This is an automated email from the ASF dual-hosted git repository.
qiaojialin pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/iotdb-docs.git
The following commit(s) were added to refs/heads/main by this push:
new ec4b66c fix some docbugs of latest version (#189)
ec4b66c is described below
commit ec4b66c829f14818c508609dc186c4da4686c0d6
Author: wanghui42 <[email protected]>
AuthorDate: Thu Mar 7 12:01:01 2024 +0800
fix some docbugs of latest version (#189)
---
.../Master/API/Programming-Python-Native-API.md | 136 ++++++++++++---------
.../Master/QuickStart/ClusterQuickStart.md | 2 +-
src/UserGuide/Master/QuickStart/QuickStart.md | 6 +-
.../latest/API/Programming-Python-Native-API.md | 4 +-
.../latest/QuickStart/ClusterQuickStart.md | 2 +-
src/UserGuide/latest/QuickStart/QuickStart.md | 6 +-
.../Master/API/Programming-Python-Native-API.md | 4 +-
.../Master/IoTDB-Introduction/Scenario.md | 2 +-
.../Master/QuickStart/ClusterQuickStart.md | 4 +-
src/zh/UserGuide/Master/QuickStart/QuickStart.md | 6 +-
.../latest/API/Programming-Python-Native-API.md | 4 +-
.../latest/IoTDB-Introduction/Scenario.md | 2 +-
.../latest/QuickStart/ClusterQuickStart.md | 4 +-
src/zh/UserGuide/latest/QuickStart/QuickStart.md | 8 +-
14 files changed, 103 insertions(+), 87 deletions(-)
diff --git a/src/UserGuide/Master/API/Programming-Python-Native-API.md
b/src/UserGuide/Master/API/Programming-Python-Native-API.md
index 8bbadb4..b17d73e 100644
--- a/src/UserGuide/Master/API/Programming-Python-Native-API.md
+++ b/src/UserGuide/Master/API/Programming-Python-Native-API.md
@@ -21,13 +21,19 @@
# Python Native API
+## Requirements
+
+You have to install thrift (>=0.13) before using the package.
+
+
+
## How to use (Example)
First, download the package: `pip3 install apache-iotdb`
-You can see an example of how to use the package to read and write data here:
[Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)
+You can get an example of using the package to read and write data at here:
[Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionExample.py)
-An example of aligned timeseries: [Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)
+An example of aligned timeseries: [Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionAlignedTimeseriesExample.py)
(you need to add `import iotdb` in the head of the file)
@@ -81,7 +87,7 @@ session = Session.init_from_node_urls(
session.open(enable_rpc_compression=False)
```
-Notice: The RPC compression setting of the client is required to match that of
the IoTDB server
+Notice: this RPC compression status of client must comply with that of IoTDB
server
* Close a Session
@@ -90,11 +96,7 @@ session.close()
```
## Managing Session through SessionPool
-Utilizing `SessionPool` to manage sessions eliminates the need to worry about
session reuse.
-When the number of session connections reaches the maximum capacity of the
pool, requests for acquiring a session will block.
-You can set a timeout after which new requests are considered unsuccessful.
-
-After using a session, it should always be returned to the SessionPool using
the `putBack` method for proper management.
+Utilizing SessionPool to manage sessions eliminates the need to worry about
session reuse. When the number of session connections reaches the maximum
capacity of the pool, requests for acquiring a session will be blocked, and you
can set the blocking wait time through parameters. After using a session, it
should be returned to the SessionPool using the `putBack` method for proper
management.
### Create SessionPool
@@ -108,9 +110,7 @@ wait_timeout_in_ms = 3000
# # Create the connection pool
session_pool = SessionPool(pool_config, max_pool_size, wait_timeout_in_ms)
```
-
-### Create a SessionPool using distributed nodes
-
+### Create a SessionPool using distributed nodes.
```python
pool_config = PoolConfig(node_urls=node_urls=["127.0.0.1:6667",
"127.0.0.1:6668", "127.0.0.1:6669"], user_name=username,
password=password, fetch_size=1024,
@@ -118,7 +118,6 @@ pool_config =
PoolConfig(node_urls=node_urls=["127.0.0.1:6667", "127.0.0.1:6668"
max_pool_size = 5
wait_timeout_in_ms = 3000
```
-
### Acquiring a session through SessionPool and manually calling PutBack after
use
```python
@@ -133,7 +132,7 @@ session_pool.put_back(session)
session_pool.close()
```
-## Data Definition Interface (DDI)
+## Data Definition Interface (DDL Interface)
### Database Management
@@ -189,12 +188,13 @@ session.check_time_series_exists(path)
### Insert
-It is recommended to use `insertTablet` to help improve write efficiency.
