This article explains how to improve PHP application performance by implementing a data caching class, illustrates a weather‑API example, shows how to set cache duration, avoid duplicate data storage, and discusses production considerations such as concurrency, large data, security, and expiration handling.
This article details a month‑long investigation and step‑by‑step tuning of a Java server's JVM parameters, memory‑leak fixes, and metaspace adjustments that reduced FullGC from dozens of times daily to a single occurrence every ten days while improving overall throughput.
This article demonstrates how to insert 300,000 rows into a MySQL table using MyBatis and JDBC, compares direct batch insertion, row‑by‑row insertion, and optimized batch strategies, and provides performance measurements and practical tips for efficient large‑scale data loading.
Blaze is Kuaishou's self‑developed native execution engine that leverages Rust, DataFusion, and SIMD vectorization to accelerate Spark workloads, offering a 30%+ compute boost, detailed architectural components, deep production‑grade optimizations, and a roadmap for broader adoption.
This article explores the two‑stage LLM inference pipeline, introduces TTFT and TPOT metrics, explains the motivation for prefilling‑decoding separation, presents experimental comparisons between split and merged architectures, and details optimization techniques and parallel‑strategy modeling for DistServe.
This article presents a real‑world case of optimizing a high‑concurrency transaction‑statistics API, detailing diagnosis of a 30‑second latency, SQL refactoring with array_agg and unnest, Java‑level improvements, and Caffeine caching, while also sharing promotional offers for ChatGPT services and a developer community.
This article demonstrates how to insert 300,000 rows into a MySQL table efficiently by defining a User entity, configuring MyBatis and JDBC, comparing direct batch insertion, row‑by‑row insertion, and optimized batch strategies with configurable batch sizes and wait times, and provides performance results and best‑practice recommendations.
This article presents nine comprehensive performance‑optimization strategies—including load balancing, sharding, read/write separation, caching, indexing, CDN, asynchronous processing, code refinement, and algorithm improvement—aimed at boosting the efficiency and scalability of large‑scale backend systems.
This article presents a comprehensive technical overview of using ClickHouse as a native backend to accelerate Spark SQL execution, covering Spark performance bottlenecks, ClickHouse's CPU‑level optimizations, the design and implementation of the Spark‑Native integration, and detailed TPC‑DS benchmark results demonstrating up to 3.5× speedup.
This case study details how the AiFenxi business intelligence platform integrated Apache APISIX as a high‑performance API gateway within Tencent Cloud TKE, addressing latency, scalability, and security challenges, and outlines the architectural changes, deployment steps, and resulting performance improvements.
This article presents a detailed technical overview of accelerating Spark's compute engine using ClickHouse as a native backend, covering Spark performance background, ClickHouse's advantages, the design and implementation of a Spark‑Native acceleration solution, and extensive performance evaluation results.
The article examines PHP’s rise to the 15th spot in the TIOBE June index, analyzing its deep web roots, mature frameworks, performance gains, vibrant community, and integration with modern technologies like Docker and front‑end frameworks, while also discussing future challenges such as scalability, type safety, and cloud‑native adoption.
Meituan enhances Apache Spark by integrating the Gluten‑Velox vectorized execution engine, converting row‑wise operations to columnar SIMD processing, which yields over 40 % memory savings and up to 13 % faster runtimes across thousands of ETL jobs, while addressing stability, ORC support, shuffle redesign, and off‑heap memory optimization.
This article explains why CPU caches are needed, describes the hierarchy and internal structure of L1, L2, and L3 caches, compares direct‑mapped, set‑associative and fully‑associative designs, and shows how cache‑aware coding (row‑major vs column‑major loops) dramatically improves execution speed.
This article describes how a unified membership system serving billions of users across multiple platforms achieves high performance and high availability through dual‑center Elasticsearch clusters, traffic isolation, deep ES optimizations, Redis caching, dual‑center MySQL partitioning, seamless migration, and fine‑grained flow‑control and degradation strategies.
This article explores common performance bottlenecks of WebView and H5 pages in mobile apps and presents a comprehensive set of optimization strategies—including preloading, rendering tweaks, network enhancements, and memory management—to achieve near‑instant page loads and improve overall user experience.
The article examines how the shift to Software‑Defined Vehicles introduces complex performance engineering challenges across software, hardware, and organizational domains, and proposes an engineering‑driven, continuous‑observability approach—including modeling, monitoring, iterative optimization, and specialized team structures—to sustainably improve automotive software performance.
