This is an automated email from the ASF dual-hosted git repository.
kassiez pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/doris-website.git
The following commit(s) were added to refs/heads/master by this push:
new 579b670b70b [Improvement](docs) refine query acceleration doc (#1678)
579b670b70b is described below
commit 579b670b70b83318a730f9ed23fbf46a7b83a4c4
Author: xzj7019 <[email protected]>
AuthorDate: Tue Dec 31 10:16:13 2024 +0800
[Improvement](docs) refine query acceleration doc (#1678)
## Versions
- [x] dev
- [x] 3.0
- [x] 2.1
- [ ] 2.0
## Languages
- [x] Chinese
- [x] English
## Docs Checklist
- [ ] Checked by AI
- [ ] Test Cases Built
---
.../tuning/tuning-plan/optimizing-table-index.md | 61 +---------------------
.../tuning/tuning-plan/optimizing-table-index.md | 59 +--------------------
.../tuning/tuning-plan/optimizing-table-index.md | 59 +--------------------
.../tuning/tuning-plan/optimizing-table-index.md | 59 +--------------------
.../tuning/tuning-plan/optimizing-table-index.md | 61 +---------------------
.../tuning/tuning-plan/optimizing-table-index.md | 61 +---------------------
6 files changed, 6 insertions(+), 354 deletions(-)
diff --git
a/docs/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
b/docs/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
index 4748a908e1c..09023febf1d 100644
--- a/docs/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
+++ b/docs/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
@@ -94,65 +94,6 @@ For full-text searches of text types and equal value or
range queries on string,
:::
-## Case 3: Adjusting Field Order to Leverage ZoneMap Index for Data Filtering
-
-The ZoneMap index is a built-in index that maintains statistical information
such as Min/Max/Count on column-stored data. When Doris scans the storage layer
for data, it can quickly filter out data blocks that do not meet the filtering
conditions based on the ZoneMap statistical information (such as Min/Max) of
the filtering field, thereby effectively reducing the amount of table scanning.
-
-By default, ZoneMap selects the first column of the schema to establish an
index. Therefore, by reasonably adjusting the field order, this feature can be
fully utilized to accelerate data filtering at the storage layer.
-
-Taking the `store_sales` table in the standard test set TPC-DS as an example,
its original schema definition is as follows:
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ss_sold_date_sk bigint,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-An example of a query fragment is as follows:
-
-```sql
-select *
-from store_sales, date_dim dt
-where dt.d_date_sk = store_sales.ss_sold_date_sk
- and ss_sold_date_sk between 2450816 and 2451000;
-```
-
-To leverage the range filtering condition on the fact table `store_sales` for
rapid storage layer filtering, we can consider adjusting the field definition
order to use the ZoneMap index. Since ZoneMap is established on the first field
by default, we need to adjust the filtering field `ss_sold_date_sk` to the
first position in the schema.
-
-The adjusted schema is as follows:
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_sold_date_sk bigint,
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_sold_date_sk, ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_sold_date_sk, ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-:::tip
-
-Adjust the equal value or range filtering field to the first column of the
schema to leverage the ZoneMap index for data block-level filtering. This can
accelerate the table scanning process, thereby achieving the purpose of
performance tuning.
-
-:::
-
## Summary
-In schema tuning, apart from table-level schema optimization, index
optimization also occupies an important position. Doris provides multiple index
types, including built-in indexes such as prefix and ZoneMap, as well as
secondary indexes such as inverted indexes, which provide strong support for
performance acceleration. By reasonably utilizing these indexes, we can
significantly improve the speed of business queries and analyses in multiple
scenarios, which is of great significance for [...]
\ No newline at end of file
+In schema tuning, apart from table-level schema optimization, index
optimization also occupies an important position. Doris provides multiple index
types, including built-in indexes such as prefix index, as well as secondary
indexes such as inverted indexes, which provide strong support for performance
acceleration. By reasonably utilizing these indexes, we can significantly
improve the speed of business queries and analyses in multiple scenarios, which
is of great significance for multi [...]
