Cloudera

AUGUST 4, 2022

Z-order is an ordering for multi-dimensional data, e.g. rows in a database table. Once data is in Z-order it is possible to efficiently search against more columns. This article reveals how Z-ordering works and how one can use it with Apache Impala. Lexical ordering. More on that later.

IoT 103

IoT Measurement Statistics Cost-Benefit 103

AWS Big Data

NOVEMBER 17, 2023

By using these statistics, CBO improves query run plans and boosts the performance of queries run in Athena. TPC-DS benchmarks These benchmarks demonstrate the power of the cost-based optimizer—queries run up to 2x times faster with CBO enabled compared to running the same TPC-DS queries without CBO.

Optimization 110

Optimization Statistics Metadata Data Lake 110

AWS Big Data

JUNE 9, 2023

This data is then projected into analytics services such as data warehouses, search systems, stream processors, query editors, notebooks, and machine learning (ML) models through direct access, real-time, and batch workflows.

Data Lake 111

Data Lake Metadata Optimization Statistics 111

Cloudera

NOVEMBER 13, 2020

What if our queries are very selective? It turns out that Apache Impala scales down with data just as well as it scales up. We’ll discuss the architecture and features of Impala that enable low latencies on small queries and share some practical tips on how to understand the performance of your queries.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143

Cloudera

MAY 18, 2021

Speed matters in financial markets. Whether the goal is to maximize alpha or minimize exposure, financial technologists invest heavily in having the most up-to-date insights on the state of the market and where it is going. In case you missed it, part I starts with a simple case of calculating streaming VWAP. WITH (.

Risk 94

Risk Marketing Risk Management Data-driven 94

Cloudera

MARCH 23, 2022

Through Cloudera’s contributions, we have extended support for Hive and Impala, delivering on the vision of a data architecture for multi-function analytics from large scale data engineering (DE) workloads and stream processing (DF) to fast BI and querying (within DW) and machine learning (ML). . What is Apache Iceberg?

Metadata 89

Metadata Data Architecture Machine Learning Cost-Benefit 89

Occam's Razor

JANUARY 10, 2011

Regardless of where you are I hope these six lessons help speed up your journey, avoid the mistakes I made and achieve success sooner: #1: An obsession with tools & implementations will kill you. Your real impact comes not from providing pretty pie charts from a complex Discover2 query. Get over it. Stop switching tools!

Analytics 120

Analytics Measurement Data-driven Optimization 120