This article presents JD Logistics' one‑stop agile BI platform, detailing the complex data sources, rapid business demands, the UData solution architecture, performance and usability improvements, and future upgrade plans that together enable faster data integration, self‑service reporting, and enhanced decision‑making across the organization.
This article details how the WeChat team leverages ClickHouse at massive scale, introduces a suite of performance observation tools, describes lakehouse reading and bitmap optimizations, and explains the integration of AI workloads, demonstrating overall query speedups of up to tenfold across diverse scenarios.
This article explores fundamental PHP caching techniques—including OPcache, HTTP header client caching, Memcached/Redis object caching, reverse‑proxy page caching, dynamic content caching, and cache invalidation—providing code examples and practical guidance to help developers dramatically improve application performance and scalability.
The article examines performance bottlenecks in marketing systems when filtering blacklisted accounts, proposes multithreaded processing and bitmap-based set operations—including Java BitSet and RoaringBitmap—to dramatically reduce processing time from tens of minutes to milliseconds, and discusses implementation details, memory efficiency, and broader applications such as indexing and Redis.
This article details Mobile QQ's 20‑year evolution, the overwhelming technical debt that made its monolithic architecture unsustainable, and the multi‑stage decoupling, refactoring, and NT architecture upgrades that dramatically improved modularity, performance, development efficiency, and user experience across all platforms.
This guide explains how to deploy RabbitMQ on Kubernetes and improve its performance through Helm installation, resource tuning, monitoring, scaling, security hardening, and advanced configuration techniques, providing practical code examples for each step.
This article explains how virtual scrolling can dramatically improve the performance of large online document editors by rendering only visible content, discusses various implementation strategies such as progressive pagination, canvas rendering, line‑ and block‑level virtualization, and details state management, view‑locking, fast‑scroll handling, and integration scenarios like anchor navigation, find‑replace, and comment systems, while providing code examples and performance test results.
By migrating the CatEar FM live‑streaming app’s WebSocket layer to Chromium’s Cronet network stack, the team unified cross‑platform code, added customizable DNS and proxy support, and cut handshake latency by roughly 150 ms on Android and 250 ms on iOS, paving the way for future HTTP/2 and HTTP/3‑based WebSocket transports.
This article details the product models, usage scenarios, and a series of performance and operational optimizations—including query plan health checks, space reclamation, resource isolation, cloud‑native deployment, cross‑region high availability, and unified monitoring—implemented for the TiDB service operated by 360 Zhihui Cloud since its launch in April 2023.
This article presents a comprehensive case study of Zhihu's Bridge platform, detailing its background, five core modules, unified architecture built on Spark and Flink, bitmap‑based tagging, and performance optimizations that address query speed, write latency, and high‑QPS online checks while outlining future directions with Doris 2.0 and large language models.
The article explains what constitutes an SQL problem, presents a typical case of performance degradation caused by mismatched character sets, and outlines how the SQLE platform can help developers, testers, and DBAs systematically manage and improve SQL quality throughout the software lifecycle.
The article examines Linux 6.1’s preemption mechanism, explaining latency sources, the three preemption configurations (none, voluntary, full), the TIF_NEED_RESCHED flag and preempt_count tracking, and how preempt_enable/disable affect real‑time responsiveness, illustrated by a case where RT threads cannot preempt CFS due to disabled preemption in critical driver code.
The article explains how NCCL’s collective communication libraries enable efficient large‑scale model training by parsing GPU‑to‑NIC topology, forming flat‑ring and tree rings, improving logging and bandwidth metrics, detailing Ring AllReduce primitives, and proposing solutions to missing topology, metric, and mapping information for future optimization.
This article demonstrates how to build a high‑performance data processing engine using PHP and SOAP by setting up a SOAP server, creating a client, and applying optimization techniques such as efficient function design, caching, asynchronous processing, and database tuning.
This article explains how to reduce server load and improve performance of Go applications on Kubernetes by using lightweight base images, fine‑tuning resource limits, adjusting garbage‑collection settings, employing connection pools, configuring health probes, and leveraging autoscaling, load balancing, and caching techniques.
The article introduces Archer, a new big‑data warehouse engine built on Iceberg that adds an inverted‑index mechanism using Tantivy to provide full‑text and JSON search, storage‑compute separation, and significant performance gains over traditional Elasticsearch and Iceberg connectors.
