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A Definitive Guide to Using BigQuery Efficiently

Towards Data Science

Like a dragon guarding its treasure, each byte stored and each query executed demands its share of gold coins. Join as we journey through the depths of cost optimization, where every byte is a precious coin. It is also possible to set a maximum for the bytes billed for your query. Photo by Konstantin Evdokimov on Unsplash ?

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Open-Sourcing AvroTensorDataset: A Performant TensorFlow Dataset For Processing Avro Data

LinkedIn Engineering

An Avro file is formatted with the following bytes: Figure 1: Avro file and data block byte layout The Avro file consists of four “magic” bytes, file metadata (including a schema, which all objects in this file must conform to), a 16-byte file-specific sync marker, and a sequence of data blocks separated by the file’s sync marker.

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Aligning Velox and Apache Arrow: Towards composable data management

Engineering at Meta

In the new representation , the first four bytes of the view object always contain the string size. Otherwise, a prefix of the string is stored in the next four bytes, followed by the buffer ID (StringViews can contain multiple data buffers) and the offset in that data buffer. first writing StringView at position 2, then 0 and 1).

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5 Big Data Challenges in 2024

Knowledge Hut

quintillion bytes (or 2.5 Two, it creates a commonality of data definitions, concepts, metadata and the like. With the rise in opportunities related to Big Data, challenges are also bound to increase. Below are the 5 major Big Data challenges that enterprises face in 2024: 1. exabytes) of information is being generated every day.

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Improving Efficiency Of Goku Time Series Database at Pinterest (Part?—?1)

Pinterest Engineering

The bucket in itself is actually nothing but a collection of SST files holding all the time series data and metadata for the corresponding bucket size. See the graph below, which shows the compaction read and write bytes on a cluster when it is bootstrapping for the first time. The bucket id is unix time divided by bucket size.

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Optimization Strategies for Iceberg Tables

Cloudera

A bloated metadata.json file could increase both read/write times because a large metadata file needs to be read/written every time. Regularly expiring snapshots is recommended to delete data files that are no longer needed, and to keep the size of table metadata small.

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Bending pause times to your will with Generational ZGC

Netflix Tech

Half of all services required for streaming video use our Hollow library for on-heap metadata. We paid particular attention to deallocation of direct byte buffers, but we haven’t seen any impact thus far. In the worst case we evaluated, non-generational ZGC caused 36% more CPU utilization than G1 for the same workload.

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