+It is recommended to use insertTablet to help improve write efficiency.
-* Insert a Tablet，which is multiple rows of data for one device, each row has
the same measurements
+* Insert a Tablet，which is multiple rows of a device, each row has the same
measurements
* **Better Write Performance**
* **Support null values**: fill the null value with any value, and then
mark the null value via BitMap (from v0.13)
+
We have two implementations of Tablet in Python API.
* Normal Tablet
@@ -227,12 +227,12 @@ session.insert_tablet(tablet_)
* Numpy Tablet
Comparing with Tablet, Numpy Tablet is using
[numpy.ndarray](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html)
to record data.
-With less memory footprint and time cost of serialization, therefore the
insert performance will be better.
+With less memory footprint and time cost of serialization, the insert
performance will be better.
**Notice**
-1. time and numerical value columns in Tablet is `ndarray`
-2. recommended to use the specific `dtypes` to each `ndarray`, see the example
below
- (if not, the default `dtypes` are also ok).
+1. time and numerical value columns in Tablet is ndarray
+2. recommended to use the specific dtypes to each ndarray, see the example
below
+ (if not, the default dtypes are also ok).
```python
import numpy as np
@@ -303,7 +303,7 @@ session.insert_records(
```
* Insert multiple Records that belong to the same device.
- With type info the server has no need to do type inference, which results in
a better performance.
+ With type info the server has no need to do type inference, which leads a
better performance
```python
@@ -312,10 +312,7 @@ session.insert_records_of_one_device(device_id, time_list,
measurements_list, da
### Insert with type inference
-If type-information is not present, all values will be converted to their
`String` representation.
-The server then performs type inference to guess the datatype, based on this
string-representation.
-For example, if value string equals "true", it can be automatically inferred
to be a `Boolean` type. If string value is "3.2", it can be automatically
inferred as a `Float` type.
-However, please keep in mind, that this process of guessing the type for a
given value comes at a performance cost.
+When the data is of String type, we can use the following interface to perform
type inference based on the value of the value itself. For example, if value is
"true" , it can be automatically inferred to be a boolean type. If value is
"3.2" , it can be automatically inferred as a flout type. Without type
information, server has to do type inference, which may cost some time.
* Insert a Record, which contains multiple measurement value of a device at a
timestamp
@@ -325,7 +322,7 @@ session.insert_str_record(device_id, timestamp,
measurements, string_values)
### Insert of Aligned Timeseries
-The insertion of aligned timeseries uses interfaces such as
`insert_aligned_XXX`, and others are similar to the above interfaces:
+The Insert of aligned timeseries uses interfaces like insert_aligned_XXX, and
others are similar to the above interfaces:
* insert_aligned_record
* insert_aligned_records
@@ -342,7 +339,7 @@ The insertion of aligned timeseries uses interfaces such as
`insert_aligned_XXX`
session.execute_query_statement(sql)
```
-* Execute non-query statement
+* Execute non query statement
```python
session.execute_non_query_statement(sql)
@@ -355,11 +352,8 @@ session.execute_statement(sql)
```
## Schema Template
-
### Create Schema Template
-
-The process of creating a schema template is as follows
-
+The step for creating a metadata template is as follows
1. Create the template class
2. Adding MeasurementNode
3. Execute create schema template function
@@ -435,15 +429,16 @@ session.show_paths_template_using_on(template_name)
```
### Drop Schema Template
-
-Delete an existing schema template，dropping an already set template is not
supported
+Delete an existing metadata template，dropping an already set template is not
supported
```python
session.drop_schema_template("template_python")
```
+
## Pandas Support
-To easily transform a query result to a [Pandas
Dataframe](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
the `SessionDataSet` has a method `.todf()` which consumes the dataset and
transforms it to a pandas dataframe.
+To easily transform a query result to a [Pandas
Dataframe](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)
+the SessionDataSet has a method `.todf()` which consumes the dataset and
transforms it to a pandas dataframe.
Example:
@@ -467,9 +462,10 @@ session.close()
df = ...
