different databases – HBase, Cassandra, MongoDB using specific Beam APIs. We also have a JdbcIO for JDBC connections. Here I show how to connect with MSSQL database using Beam and do some data importing and exporting in Kerberised environment.

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Apache Beam and HBase

HBase is a NoSql database, which allows you to store data in many different formats (like pictures, pdfs, textfiles and others) and gives the ability to do fast and efficient data lookups. HBase has two APIs to chose from – Java API and HBase Shell. We can also connect HBase with some different tools like Hive or Phoenix and use SQL. HBase also integrates with Apache Beam via HBaseIO transform.

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