This article explains why Mini Programs are popular, describes their dual‑thread architecture, and provides concrete strategies—including reducing call frequency, limiting data volume, and applying data layering and rendering chunking—to optimize setData performance and improve user experience.
This article details how Alluxio was adopted to replace NAS in autonomous driving model training, describing the data closed‑loop workflow, the challenges of the previous system, Alluxio's architectural benefits, deployment strategies across single and multiple data centers, functional and performance testing, operational tuning, and the resulting cost and efficiency gains.
This article explains the fundamentals of caching, enumerates various client‑side, server‑side and distributed cache types, describes common caching patterns and expiration policies, and highlights practical considerations to effectively improve web application performance and reliability.
This article describes how 58.com designed and implemented a large‑scale user profiling platform using ClickHouse, covering system overview, core modules, major challenges of scale, complexity and performance, and the detailed storage, query, and optimization techniques applied to meet business needs.
This article presents a comprehensive log governance and mining solution for distributed systems, covering background challenges, usage scenarios, and detailed strategies such as distributed log integration, front‑back end traceability, standardized log management, large‑payload handling, efficient cleaning, and future plans for componentization and sampling.
This article explains how a data‑driven approach to code reduction—measuring function usage, weighting functions, and prioritizing deletions—enabled a large‑scale backend coupon system to cut code‑review effort by up to 40%, improve readability, and manage the high risks of refactoring.
This article explains the CPU cache locality principle, shows how to restructure Go data access patterns—including data structures, field ordering, memory allocation, and false sharing avoidance—and demonstrates measurable performance gains with a matrix‑multiplication benchmark.
Java developers must master performance optimization by using tools like Skywalking and Arthas, which leverage Java agents, class-loading and bytecode manipulation (via ByteBuddy/ByteKit) to locate bottlenecks, filter data with OGNL, and fine-tune interface response times in real-time.
This article documents how a team reduced the average deployment time of the omega application from 229 seconds to 69.71 seconds—a 69% speed‑up—by analyzing startup logs, removing unused middleware, upgrading libraries, fixing logging configurations, and applying async bean creation and script optimizations.
This article details a series of Kafka message backlog incidents in a busy restaurant ordering system, analyzes root causes such as consumer speed, database indexing, and sudden traffic spikes, and presents step‑by‑step optimizations—including batch queries, index tuning, data archiving, and thread‑pool adjustments—to restore real‑time performance.
Spring 6.2 introduces asynchronous bean initialization, a new addSingletonCallback mechanism, global transaction rollback settings, and injection performance optimizations, eliminating blocking during multi‑threaded event publishing and dramatically reducing startup time, as demonstrated with code examples and performance test results.
Manbang Group scaled its digital freight platform by replacing self‑built Eureka and ZooKeeper clusters with Alibaba Cloud MSE Nacos and ZooKeeper, achieving seamless traffic migration, dramatic performance gains, and high‑availability features such as push‑empty protection and incremental pull for Eureka clients.
This article presents a comprehensive overview of Tencent PCG's GPU‑based recommendation model training framework, detailing why GPU adoption is essential, the hardware and software challenges faced, the multi‑level data architecture, pipeline design, and a series of network, storage, and compute optimizations, followed by future directions.
This article shares the architecture design, cluster deployment, storage selection, multi‑region mode, service discovery, performance tuning, monitoring, alerting, and future plans of a production‑grade Apache Pulsar platform running on Kubernetes, providing valuable insights for engineers adopting Pulsar.
This article shares 360's practical experience deploying Apache Pulsar on Kubernetes, covering architecture design, storage choices, multi‑cluster modes, service discovery, performance tuning, monitoring, alerting, and future plans, offering valuable guidance for engineers building cloud‑native messaging platforms.
This article explains how Lazada’s internal selection platform leveraged Hologres and the RoaringBitmap compression algorithm to dramatically reduce storage costs, accelerate set operations, and break the 200,000‑item pool limit, achieving up to a 99% speed improvement in scheduling.
This article details the migration of the Cloud Music desktop client from a legacy NEJ‑CEF hybrid to a React‑based architecture, outlines four major performance challenges, and explains the step‑by‑step optimizations—including API preloading, render memoization, virtual‑list replacement, and resource‑usage reductions—that cut startup latency by 48%, eliminated interaction stutter, and dramatically lowered CPU, GPU, and memory consumption.
This article details the design, implementation, and evaluation of an AI‑powered tool that automatically creates compliant Git commit messages by leveraging large language models, custom plugins, and performance‑focused optimizations to improve developer productivity and commit quality.
