luzhijing commented on code in PR #824: URL: https://github.com/apache/doris-website/pull/824#discussion_r1668560787
########## versioned_docs/version-2.1/table-design/data-partition.md: ########## @@ -38,31 +38,31 @@ A table consists of rows and columns: - Column: Used to describe different fields in a row of data; -- Columns can be divided into two types: Key and Value. From a business perspective, Key and Value can correspond to dimension columns and metric columns, respectively. The key columns in Doris are those specified in the table creation statement, which are the columns following the keywords `unique key`, `aggregate key`, or `duplicate key`. The remaining columns are value columns. From the perspective of the aggregation model, rows with the same Key columns will be aggregated into a single row. The aggregation method for value columns is specified by the user during table creation. For more information on aggregation models, refer to the Doris [Data Model](../table-design/data-model/overview). +- Columns can be divided into two types: Key and Value. From a business perspective, Key and Value can correspond to dimension columns and metric columns respectively. The key columns in Apache Doris are those specified in the table creation statement, which are the columns following the keywords `unique key`, `aggregate key`, or `duplicate key`. The remaining columns are value columns. From the perspective of the aggregation model, rows with the same Key columns will be aggregated into a single row. The aggregation method for value columns is specified by the user during table creation. For more information on aggregation models, refer to the Doris [Data Model](../table-design/data-model/overview). ### Partition & Tablet -Doris supports two levels of data partitioning. The first level is Partitioning, which supports Range and List partition. The second level is Bucket (also known as Tablet), which supports Hash and Random . If no partitioning is established during table creation, Doris generates a default partition that is transparent to the user. When using the default partition, only Bucket is supported. +Apache Doris supports two levels of data partitioning. The first level is partition, which supports RANGE partitioning and LIST partitioning. The second level is tablet (also called bucket), which supports Hash bucket and Random bucket. If no partition is established during table creation, Apache Doris generates a default partition that is transparent to the user. When using the default partition, only bucket is supported. -In the Doris storage engine, data is horizontally partitioned into several tablets. Each tablet contains several rows of data. There is no overlap between the data in different tablets, and they are stored physically independently. +In the Apache Doris storage engine, data is horizontally partitioned into several tablets. Each tablet contains several rows of data. There is no overlap between the data in different tablets, and they are stored physically independently. Multiple tablets logically belong to different partitions. A single tablet belongs to only one partition, while a partition contains several tablets. Because tablets are stored physically independently, partitions can also be considered physically independent. The tablet is the smallest physical storage unit for operations such as data movement and replication. Several partitions compose a table. The partition can be considered the smallest logical management unit. -Benefits of Two-Level data partitioning: +The benefits of Apache Doris's two-level data partitioning are as follows: -- For dimensions with time or similar ordered values, such dimension columns can be used as partitioning columns. The partition granularity can be evaluated based on import frequency and partition data volume. +- Columns with ordered values can be used as partitioning columns. The partition granularity can be evaluated based on import frequency and partition data volume. -- Historical data deletion requirements: If there is a need to delete historical data (such as retaining only the data for the most recent several days), composite partition can be used to achieve this goal by deleting historical partitions. Alternatively, DELETE statements can be sent within specified partitions to delete data. +- If there is a need to delete historical data (such as retaining only the data for the most recent several days), composite partition can be used to achieve this goal by deleting historical partitions. Alternatively, `DELETE` statements can be sent within specified partitions to delete data. -- Solving data skew issues: Each partition can specify the number of buckets independently. For example, when partitioning by day and there are significant differences in data volume between days, the number of buckets for each partition can be specified to reasonably distribute data across different partitions. It is recommended to choose a column with high distinctiveness as the bucketing column. +- Each partition can specify the number of buckets independently. For example, when data is partitioned by day and there are significant differences in data volume between days, the number of tablets for each partition can be specified to reasonably distribute data across different partitions. It is recommended to choose a column with high distinctiveness as the bucketing column. Review Comment: buckets -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. 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