This document introduces Mroonga, a storage engine for MariaDB that provides fast full-text search capabilities for Japanese text. It discusses how Mroonga is faster than other options like InnoDB FTS through its optimized inverted index implementation and column-store architecture. The document also explains that Mroonga is easy for beginners to use as it requires only standard MySQL features and is pre-bundled with MariaDB. More advanced features allow customizations for specialists.
The document discusses using a key-value store (KVS) to store pageview data more efficiently than a relational database. It proposes storing each pageview record as a key-value pair with the key containing fields like page, gender, age. This allows for fast retrieval of records by key. It also questions whether using MongoDB or another NoSQL database would be better than building a custom KVS on top of MySQL. Finally it provides a link to Gree's career page for additional information.
Embulk, an open-source plugin-based parallel bulk data loaderSadayuki Furuhashi
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The document discusses Embulk, an open-source parallel bulk data loader that uses plugins. Embulk loads records from various sources ("A") to various targets ("B") using plugins for different source and target types. This makes the painful process of data integration more relaxed. Embulk executes in parallel, validates data, handles errors, behaves deterministically, and allows for idempotent retries of bulk loads.
The document discusses using a key-value store (KVS) to store pageview data more efficiently than a relational database. It proposes storing each pageview record as a key-value pair with the key containing fields like page, gender, age. This allows for fast retrieval of records by key. It also questions whether using MongoDB or another NoSQL database would be better than building a custom KVS on top of MySQL. Finally it provides a link to Gree's career page for additional information.
Embulk, an open-source plugin-based parallel bulk data loaderSadayuki Furuhashi
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The document discusses Embulk, an open-source parallel bulk data loader that uses plugins. Embulk loads records from various sources ("A") to various targets ("B") using plugins for different source and target types. This makes the painful process of data integration more relaxed. Embulk executes in parallel, validates data, handles errors, behaves deterministically, and allows for idempotent retries of bulk loads.
The document discusses Docker and microservices. It provides motivation for using microservices, including code bloat, increased costs of code changes, and the need for diversity and specialization. It then covers Docker basics like creating images and containers. It discusses how Docker can be used to implement microservices and addresses challenges like transactions across containers and logging. The document concludes that organizations also need to be "micro-ized".
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