This article explains the fundamentals of garbage collection, compares manual and automatic memory management, outlines common GC algorithms, and provides practical guidance on performance analysis, tool selection, and optimization techniques to improve application responsiveness and resource utilization.
This article explains how using an off‑heap local cache (OHC) can dramatically lower GC pauses and cut interface latency by up to tenfold, covering the underlying principles, configuration, custom serializers, performance testing, monitoring metrics, and practical optimization recommendations for high‑traffic Java backend services.
This guide walks you through Nginx fundamentals, core and advanced configuration, reverse‑proxy setup, access control, HTTPS security, system parameter tuning, and practical deployment examples, providing a comprehensive visual reference for mastering high‑performance web server management.
This article outlines the architecture of JD's H5 marketing pages, compares native and H5 development, details container layering, describes functional implementation, and presents a comprehensive set of server‑side and front‑end testing methods, performance optimization, online tracking, and current pain points to improve testability and reliability.
This article explains how Alluxio enables a unified lake‑warehouse architecture by decoupling compute and storage, outlines its core capabilities, evaluates the cost‑saving and performance benefits, discusses the technical challenges, and presents several practical deployment scenarios in finance and AI workloads.
This article explains how Profile‑Guided Optimization (PGO) can increase MySQL throughput by 30‑50% without changing application code, detailing the required compilation steps, necessary CMake flags, and real‑world benchmark results that demonstrate the performance gains and their limitations.
This article compiles seven hands‑on Linux performance‑optimization practices—including hardware, kernel, and network tuning, diagnostic commands, memory accounting, swap usage, and TCP parameter adjustments—to help engineers quickly identify and resolve stability and speed issues in production environments.
This article provides a comprehensive overview of Apache Hudi 1.0, detailing its architectural redesign, five major development directions, and the most important new capabilities such as LSM‑tree timeline, function indexes, file‑group readers/writers, partial updates, and non‑blocking concurrency control, along with performance evaluations and resource links.
The article uses Rust benchmarks to show how cache layout, prefetching, associativity, false sharing, pipeline stalls, and loop data dependencies impact performance, and demonstrates practical optimizations such as row‑major traversal, proper alignment, avoiding dependent loops, and leveraging sequential access to achieve near‑optimal speed.
A Tencent engineer fixed a severe memory‑leak in the qs library’s encode function by processing 30 MB strings in 1024‑character chunks, reducing heap usage from 2.5 GB to 0.48 GB and cutting runtime from 7.9 s to 2.1 s, achieving a five‑fold speedup and memory reduction, and contributed the change as an open‑source pull request.
This article details ZA Bank’s implementation of a Flutter hot‑fix solution, describing the evaluation of various approaches, the selection of a FlutterWeb‑based page‑downgrade strategy, the design of backend patch management, challenges such as font loading and package size, and the resulting high fix rate and performance improvements.
This article details how the AnnieX cross‑platform container was enhanced for the 2024 Douyin Spring Festival by introducing an interactive suite that includes engine pre‑heating, a shared offline asset library, and advanced 3D resource compression techniques, resulting in significant performance gains and bandwidth savings.
This tutorial explains Lua scripting fundamentals, why Lua is ideal for Redis, common use cases, and step‑by‑step integration of Lua scripts into Spring Boot applications—including dependency setup, configuration, code examples, performance benefits, error handling, security considerations, and best‑practice recommendations.
This article details the technical implementation of the "Lucky Dragon" Spring Festival interactive game in Douyin, covering the cross‑platform framework, SAR Creator engine, scene construction, animation control, coordinate synchronization, terrain management, and performance‑focused scene switching strategies.
This article introduces the fundamentals of bitwise operations, explains common operators, presents practical tricks such as parity checks, swapping without extra space, clearing and extracting the lowest set bit, and demonstrates real‑world applications like bit counting and permission management with clear C code examples.
This article introduces Spring 6.2’s Parallel Bean Initialization feature, explains its benefits for reducing startup time, provides step‑by‑step code examples for configuring background bean initialization and a bootstrap executor, compares traditional and concurrent initialization timings, and details the underlying implementation in the Spring container.
This article explains why Ansible can be slow with many tasks, shows how to profile task execution, analyzes the detailed SSH‑based execution process, and provides practical optimizations such as adjusting forks, using async/poll, enabling persistent SSH connections, pipelining, tweaking fact collection, and employing the Mitogen strategy plugin.
