Storage articles

Looking for something else? Check the categories of Storage:

Apache Avro Apache Cassandra Apache Hudi Apache Iceberg Apache Parquet Apache ZooKeeper Delta Lake Elasticsearch Embedded databases HDFS MySQL PostgreSQL Time series

If not, below you can find all articles belonging to Storage.

Table file formats - isolation levels: Delta Lake

If Delta Lake implemented the commits only, I could stop exploring this transactional part after the previous article. But as for RDBMS, Delta Lake implements other ACID-related concepts. One of these are isolation levels.

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Table file formats - commits: Delta Lake

One of the great features of modern table file formats is the ability to handle write conflicts. It wouldn't be possible without commits that are the topic of this new blog post.

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Table file formats - Schema evolution: Delta Lake

Data lakes have made the data-on-read schema popular. Things seem to change with the new open table file formats, like Delta Lake or Apache Iceberg. Why? Let's try to understand that by analyzing their schema evolution parts.

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Table file formats - Z-Order compaction: Apache Iceberg

Last time you discovered the Z-Order compaction in Delta Lake. But guess what? Apache Iceberg also has this feature!

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Table file formats - Z-Order compaction: Delta Lake

In my recent exploration of the compaction, aka OPTIMIZE command, in Delta Lake, I found this famous Z-Ordering mode. It was one of the most outstanding features when I first heard about Delta Lake. You can't even imagine how impatient I was to see what it is doing under-the-hood. Fortunately, this time has come!

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Simplified Delta Lake operations with Mack

I like writing code and each time there is a data processing job to write with some business logic I'm very happy. However, with time I've learned to appreciate the Open Source contributions enhancing my daily work. Mack library, the topic of this blog post, is one of those projects discovered recently.

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Table file formats - compaction: Apache Iceberg

Compaction is also a feature present in Apache Iceberg. However, it works a little bit differently than for Delta Lake presented last time. Why? Let's see in this new blog post!

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Table file formats - Compaction: Delta Lake

The small files is a well known problem in data systems. Fortunately, modern table file formats have built-in features to address it. In the next series we'll see how.

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Table file formats - Change Data Capture: Delta Lake

It's time to start the 4th part of the Table file formats series. This time the topic will be Change Data Capture, so how to stream all changes made on the table. As for the 3rd part, I'm going to start with Delta Lake.

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Table file formats - reading path: Apache Hudi

After Delta Lake and Apache Iceberg it's time to see the reading part of Apache Hudi. Despite an apparent similarity with the aforementioned table formats, Apache Hudi has an interesting reading specificity related to the different table types.

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Table file formats - reading path: Apache Iceberg

Last week you could read about data reading in Delta Lake. Today it's time to cover this part in Apache Iceberg!

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Table formats - reading: Delta Lake

In the previous blog post about Delta Lake you discovered the logic for the writing part. Meantime Delta Lake 2 was released and it's for this brand new version that I'm going to share with you some findings related to the data reading.

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ACID file formats - writing: Delta Lake

It's time for the last data generation part of the ACID file formats series. This time we'll see how Delta Lake writes new files.

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ACID file formats - writing: Apache Iceberg

Last time you discovered data writing in Apache Hudi. Today it's time to see the 2nd file format from my list, Apache Iceberg.

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ACID file formats - writing: Apache Hudi

It's only when I was preparing the 2nd blog post of the series that I realized how bad my initial plan was. The article you're currently reading had been initially planned as the 6th of the series. But indeed, how could we understand more advanced features without discovering the writing path first?

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Data+AI Summit follow-up post: Why RocksDB rocks?

One reason why you can think about using a custom state store is the performance issues, or rather unpredictable execution time due to the shared memory between the default state store implementation and Apache Spark task execution. To overcome that, you can try to switch the state store implementation to an off-heap-based one, like RocksDB.

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Data+AI follow-up: Introduction to MapDB

Since there are already 2 Open Source implementations for RocksDB state store, I decided to use another backend to illustrate how to customize the state store in Structured Streaming. Initially, I wanted to try with Badger which is the store behind DGraph database but didn't find any Java-facing interface and dealing with the Java Native Interface or any other wrapper, was not an option. Fortunately, I ended up by finding MapDB, a Kotlin-based - hence a Java-facing interface - embedded database.

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ALTER DEFAULT PRIVILEGES in PostgreSQL

At first glance, managing users access in PostgreSQL is easy, you simply execute a CREATE USER, give him some grants, assign a role, and often that's all. However, after some time "permission denied" errors can appear as new objects are created and not owned by the user. To mitigate the maintenance burden for that case, PostgreSQL proposes ALTER DEFAULT privileges operator.

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Resources and metrics in Gnocchi

Data processing in Gnocchi is strongly related to the index information. One of such valuable assets are metrics and resources, covered just below.

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Cleaning old measures in Gnocchi

The specificity of Gnocchi is the precomputation of the measures. It doesn't allow ad-hoc queries but in the other side provides pretty good reading performance. However, as new time series points are coming, the old ones aren't kept with them.

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