\ No newline at end of file
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
index 98cb1a8d60c..53481808a37 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
@@ -92,63 +92,6 @@ Doris 支持倒排索引作为二级索引，以加速等值、范围及文本
:::
-## 案例 3: 调整字段顺序利用 ZoneMap 索引过滤数据
-
-ZoneMap 索引是一种内置索引，它在列存数据上维护了如 Min/Max/Count 等统计信息。当 Doris 对存储层进行数据扫描时，会根据过滤字段的
ZoneMap 统计信息（如 Min/Max）快速过滤掉不满足过滤条件的数据块，从而有效减少扫表量。
-
-默认情况下，ZoneMap 会选择 Schema 的第一列建立索引。因此，通过合理调整字段顺序，可以充分利用这一特性来加速存储层的数据过滤。
-
-以标准测试集 TPC-DS 中的 `store_sales` 表为例，其原始 Schema 定义如下：
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ss_sold_date_sk bigint,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-查询片段示例如下：
-
-```sql
-select *
-from store_sales, date_dim dt
-where dt.d_date_sk = store_sales.ss_sold_date_sk
- and ss_sold_date_sk between 2450816 and 2451000;
-```
-
-为了利用事实表 `store_sales` 上的范围过滤条件进行快速的存储层过滤，我们可以考虑调整字段定义顺序，以便使用 ZoneMap 索引。由于
ZoneMap 默认建立在第一个字段上，因此我们需要将过滤字段 `ss_sold_date_sk` 调整至 Schema 的第一个位置。
-
-调整后的 Schema 如下：
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_sold_date_sk bigint,
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_sold_date_sk, ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_sold_date_sk, ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-:::tip 优化建议
-
-将等值或范围过滤字段调整为 Schema 的第一个列，以便利用 ZoneMap 索引进行数据块级别的过滤。这样可以加速扫表过程，从而达到性能调优的目的。
-
-:::
## 总结
-在 Schema 调优中，除了表级 Schema 优化外，索引优化同样占据重要地位。Doris 提供了多种索引类型，包括前缀、ZoneMap
等内置索引，以及倒排等二级索引。这些索引为性能加速提供了强大的支持，通过合理利用这些索引，我们可以显著提升多场景下的业务查询和分析速度，这对于多场景业务查询和分析具有重要意义。
+在 Schema 调优中，除了表级 Schema 优化外，索引优化同样占据重要地位。Doris
提供了多种索引类型，包括前缀等内置索引，以及倒排等二级索引。这些索引为性能加速提供了强大的支持，通过合理利用这些索引，我们可以显著提升多场景下的业务查询和分析速度，这对于多场景业务查询和分析具有重要意义。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
index 98cb1a8d60c..53481808a37 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
@@ -92,63 +92,6 @@ Doris 支持倒排索引作为二级索引，以加速等值、范围及文本
:::
-## 案例 3: 调整字段顺序利用 ZoneMap 索引过滤数据
-
-ZoneMap 索引是一种内置索引，它在列存数据上维护了如 Min/Max/Count 等统计信息。当 Doris 对存储层进行数据扫描时，会根据过滤字段的
ZoneMap 统计信息（如 Min/Max）快速过滤掉不满足过滤条件的数据块，从而有效减少扫表量。
-
-默认情况下，ZoneMap 会选择 Schema 的第一列建立索引。因此，通过合理调整字段顺序，可以充分利用这一特性来加速存储层的数据过滤。
-
-以标准测试集 TPC-DS 中的 `store_sales` 表为例，其原始 Schema 定义如下：
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ss_sold_date_sk bigint,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-查询片段示例如下：
-
-```sql
-select *
-from store_sales, date_dim dt
-where dt.d_date_sk = store_sales.ss_sold_date_sk
- and ss_sold_date_sk between 2450816 and 2451000;
-```
-
-为了利用事实表 `store_sales` 上的范围过滤条件进行快速的存储层过滤，我们可以考虑调整字段定义顺序，以便使用 ZoneMap 索引。由于
ZoneMap 默认建立在第一个字段上，因此我们需要将过滤字段 `ss_sold_date_sk` 调整至 Schema 的第一个位置。
-
-调整后的 Schema 如下：
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_sold_date_sk bigint,
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_sold_date_sk, ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_sold_date_sk, ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-:::tip 优化建议
-
-将等值或范围过滤字段调整为 Schema 的第一个列，以便利用 ZoneMap 索引进行数据块级别的过滤。这样可以加速扫表过程，从而达到性能调优的目的。
-
-:::
## 总结
-在 Schema 调优中，除了表级 Schema 优化外，索引优化同样占据重要地位。Doris 提供了多种索引类型，包括前缀、ZoneMap
等内置索引，以及倒排等二级索引。这些索引为性能加速提供了强大的支持，通过合理利用这些索引，我们可以显著提升多场景下的业务查询和分析速度，这对于多场景业务查询和分析具有重要意义。
+在 Schema 调优中，除了表级 Schema 优化外，索引优化同样占据重要地位。Doris
提供了多种索引类型，包括前缀等内置索引，以及倒排等二级索引。这些索引为性能加速提供了强大的支持，通过合理利用这些索引，我们可以显著提升多场景下的业务查询和分析速度，这对于多场景业务查询和分析具有重要意义。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
index 98cb1a8d60c..53481808a37 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