```
+
## IoTDB Testcontainer
-The Test Support is based on the lib `testcontainers`
(https://testcontainers-python.readthedocs.io/en/latest/index.html) which you
need to install in your project if you want to use this feature.
+The Test Support is based on the lib `testcontainers`
(https://testcontainers-python.readthedocs.io/en/latest/index.html) which you
need to install in your project if you want to use the feature.
To start (and stop) an IoTDB Database in a Docker container simply do:
```python
@@ -484,16 +480,17 @@ class MyTestCase(unittest.TestCase):
session.close()
```
-Per default, it will load the image `apache/iotdb:latest`, if you want a
specific version just pass it like e.g. `IoTDBContainer("apache/iotdb:0.12.0")`
to get version `0.12.0`.
+by default it will load the image `apache/iotdb:latest`, if you want a
specific version just pass it like e.g. `IoTDBContainer("apache/iotdb:0.12.0")`
to get version `0.12.0` running.
## IoTDB DBAPI
-IoTDB DBAPI implements the `Python DB API 2.0` specification
(https://peps.python.org/pep-0249/), which defines a common interface for
accessing databases in Python.
+IoTDB DBAPI implements the Python DB API 2.0 specification
(https://peps.python.org/pep-0249/), which defines a common
+interface for accessing databases in Python.
### Examples
+ Initialization
-The initialization parameters are consistent with the session part (except for
the sqlalchemy_mode).
+The initialized parameters are consistent with the session part (except for
the sqlalchemy_mode).
```python
from iotdb.dbapi import connect
@@ -513,7 +510,7 @@ for row in cursor.fetchall():
+ execute SQL with parameter
-IoTDB DBAPI supports `pyformat` style parameters
+IoTDB DBAPI supports pyformat style parameters
```python
cursor.execute("SELECT ** FROM root WHERE time <
%(time)s",{"time":"2017-11-01T00:08:00.000"})
for row in cursor.fetchall():
@@ -540,20 +537,13 @@ conn.close()
```
## IoTDB SQLAlchemy Dialect (Experimental)
-
-The `SQLAlchemy` dialect of IoTDB is written to adapt to `Apache Superset`.
-
+The SQLAlchemy dialect of IoTDB is written to adapt to Apache Superset.
This part is still being improved.
-
-Please do not use it in production environments!
-
+Please do not use it in the production environment!
### Mapping of the metadata
-
-The data model used by `SQLAlchemy` is a relational data model, which
describes the relationships between different entities through tables.
-In contrast to that the data model of IoTDB is a hierarchical data model,
which organizes the data through a tree structure.
-
+The data model used by SQLAlchemy is a relational data model, which describes
the relationships between different entities through tables.
+While the data model of IoTDB is a hierarchical data model, which organizes
the data through a tree structure.
In order to adapt IoTDB to the dialect of SQLAlchemy, the original data model
in IoTDB needs to be reorganized.
-
Converting the data model of IoTDB into the data model of SQLAlchemy.
The metadata in the IoTDB are：
@@ -570,11 +560,11 @@ The metadata in the SQLAlchemy are：
The mapping relationship between them is：
-| The metadata in the SQLAlchemy | The metadata in the IoTDB |
-|--------------------------------|-------------------------------------------|
-| Schema | Database |
-| Table | Path ( from database to entity ) + Entity |
-| Column | Measurement |
+| The metadata in the SQLAlchemy | The metadata in the IoTDB
|
+| -------------------- | -------------------------------------------- |
+| Schema | Database |
+| Table | Path ( from database to entity ) + Entity |
+| Column | Measurement |
The following figure shows the relationship between the two more intuitively:
@@ -636,33 +626,48 @@ for row in res:
print(row)
```
+
## Developers
### Introduction
-This is an example of how to connect to IoTDB with python, using the thrift
rpc interfaces.
-Things are almost the same on Windows or Linux, but pay attention to the
difference like path separator.
+This is an example of how to connect to IoTDB with python, using the thrift
rpc interfaces. Things are almost the same on Windows or Linux, but pay
attention to the difference like path separator.
+
+
### Prerequisites
Python3.7 or later is preferred.
+You have to install Thrift (0.11.0 or later) to compile our thrift file into
python code. Below is the official tutorial of installation, eventually, you
should have a thrift executable.