The Cloud Music team integrated a lightweight on‑device full‑text engine using SQLite FTS5 with a simple tokenizer, replaced JavaScript matching with SQLite’s bm25(), parallelized queries, and cut search latency by 75%, boosting CTR 13% and average playback by 17 seconds while preserving user privacy.
This article explains how Go's sync.Pool can reduce memory allocations and garbage‑collection overhead in high‑performance applications, provides step‑by‑step usage examples, demonstrates a byte‑buffer pool, shows performance benefits, and visualizes the mechanism with UML class and sequence diagrams.
The ByteHouse performance whitepaper details the cloud‑native data warehouse’s architecture, rule‑based and cost‑based optimizer enhancements, exchange runtime, runtime filters, parallelism and wide‑table optimizations, and presents benchmark comparisons on TPC‑DS, TPC‑H and SSB datasets demonstrating orders‑of‑magnitude query speed improvements.
This article demonstrates how to replace a costly double‑for‑loop that matches two large lists of users with a HashMap lookup, showing performance measurements, the effect of adding a break statement, and detailed Java code examples for backend developers.
iQIYI improves its Android app for low‑end phones by classifying devices, streamlining startup with task‑based scheduling and baseline profiles, reducing UI thread load through card layout hard‑coding, message queuing, effect degradation, and pre‑fetching data, while continuously monitoring performance to ensure faster, smoother user experiences.
The article presents practical backend performance optimization methods—including substituting Protobuf with native C++ classes, employing cache‑friendly data structures, integrating jemalloc/tcmalloc, using lock‑free double‑buffer designs, and tailoring data formats—to achieve up to three‑fold speed improvements and significant latency reductions.
Meituan Waimai’s search team built a GPU‑accelerated, mixed vector‑and‑scalar retrieval engine that supports billions of items, achieving over 99% recall and up to 89% latency reduction by combining pre‑filtering, optimized data layouts, multi‑GPU parallelism, and FP16 precision.
This article details the background, actions, and future outlook of performance and experience optimization for the Five-Star Store mini program, covering template handling, JS error reduction, rendering speed improvements, package size reduction, and systematic testing and iteration mechanisms across multiple device platforms.
This article shares Xiaomi's real‑world challenges and solutions when building a new Spark 3.1‑based data platform, covering Multiple Catalog implementation, Hive‑to‑Spark SQL migration, automated batch upgrades, performance and stability optimizations, and future roadmap for vectorized execution.
In large‑scale Flink double‑stream joins, terabyte‑sized RocksDB state caused severe compaction latency and CPU spikes, but enabling RocksDB BlobDB KV‑separation (and an inner‑compaction patch) dramatically shrank SST files, reduced read/write latencies to sub‑millisecond levels, and cut CPU spikes by about half.
The article analyzes ByteDance and Peking University's MegaScale system that enables efficient, stable training of large language models on clusters exceeding ten thousand GPUs, detailing algorithmic tweaks, 3D parallel communication overlap, operator optimizations, data‑pipeline improvements, network tuning, and fault‑tolerance mechanisms that together achieve a 55.2% MFU on a 175B model.
OPPO's data architects combined their self‑developed Shuttle service with Alluxio to double performance, halve system pressure, and double throughput, while building a unified Data & AI lakehouse that integrates structured and unstructured data, metadata management, real‑time ingestion, and cloud cost reductions.
This guide explains how to efficiently load one billion 1‑KB log entries from HDFS or S3 into MySQL by analyzing B‑tree limits, using batch inserts, choosing the right storage engine, sharding tables, optimizing file reading, and coordinating tasks with Redis, Redisson, and Zookeeper.
Bilibili has finished beta development of its HarmonyOS native video app—the first bullet‑comment‑enabled video client on the platform—offering medium‑long video playback, personalized recommendations, search, hot lists and interactive features, while cutting build times from over twenty to under five minutes and targeting a full commercial launch with expanded services across smartphones, tablets, displays and vehicles in Q4 2024.
This article explains how to integrate Lua scripts into Spring Boot applications for Redis, covering Lua fundamentals, performance benefits, common use cases, step‑by‑step implementation with Spring Data Redis, error handling, security considerations, and best‑practice recommendations.
Meta introduces a generative recommendation framework (GR) built on the Hierarchical Sequential Transduction Unit (HSTU) that unifies heterogeneous features, treats user behavior as a new modality, and leverages novel encoder and inference optimizations to achieve order‑of‑magnitude scaling in model size, training compute, and online latency while delivering 12‑18% online gains over traditional deep recommendation models.