@@ -92,63 +92,6 @@ Doris 支持倒排索引作为二级索引，以加速等值、范围及文本
:::
-## 案例 3: 调整字段顺序利用 ZoneMap 索引过滤数据
-
-ZoneMap 索引是一种内置索引，它在列存数据上维护了如 Min/Max/Count 等统计信息。当 Doris 对存储层进行数据扫描时，会根据过滤字段的
ZoneMap 统计信息（如 Min/Max）快速过滤掉不满足过滤条件的数据块，从而有效减少扫表量。
-
-默认情况下，ZoneMap 会选择 Schema 的第一列建立索引。因此，通过合理调整字段顺序，可以充分利用这一特性来加速存储层的数据过滤。
-
-以标准测试集 TPC-DS 中的 `store_sales` 表为例，其原始 Schema 定义如下：
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ss_sold_date_sk bigint,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-查询片段示例如下：
-
-```sql
-select *
-from store_sales, date_dim dt
-where dt.d_date_sk = store_sales.ss_sold_date_sk
- and ss_sold_date_sk between 2450816 and 2451000;
-```
-
-为了利用事实表 `store_sales` 上的范围过滤条件进行快速的存储层过滤，我们可以考虑调整字段定义顺序，以便使用 ZoneMap 索引。由于
ZoneMap 默认建立在第一个字段上，因此我们需要将过滤字段 `ss_sold_date_sk` 调整至 Schema 的第一个位置。
-
-调整后的 Schema 如下：
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_sold_date_sk bigint,
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_sold_date_sk, ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_sold_date_sk, ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-:::tip 优化建议
-
-将等值或范围过滤字段调整为 Schema 的第一个列，以便利用 ZoneMap 索引进行数据块级别的过滤。这样可以加速扫表过程，从而达到性能调优的目的。
-
-:::
## 总结
-在 Schema 调优中，除了表级 Schema 优化外，索引优化同样占据重要地位。Doris 提供了多种索引类型，包括前缀、ZoneMap
等内置索引，以及倒排等二级索引。这些索引为性能加速提供了强大的支持，通过合理利用这些索引，我们可以显著提升多场景下的业务查询和分析速度，这对于多场景业务查询和分析具有重要意义。
+在 Schema 调优中，除了表级 Schema 优化外，索引优化同样占据重要地位。Doris
提供了多种索引类型，包括前缀等内置索引，以及倒排等二级索引。这些索引为性能加速提供了强大的支持，通过合理利用这些索引，我们可以显著提升多场景下的业务查询和分析速度，这对于多场景业务查询和分析具有重要意义。
diff --git
a/versioned_docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
b/versioned_docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
index 4748a908e1c..09023febf1d 100644
---
a/versioned_docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
+++
b/versioned_docs/version-2.1/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
@@ -94,65 +94,6 @@ For full-text searches of text types and equal value or
range queries on string,
:::
-## Case 3: Adjusting Field Order to Leverage ZoneMap Index for Data Filtering
-
-The ZoneMap index is a built-in index that maintains statistical information
such as Min/Max/Count on column-stored data. When Doris scans the storage layer
for data, it can quickly filter out data blocks that do not meet the filtering
conditions based on the ZoneMap statistical information (such as Min/Max) of
the filtering field, thereby effectively reducing the amount of table scanning.
-
-By default, ZoneMap selects the first column of the schema to establish an
index. Therefore, by reasonably adjusting the field order, this feature can be
fully utilized to accelerate data filtering at the storage layer.
-
-Taking the `store_sales` table in the standard test set TPC-DS as an example,
its original schema definition is as follows:
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ss_sold_date_sk bigint,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-An example of a query fragment is as follows:
-
-```sql
-select *
-from store_sales, date_dim dt
-where dt.d_date_sk = store_sales.ss_sold_date_sk
- and ss_sold_date_sk between 2450816 and 2451000;
-```
-
-To leverage the range filtering condition on the fact table `store_sales` for
rapid storage layer filtering, we can consider adjusting the field definition
order to use the ZoneMap index. Since ZoneMap is established on the first field
by default, we need to adjust the filtering field `ss_sold_date_sk` to the
first position in the schema.