+
+```
+http://thrift.apache.org/docs/install/
+```
+
Before starting you need to install `requirements_dev.txt` in your python
environment, e.g. by calling
```shell
pip install -r requirements_dev.txt
```
+
+
### Compile the thrift library and Debug
-In the root of IoTDB´s source code folder, run `mvn clean generate-sources
-pl iotdb-client/client-py -am`.
+In the root of IoTDB's source code folder, run `mvn clean generate-sources
-pl iotdb-client/client-py -am`.
This will automatically delete and repopulate the folder `iotdb/thrift` with
the generated thrift files.
This folder is ignored from git and should **never be pushed to git!**
+**Notice** Do not upload `iotdb/thrift` to the git repo.
+
+
+
+
### Session Client & Example
-The IoTDB session-interface is available in `client-py/src/iotdb/Session.py`
(similar to its Java counterpart).
-We also provide an example in `client-py/src/SessionExample.py` which
demonstrates how to use the session module.
+We packed up the Thrift interface in `client-py/src/iotdb/Session.py` (similar
with its Java counterpart), also provided an example file
`client-py/src/SessionExample.py` of how to use the session module. please read
it carefully.
+
Or, another simple example:
@@ -679,6 +684,8 @@ zone = session.get_time_zone()
session.close()
```
+
+
### Tests
Please add your custom tests in `tests` folder.
@@ -687,22 +694,30 @@ To run all defined tests just type `pytest .` in the root
folder.
**Notice** Some tests need docker to be started on your system as a test
instance is started in a docker container using
[testcontainers](https://testcontainers-python.readthedocs.io/en/latest/index.html).
+
+
### Futher Tools
[black](https://pypi.org/project/black/) and
[flake8](https://pypi.org/project/flake8/) are installed for autoformatting and
linting.
Both can be run by `black .` or `flake8 .` respectively.
+
+
## Releasing
To do a release just ensure that you have the right set of generated thrift
files.
-Then run `linting` and `auto-formatting`.
+Then run linting and auto-formatting.
Then, ensure that all tests work (via `pytest .`).
Then you are good to go to do a release!
+
+
### Preparing your environment
First, install all necessary dev dependencies via `pip install -r
requirements_dev.txt`.
+
+
### Doing the Release
There is a convenient script `release.sh` to do all steps for a release.
@@ -714,3 +729,4 @@ Namely, these are
* Run Tests via pytest
* Build
* Release to pypi
+
diff --git a/src/UserGuide/Master/QuickStart/ClusterQuickStart.md
b/src/UserGuide/Master/QuickStart/ClusterQuickStart.md
index 601ff2f..da39027 100644
--- a/src/UserGuide/Master/QuickStart/ClusterQuickStart.md
+++ b/src/UserGuide/Master/QuickStart/ClusterQuickStart.md
@@ -240,7 +240,7 @@ cd /data/iotdb
sbin/remove-datanode.sh 192.168.132.13:6667
# way 2: shrink with NodeID of `show cluster`
-sbin/remove-confignode.sh 7
+sbin/remove-datanode.sh 7
```
### 3.3 check the result
diff --git a/src/UserGuide/Master/QuickStart/QuickStart.md
b/src/UserGuide/Master/QuickStart/QuickStart.md
index e8b182b..a72e09d 100644
--- a/src/UserGuide/Master/QuickStart/QuickStart.md
+++ b/src/UserGuide/Master/QuickStart/QuickStart.md
@@ -73,7 +73,7 @@ Users can start IoTDB standalone mode by the start-standalone
script under the s
```
Note: Currently, To run standalone mode, you need to ensure that all addresses
are set to 127.0.0.1, If you need to access the IoTDB from a machine different
from the one where the IoTDB is located, please change the configuration item
`dn_rpc_address` to the IP of the machine where the IoTDB lives. And
replication factors set to 1, which is by now the default setting.
-Besides, it's recommended to use SimpleConsensus in this mode, since it brings
additional efficiency.
+Besides, it's recommended to use IoTConsensus in this mode, since it brings
additional efficiency.
### Use Cli
IoTDB offers different ways to interact with server, here we introduce basic
steps of using Cli tool to insert and query data.
