Tag

Table Format

0 views collected around this technical thread.

DataFunSummit
DataFunSummit
Mar 10, 2023 · Big Data

Interview on Data Lake and Lakehouse: Current Applications, Challenges, and Evolution

This interview with NetEase’s data‑lake technology manager explores the distinction between data lakes and lakehouses, the evolution of table‑format technologies such as Iceberg, Hudi and Delta Lake, their maturity across key capabilities, and the practical adoption challenges faced by enterprises.

Big DataDelta LakeHudi
0 likes · 14 min read
Interview on Data Lake and Lakehouse: Current Applications, Challenges, and Evolution
DataFunTalk
DataFunTalk
Feb 20, 2023 · Big Data

Understanding Data Lakes and Their Application at iQIYI: Concepts, Scenarios, and Iceberg Implementation

This article explains the definition of data lakes (public‑cloud and non‑public‑cloud), outlines their key characteristics, presents three typical business scenarios—real‑time event analysis, change‑data analysis, and stream‑batch integration—summarizes required product features, evaluates open‑source lake formats, and details iQIYI's adoption of Apache Iceberg across multiple services to achieve low‑latency, large‑scale, cost‑effective analytics.

Big DataIcebergStreaming
0 likes · 23 min read
Understanding Data Lakes and Their Application at iQIYI: Concepts, Scenarios, and Iceberg Implementation
DataFunSummit
DataFunSummit
Jan 10, 2023 · Big Data

Exploring Iceberg in Huawei Terminal Cloud: Architecture, Features, and Future Plans

This article presents a comprehensive overview of Iceberg's adoption in Huawei Terminal Cloud, covering its architectural overview, key features such as Git‑style data management, real‑time processing, acceleration layers, and future development directions, along with a Q&A session addressing performance and implementation details.

Big DataFlinkGit-style Data Management
0 likes · 15 min read
Exploring Iceberg in Huawei Terminal Cloud: Architecture, Features, and Future Plans
Big Data Technology Architecture
Big Data Technology Architecture
Jun 10, 2021 · Big Data

Understanding Apache Iceberg: Design, Architecture, and Its Application at NetEase Cloud Music

This article explains Apache Iceberg’s table‑format design, compares it with Hive’s limitations, details its snapshot‑based architecture and metadata handling, and describes how NetEase Cloud Music leveraged Iceberg to dramatically improve large‑scale log processing performance and stability.

Apache IcebergBig DataSpark
0 likes · 12 min read
Understanding Apache Iceberg: Design, Architecture, and Its Application at NetEase Cloud Music
DataFunTalk
DataFunTalk
Apr 26, 2021 · Big Data

Detailed Design and Practical Application of Apache Iceberg at NetEase Cloud Music

This article explains the motivations behind Apache Iceberg, its design principles such as snapshot and MVCC, compares it with Hive, and describes how NetEase Cloud Music adopted Iceberg to improve metadata handling, query performance, and operational stability for massive daily log data.

Apache IcebergBig DataHive
0 likes · 13 min read
Detailed Design and Practical Application of Apache Iceberg at NetEase Cloud Music
Big Data Technology Architecture
Big Data Technology Architecture
Apr 5, 2021 · Big Data

Understanding Apache Iceberg: Table Format Architecture, Comparison with Hive Metastore, and Business Benefits

This article introduces Apache Iceberg as an open table format for massive analytic datasets, explains its underlying concepts such as schema, partitioning, statistics, and read/write APIs, compares it with Hive Metastore, outlines its ACID commit process, highlights the performance and operational advantages for big‑data workloads, and previews upcoming community features.

ACIDApache IcebergBig Data
0 likes · 19 min read
Understanding Apache Iceberg: Table Format Architecture, Comparison with Hive Metastore, and Business Benefits
DataFunTalk
DataFunTalk
Dec 3, 2020 · Big Data

Streaming Data Lake Ingestion with Apache Flink and Apache Iceberg

This article explains how Apache Flink integrates with data lake architectures, especially using Apache Iceberg as a table format, to enable real‑time streaming ingestion, CDC processing, near‑real‑time lambda architectures, and future enhancements like automatic file merging and row‑level deletes.

Apache IcebergBig DataFlink
0 likes · 13 min read
Streaming Data Lake Ingestion with Apache Flink and Apache Iceberg
Big Data Technology Architecture
Big Data Technology Architecture
Nov 27, 2020 · Big Data

Integrating Apache Flink with Data Lakes Using Apache Iceberg: Architecture, Use Cases, and Future Roadmap

This article explains how Apache Flink combines with Apache Iceberg to build unified stream‑batch data lake solutions, covering data lake fundamentals, architectural layers, classic business scenarios, reasons for choosing Iceberg, streaming ingestion design, and upcoming community enhancements.

Apache FlinkApache IcebergBig Data
0 likes · 13 min read
Integrating Apache Flink with Data Lakes Using Apache Iceberg: Architecture, Use Cases, and Future Roadmap
DataFunTalk
DataFunTalk
Oct 9, 2020 · Big Data

NetEase’s Data Lake Iceberg: Challenges, Core Principles, and Practical Implementation

This article examines the pain points of traditional data warehouse platforms, explains the core concepts and advantages of the Iceberg data lake table format, compares it with Metastore, reviews the current Iceberg community ecosystem, and details NetEase’s practical integration with Hive, Impala, and Flink to improve ETL efficiency and support unified batch‑stream processing.

Big DataETLFlink
0 likes · 13 min read
NetEase’s Data Lake Iceberg: Challenges, Core Principles, and Practical Implementation