-
-The adjusted schema is as follows:
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_sold_date_sk bigint,
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_sold_date_sk, ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_sold_date_sk, ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-:::tip
-
-Adjust the equal value or range filtering field to the first column of the
schema to leverage the ZoneMap index for data block-level filtering. This can
accelerate the table scanning process, thereby achieving the purpose of
performance tuning.
-
-:::
-
## Summary
-In schema tuning, apart from table-level schema optimization, index
optimization also occupies an important position. Doris provides multiple index
types, including built-in indexes such as prefix and ZoneMap, as well as
secondary indexes such as inverted indexes, which provide strong support for
performance acceleration. By reasonably utilizing these indexes, we can
significantly improve the speed of business queries and analyses in multiple
scenarios, which is of great significance for [...]
\ No newline at end of file
+In schema tuning, apart from table-level schema optimization, index
optimization also occupies an important position. Doris provides multiple index
types, including built-in indexes such as prefix index, as well as secondary
indexes such as inverted indexes, which provide strong support for performance
acceleration. By reasonably utilizing these indexes, we can significantly
improve the speed of business queries and analyses in multiple scenarios, which
is of great significance for multi [...]
\ No newline at end of file
diff --git
a/versioned_docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
b/versioned_docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
index 4748a908e1c..09023febf1d 100644
---
a/versioned_docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
+++
b/versioned_docs/version-3.0/query-acceleration/tuning/tuning-plan/optimizing-table-index.md
@@ -94,65 +94,6 @@ For full-text searches of text types and equal value or
range queries on string,
:::
-## Case 3: Adjusting Field Order to Leverage ZoneMap Index for Data Filtering
-
-The ZoneMap index is a built-in index that maintains statistical information
such as Min/Max/Count on column-stored data. When Doris scans the storage layer
for data, it can quickly filter out data blocks that do not meet the filtering
conditions based on the ZoneMap statistical information (such as Min/Max) of
the filtering field, thereby effectively reducing the amount of table scanning.
-
-By default, ZoneMap selects the first column of the schema to establish an
index. Therefore, by reasonably adjusting the field order, this feature can be
fully utilized to accelerate data filtering at the storage layer.
-
-Taking the `store_sales` table in the standard test set TPC-DS as an example,
its original schema definition is as follows:
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ss_sold_date_sk bigint,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-An example of a query fragment is as follows:
-
-```sql
-select *
-from store_sales, date_dim dt
-where dt.d_date_sk = store_sales.ss_sold_date_sk
- and ss_sold_date_sk between 2450816 and 2451000;
-```
-
-To leverage the range filtering condition on the fact table `store_sales` for
rapid storage layer filtering, we can consider adjusting the field definition
order to use the ZoneMap index. Since ZoneMap is established on the first field
by default, we need to adjust the filtering field `ss_sold_date_sk` to the
first position in the schema.
-
-The adjusted schema is as follows:
-
-```sql
-CREATE TABLE IF NOT EXISTS store_sales (
- ss_sold_date_sk bigint,
- ss_item_sk bigint not null,
- ss_ticket_number bigint not null,
- ......
- ss_net_paid_inc_tax decimalv3(7,2),
- ss_net_profit decimalv3(7,2)
-)
-DUPLICATE KEY(ss_sold_date_sk, ss_item_sk, ss_ticket_number)
-DISTRIBUTED BY HASH(ss_sold_date_sk, ss_item_sk, ss_ticket_number) BUCKETS 32
-PROPERTIES (
- "replication_num" = "1"
-);
-```
-
-:::tip
-
-Adjust the equal value or range filtering field to the first column of the
schema to leverage the ZoneMap index for data block-level filtering. This can
accelerate the table scanning process, thereby achieving the purpose of
performance tuning.
-
-:::
-
## Summary
-In schema tuning, apart from table-level schema optimization, index
optimization also occupies an important position. Doris provides multiple index
types, including built-in indexes such as prefix and ZoneMap, as well as
secondary indexes such as inverted indexes, which provide strong support for
performance acceleration. By reasonably utilizing these indexes, we can
significantly improve the speed of business queries and analyses in multiple
scenarios, which is of great significance for [...]
\ No newline at end of file
+In schema tuning, apart from table-level schema optimization, index
optimization also occupies an important position. Doris provides multiple index
types, including built-in indexes such as prefix index, as well as secondary
indexes such as inverted indexes, which provide strong support for performance
acceleration. By reasonably utilizing these indexes, we can significantly
improve the speed of business queries and analyses in multiple scenarios, which
is of great significance for multi [...]
\ No newline at end of file
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