@@ -237,6 +237,6 @@ More about administration management：[Administration
Management](https://iotdb
The configuration files is in the `conf` folder, includes:
-* environment configuration (`datanode-env.bat`, `datanode-env.sh`),
-* system configuration (`iotdb-datanode.properties`)
+* environment configuration (`datanode-env.bat`,
`datanode-env.sh`,`confignode-env.bat`,`confignode-env.sh`),
+* system configuration
(`iotdb-datanode.properties`,`iotdb-common.properties`,`iotdb-confingnode.properties`,`iotdb-datanode.properties`,`iotdb-cluster.properties`)
* log configuration (`logback.xml`).
diff --git a/src/UserGuide/latest/API/Programming-Python-Native-API.md
b/src/UserGuide/latest/API/Programming-Python-Native-API.md
index 4905cf0..b17d73e 100644
--- a/src/UserGuide/latest/API/Programming-Python-Native-API.md
+++ b/src/UserGuide/latest/API/Programming-Python-Native-API.md
@@ -31,9 +31,9 @@ You have to install thrift (>=0.13) before using the package.
First, download the package: `pip3 install apache-iotdb`
-You can get an example of using the package to read and write data at here:
[Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)
+You can get an example of using the package to read and write data at here:
[Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionExample.py)
-An example of aligned timeseries: [Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)
+An example of aligned timeseries: [Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionAlignedTimeseriesExample.py)
(you need to add `import iotdb` in the head of the file)
diff --git a/src/UserGuide/latest/QuickStart/ClusterQuickStart.md
b/src/UserGuide/latest/QuickStart/ClusterQuickStart.md
index 601ff2f..da39027 100644
--- a/src/UserGuide/latest/QuickStart/ClusterQuickStart.md
+++ b/src/UserGuide/latest/QuickStart/ClusterQuickStart.md
@@ -240,7 +240,7 @@ cd /data/iotdb
sbin/remove-datanode.sh 192.168.132.13:6667
# way 2: shrink with NodeID of `show cluster`
-sbin/remove-confignode.sh 7
+sbin/remove-datanode.sh 7
```
### 3.3 check the result
diff --git a/src/UserGuide/latest/QuickStart/QuickStart.md
b/src/UserGuide/latest/QuickStart/QuickStart.md
index 4d74ab7..fea9f0e 100644
--- a/src/UserGuide/latest/QuickStart/QuickStart.md
+++ b/src/UserGuide/latest/QuickStart/QuickStart.md
@@ -73,7 +73,7 @@ Users can start IoTDB standalone mode by the start-standalone
script under the s
```
Note: Currently, To run standalone mode, you need to ensure that all addresses
are set to 127.0.0.1, If you need to access the IoTDB from a machine different
from the one where the IoTDB is located, please change the configuration item
`dn_rpc_address` to the IP of the machine where the IoTDB lives. And
replication factors set to 1, which is by now the default setting.
-Besides, it's recommended to use SimpleConsensus in this mode, since it brings
additional efficiency.
+Besides, it's recommended to use IoTConsensus in this mode, since it brings
additional efficiency.
### Use Cli
IoTDB offers different ways to interact with server, here we introduce basic
steps of using Cli tool to insert and query data.
@@ -237,6 +237,6 @@ More about administration management：[Administration
Management](https://iotdb
The configuration files is in the `conf` folder, includes:
-* environment configuration (`datanode-env.bat`, `datanode-env.sh`),
-* system configuration (`iotdb-datanode.properties`)
+* environment configuration (`datanode-env.bat`,
`datanode-env.sh`,`confignode-env.bat`,`confignode-env.sh`),
+* system configuration
(`iotdb-datanode.properties`,`iotdb-common.properties`,`iotdb-confingnode.properties`,`iotdb-datanode.properties`,`iotdb-cluster.properties`)
* log configuration (`logback.xml`).
