蠍襦覯 觜 蟲豢 , れ企 企殊磯 弰 觜るり骸 誤朱 螻ろ伎 れ 伎 誤 螳 襴暑 | Let me introduce you in detail the services available on the Naver cloud platform and what the infrastructure needs to consider when building a global service.
[pgday.Seoul 2022] PostgreSQL with Google CloudPgDay.Seoul
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Google Cloud offers several fully managed database services for PostgreSQL workloads, including Cloud SQL and AlloyDB.
Cloud SQL provides a fully managed relational database service for PostgreSQL, MySQL, and SQL Server. It offers 99.999% availability, unlimited scaling, and automatic failure recovery.
AlloyDB is a new database engine compatible with PostgreSQL that provides up to 4x faster transactions and 100x faster analytics queries than standard PostgreSQL. It features independent scaling of storage and computing resources.
Google Cloud aims to be the best home for PostgreSQL workloads by providing compatibility with open source PostgreSQL and enterprise-grade features, performance, reliability, and support across its database services.
[Pgday.Seoul 2021] 2. Porting Oracle UDF and OptimizationPgDay.Seoul
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The document discusses porting functions from Oracle to PostgreSQL and optimizing performance, including different function types in PostgreSQL like SQL functions and PL/pgSQL functions, as well as volatility categories. It also provides examples of test data created for use in examples and covers strategies for analyzing inefficient Oracle functions and improving them to leverage the PostgreSQL optimizer.
This document summarizes how to set up and use Citus, an open-source PostgreSQL-based distributed database. It explains how to install Citus, add worker nodes, create distributed tables, and use features like reference tables to perform distributed queries across the cluster.
[Pgday.Seoul 2018] PostgreSQL 焔レ 螳覦 殊企襴 OS 螳 apposhaPgDay.Seoul
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This document introduces AppOS, an operating system specialized for database performance. It discusses how AppOS improves on Linux by being more optimized for database workloads through techniques like specialized caching, I/O scheduling based on database priorities, and atomic writes. It also explains how AppOS is portable, high performing, and extensible to support different databases through its modular design. Future plans include improving cache management, parallel query optimization, and cooperative CPU scheduling.
[Pgday.Seoul 2018] 願鍵譬 DB PostgreSQL襦 Migration DB2PGPgDay.Seoul
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This document discusses DB2PG, a tool for migrating data between different database management systems. It began as an internal project in 2016 and has expanded its supported migration paths over time. It can now migrate schemas, tables, data types and more between Oracle, SQL Server, DB2, MySQL and other databases. The tool uses Java and supports multi-threaded imports for faster migration. Configuration files allow customizing the data type mappings and queries used during migration. The tool is open source and available on GitHub under the GPL v3 license.
The document discusses setting up PostgreSQL in an AWS cloud environment. It provides information on using PostgreSQL with AWS services like RDS, Aurora, EC2 and EBS. It compares IaaS vs PaaS deployment options and discusses features of AWS databases like backups, read replicas, high availability and security. The document also summarizes benefits of Aurora over traditional databases like faster crash recovery, continuous backups and independent scaling of database layers.
[Pgday.Seoul 2017] 6. GIN vs GiST 碁煙 伎手鍵 - 覦讌PgDay.Seoul
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B-tree is ideal for unique values while GIN is ideal for indexes with many duplicates. GIST can index most data types and is useful for operations like containment and overlap. A comparison found that GIN indexes have faster search times but slower update times than GiST indexes, and GIN indexes are larger in size and take longer to build. In summary, the best index type depends on the data characteristics and query operations.
This document provides technical details about PostgreSQL WAL (Write Ahead Log) buffers. It describes the structure and purpose of WAL segments, WAL records, and their components. It also explains how the WAL is used to safely recover transactions after a server crash by replaying the log.
4. 伎手鍵...III.
1. Big Data / Internet of Things / Data warehousing
2. Migrations from other databases to PostgreSQL
3. Operations and administration
4. Performance and feature implementation
5. Tuning PostgreSQL for different work loads
6. Replication, clustering, HA, sharding
7. Tools and utilities for PostgreSQL
8. Benchmarking and hardware, tuning
9. PostgreSQL community and hacking
10. Use cases/Case studies (novel ways in which PostgreSQL is used)
11. PostgreSQL features in development
12. App devs perspectives on Postgres
13. Integrating PostgreSQL with 3rd-party software
14. Location-aware and mapping software with PostGIS
15. Research and teaching with PostgreSQL
21. 谿曙リ骸 譟壱(OS Utility )03-1
1. 螳(覿譟燕) OS Utility 譟壱 (pipeline 牛 朱 螳 豢)
2. 襴 IO 襯 豕 覦一蟇磯 伎れ 豢
Utility Description
strings print the strings of printable characters in files.
iconv Convert encoding of given files from one encoding to another
split split a file into pieces
sed stream editor for filtering and transforming text
Utility Description
ionice get/set program io scheduling class and priority