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+---
+title: Installation Hive lineage
+sidebar_position: 1
+---
+
+This paper mainly introduces the 'Hive' engine blood collection scheme in 'Linkis'.
+
+
+## 1. Introduction
+
+Hive provides a built-in lineage hook called LineageLogger, which is used to capture and record lineage information generated during query execution. By using the LineageLogger hook, you can capture and log the input and output tables, as well as column-level lineage relationships for queries.
+
+## 2. The Hive lineage collected into the log
+
+### 2.1 Modify `hive-site.xml`
+
+```shell
+vim $HIVE_HOME/conf/hive-site.xml
+
+Add the following configuration
+
+ hive.exec.post.hooks
+ org.apache.hadoop.hive.ql.hooks.LineageLogger
+
+```
+
+### 2.2 Modify `hive-log4j2.properties`
+
+```shell
+vim $HIVE_HOME/conf/hive-log4j2.properties
+
+Add the following configuration
+og4j.logger.org.apache.hadoop.hive.ql.hooks.LineageLogger=INFO
+```
+
+### 2.3 Submit task
+```shell
+sh ./bin/linkis-cli -engineType hive-3.1.3 \
+-codeType hql -code \
+"CREATE TABLE input_table (
+ column1 INT,
+ column2 STRING
+);
+CREATE TABLE output_table (
+ column3 INT,
+ column4 STRING
+);
+INSERT INTO TABLE output_table
+SELECT column1, column2
+FROM input_table;" \
+-submitUser hadoop -proxyUser hadoop
+```
+
+### 2.4 View logs
+```shell
+cat /appcom/tmp/hadoop/20230922/hive/946375fe-f189-487c-b3a7-f9fa821edace/logs/stdout
+```
+
+The output is as follows:
+
+
+Details are as follows:
+```json
+{
+ "version":"1.0",
+ "user":"hadoop",
+ "timestamp":1695354104,
+ "duration":15318,
+ "jobIds":[
+ "job_1691375506204_0488"
+ ],
+ "engine":"mr",
+ "database":"default",
+ "hash":"dbb11fce57f10dccb6ef724f66af611c",
+ "queryText":"INSERT INTO TABLE output_table\nSELECT column1, column2\nFROM input_table",
+ "edges":[
+ {
+ "sources":[
+ 2
+ ],
+ "targets":[
+ 0
+ ],
+ "edgeType":"PROJECTION"
+ },
+ {
+ "sources":[
+ 3
+ ],
+ "targets":[
+ 1
+ ],
+ "edgeType":"PROJECTION"
+ },
+ {
+ "sources":[
+ 2
+ ],
+ "targets":[
+ 0
+ ],
+ "expression":"compute_stats(default.input_table.column1, 'hll')",
+ "edgeType":"PROJECTION"
+ },
+ {
+ "sources":[
+ 3
+ ],
+ "targets":[
+ 1
+ ],
+ "expression":"compute_stats(default.input_table.column2, 'hll')",
+ "edgeType":"PROJECTION"
+ }
+ ],
+ "vertices":[
+ {
+ "id":0,
+ "vertexType":"COLUMN",
+ "vertexId":"default.output_table.column3"
+ },
+ {
+ "id":1,
+ "vertexType":"COLUMN",
+ "vertexId":"default.output_table.column4"
+ },
+ {
+ "id":2,
+ "vertexType":"COLUMN",
+ "vertexId":"default.input_table.column1"
+ },
+ {
+ "id":3,
+ "vertexType":"COLUMN",
+ "vertexId":"default.input_table.column2"
+ }
+ ]
+}
+```
+
diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/current/deployment/images/hive-lineage-log.png b/i18n/zh-CN/docusaurus-plugin-content-docs/current/deployment/images/hive-lineage-log.png
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diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/current/deployment/integrated/hive-lineage.md b/i18n/zh-CN/docusaurus-plugin-content-docs/current/deployment/integrated/hive-lineage.md
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+---
+title: 集成 Hive血缘
+sidebar_position: 1
+---
+
+本文主要介绍在 `Linkis` 中， `Hive` 引擎血缘采集方案。
+
+
+## 1. 介绍
+
+Hive 提供了一个内置的Hook LineageLogger，它用于记录查询执行期间生成的血缘信息。通过使用 LineageLogger Hook，你可以捕获和记录查询的输入和输出表以及列级别的血缘关系
+
+## 2. 将hive血缘采集至日志
+
+### 2.1 修改`hive-site.xml`
+
+```shell
+vim $HIVE_HOME/conf/hive-site.xml
+
+增加如下配置
+
+ hive.exec.post.hooks
+ org.apache.hadoop.hive.ql.hooks.LineageLogger
+
+```
+
+### 2.2 修改`hive-log4j2.properties`
+
+```shell
+vim $HIVE_HOME/conf/hive-log4j2.properties
+
+增加如下配置
+og4j.logger.org.apache.hadoop.hive.ql.hooks.LineageLogger=INFO
+```
+
+### 2.3 提交任务
+```shell
+sh ./bin/linkis-cli -engineType hive-3.1.3 \
+-codeType hql -code \
+"CREATE TABLE input_table (
+ column1 INT,
+ column2 STRING
+);
+CREATE TABLE output_table (
+ column3 INT,
+ column4 STRING
+);
+INSERT INTO TABLE output_table
+SELECT column1, column2
+FROM input_table;" \
+-submitUser hadoop -proxyUser hadoop
+```
+
+### 2.4 查看日志
+```shell
+cat /appcom/tmp/hadoop/20230922/hive/946375fe-f189-487c-b3a7-f9fa821edace/logs/stdout
+```
+
+输出结果如下:
+
+
+详细信息如下:
+```json
+{
+ "version":"1.0",
+ "user":"hadoop",
+ "timestamp":1695354104,
+ "duration":15318,
+ "jobIds":[
+ "job_1691375506204_0488"
+ ],
+ "engine":"mr",
+ "database":"default",
+ "hash":"dbb11fce57f10dccb6ef724f66af611c",
+ "queryText":"INSERT INTO TABLE output_table\nSELECT column1, column2\nFROM input_table",
+ "edges":[
+ {
+ "sources":[
+ 2
+ ],
+ "targets":[
+ 0
+ ],
+ "edgeType":"PROJECTION"
+ },
+ {
+ "sources":[
+ 3
+ ],
+ "targets":[
+ 1
+ ],
+ "edgeType":"PROJECTION"
+ },
+ {
+ "sources":[
+ 2
+ ],
+ "targets":[
+ 0
+ ],
+ "expression":"compute_stats(default.input_table.column1, 'hll')",
+ "edgeType":"PROJECTION"
+ },
+ {
+ "sources":[
+ 3
+ ],
+ "targets":[
+ 1
+ ],
+ "expression":"compute_stats(default.input_table.column2, 'hll')",
+ "edgeType":"PROJECTION"
+ }
+ ],
+ "vertices":[
+ {
+ "id":0,
+ "vertexType":"COLUMN",
+ "vertexId":"default.output_table.column3"
+ },
+ {
+ "id":1,
+ "vertexType":"COLUMN",
+ "vertexId":"default.output_table.column4"
+ },
+ {
+ "id":2,
+ "vertexType":"COLUMN",
+ "vertexId":"default.input_table.column1"
+ },
+ {
+ "id":3,
+ "vertexType":"COLUMN",
+ "vertexId":"default.input_table.column2"
+ }
+ ]
+}
+```
+