This article explains the value of user profiling platforms, outlines their core functions, presents a layered architecture with open‑source options, and details engineering optimizations—from wide‑table design to BitMap caching and task‑mode execution—while also discussing current industry trends.
The article details how the Xiaohongshu data warehouse team integrated StarRocks into their offline processing pipeline, replacing Spark for heavy Cube calculations, which reduced job execution from hours to minutes, cut resource consumption by over 90%, advanced daily data output by 1.5 hours, and lowered refresh cost by more than 99%.
This article presents a detailed case study of optimizing a distributed batch processing system by replacing static shard‑key concurrency with a dynamic task‑grabbing mechanism, dramatically reducing execution time from several hours to under fifteen minutes while maintaining stable resource usage.
This article details ByteDance's large‑scale evolution of Spark Shuffle to a cloud‑native architecture, describing background, stability and mixed‑resource scenarios, challenges such as CPU and I/O limits, custom ESS enhancements, shuffle throttling, spill‑split mechanisms, and the Cloud Shuffle Service with its push‑based design and performance gains.
By replacing part of its Spark‑based offline pipeline with StarRocks, Xiaohongshu’s data‑warehouse team cut job execution from hours to minutes, reduced resource usage over 90 %, lowered back‑fill cost by 99 %, and accelerated daily data production by 1.5 hours.
This article demonstrates various methods for inserting 300,000 rows into a MySQL database using Java, including direct batch insertion with MyBatis, row‑by‑row insertion, and optimized batch strategies for both MyBatis and JDBC, along with performance results and practical tips.
This article introduces KwaiBI, the internal data analysis product of Kuaishou, outlines its five major functional areas, details the performance challenges of large‑scale analytics, and presents a comprehensive set of optimization techniques—including cache warming, query rewriting, materialized acceleration, and the Bleem lake‑house engine—along with future directions and a brief Q&A.
This article dissects Redis's memory architecture, explains each memory component, walks through object encoding rules, buffer handling, fragmentation, and child‑process memory, then presents two production incidents with step‑by‑step analysis and concrete optimization actions to prevent future memory alarms.
This article presents Tencent Game's comprehensive lakehouse integration practice, detailing the project background, storage‑compute separation, data layering, unified DDL/DML operations, performance optimizations, and future plans, illustrating how StarRocks, Iceberg, and Spark are combined to achieve scalable, cost‑effective analytics for massive game data.
This presentation by Ctrip algorithm expert Wei Peng details the rapid development of large language models, their core capabilities, and practical applications in the travel industry, covering content marketing, multimodal interactions, customer service efficiency, model comparisons, fine‑tuning, and inference performance optimization.
This article walks through a series‑by‑step performance‑tuning process for high‑throughput C++ services, replacing Protobuf with plain classes, adopting cache‑friendly hash tables, switching to jemalloc, implementing a double‑buffer lock‑free data structure, and tailoring data formats, each backed by concrete code examples, benchmark results, and analysis of trade‑offs.
In this article the author walks through the 1 billion‑row (1brc) challenge, shows a naïve PHP implementation, profiles its bottlenecks, and incrementally applies optimizations—switching from fgetcsv to fgets, using references, adding type casts, enabling JIT and parallel processing—to reduce runtime from 25 minutes to under 30 seconds.
The article presents a comprehensive case study of Ctrip's flight order itinerary system, detailing its background challenges, design goals, modular architecture, data aggregation strategies, sharding and Redis caching optimizations, and the adoption of Java structured concurrency to achieve high performance, reliability, and scalability.
iQIYI migrated hundreds of petabytes of Hive tables to Apache Iceberg using dual‑write, in‑place, and CTAS strategies, combined with partition pruning, Bloom filters, and Trino/Alluxio optimizations, achieving up to 40% lower query latency, simplified pipelines, and faster, cost‑effective data lake operations.
This article explains the concept of full‑chain load testing for e‑commerce systems, outlines why it is essential, discusses major challenges such as coordination and data isolation, and provides practical steps and optimization strategies to reliably simulate real‑world traffic and improve system stability.
The article explains why collective communication is critical for distributed large‑model training, outlines the new requirements for system reliability, and introduces Baidu’s Collective Communication Library (BCCL), detailing its enhanced observability, fault‑diagnosis, stability, and performance optimizations that raise effective training time to 98 % and bandwidth utilization to 95 %.