diff --git a/src/zh/UserGuide/Master/API/Programming-Python-Native-API.md
b/src/zh/UserGuide/Master/API/Programming-Python-Native-API.md
index 54305b6..c9f6183 100644
--- a/src/zh/UserGuide/Master/API/Programming-Python-Native-API.md
+++ b/src/zh/UserGuide/Master/API/Programming-Python-Native-API.md
@@ -29,9 +29,9 @@
首先下载包：`pip3 install apache-iotdb`
-您可以从这里得到一个使用该包进行数据读写的例子：[Session
Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)
+您可以从这里得到一个使用该包进行数据读写的例子：[Session
Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionExample.py)
-关于对齐时间序列读写的例子：[Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)
+关于对齐时间序列读写的例子：[Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionAlignedTimeseriesExample.py)
（您需要在文件的头部添加`import iotdb`）
diff --git a/src/zh/UserGuide/Master/IoTDB-Introduction/Scenario.md
b/src/zh/UserGuide/Master/IoTDB-Introduction/Scenario.md
index 3fad46c..ae104b0 100644
--- a/src/zh/UserGuide/Master/IoTDB-Introduction/Scenario.md
+++ b/src/zh/UserGuide/Master/IoTDB-Introduction/Scenario.md
@@ -86,7 +86,7 @@
某电厂需要对风机锅炉设备、发电机、变电设备等主辅机数万测点进行监控。在以往的供暖供热过程中缺少对于下一阶段的供热量的预判，导致无效供热、过度供热、供热不足等情况。
-使用IoTDB作为存储与分析引擎后，结合气象数据、楼控数据、户控数据、换热站数据、官网数据、热源侧数据等总和评判供热量，所有数据在IoTDB中进行时间对齐，为智慧供热提供可靠的数据依据，实现智慧供热。同时也解决了按需计费、管网、热战等相关供热过程中各重要组成部分的工况监控，减少了人力投入。
+使用IoTDB作为存储与分析引擎后，结合气象数据、楼控数据、户控数据、换热站数据、官网数据、热源侧数据等总和评判供热量，所有数据在IoTDB中进行时间对齐，为智慧供热提供可靠的数据依据，实现智慧供热。同时也解决了按需计费、管网、热站等相关供热过程中各重要组成部分的工况监控，减少了人力投入。
### 架构
diff --git a/src/zh/UserGuide/Master/QuickStart/ClusterQuickStart.md
b/src/zh/UserGuide/Master/QuickStart/ClusterQuickStart.md
index d7dfa5d..af858d9 100644
--- a/src/zh/UserGuide/Master/QuickStart/ClusterQuickStart.md
+++ b/src/zh/UserGuide/Master/QuickStart/ClusterQuickStart.md
@@ -147,7 +147,7 @@ sbin/stop-standalone.sh
# 2. 检查是否还有进程残留
jps
# 或者
-ps -ef|gerp iotdb
+ps -ef|grep iotdb
# 3. 如果有进程残留，则手动kill
kill -9 <pid>
@@ -234,7 +234,7 @@ cd /data/iotdb
sbin/remove-datanode.sh 192.168.132.13:6667
# 方式二：使用节点编号移除, `show cluster`中的 NodeID
-sbin/remove-confignode.sh 7
+sbin/remove-datanode.sh 7
```
### 3.3 验证缩容结果
diff --git a/src/zh/UserGuide/Master/QuickStart/QuickStart.md
b/src/zh/UserGuide/Master/QuickStart/QuickStart.md
index 6e6c385..553aa7f 100644
--- a/src/zh/UserGuide/Master/QuickStart/QuickStart.md
+++ b/src/zh/UserGuide/Master/QuickStart/QuickStart.md
@@ -67,7 +67,7 @@ Windows 系统启动命令如下：
> sbin\start-standalone.bat
```
-注意：目前，要使用单机模式，你需要保证所有的地址设置为 127.0.0.1，如果需要从非 IoTDB 所在的机器访问此IoTDB，请将配置项
`dn_rpc_address` 修改为 IoTDB 所在的机器 IP。副本数设置为1。并且，推荐使用
SimpleConsensus，因为这会带来额外的效率。这些现在都是默认配置。
+注意：目前，要使用单机模式，你需要保证所有的地址设置为 127.0.0.1，如果需要从非 IoTDB 所在的机器访问此IoTDB，请将配置项
`dn_rpc_address` 修改为 IoTDB 所在的机器 IP。副本数设置为1。并且，推荐使用
IoTConsensus，因为这会带来额外的效率。这些现在都是默认配置。
### 使用 Cli 工具
@@ -268,6 +268,6 @@ Example: IoTDB > ALTER USER root SET PASSWORD 'newpwd';
配置文件在"conf"文件夹下，包括：
- * 环境配置模块 (`datanode-env.bat`, `datanode-env.sh`),
- * 系统配置模块 (`iotdb-datanode.properties`)
+ * 环境配置模块 (`datanode-env.bat`,
`datanode-env.sh`,`confignode-env.bat`,`confignode-env.sh`),
+ * 系统配置模块
(`iotdb-datanode.properties`,`iotdb-common.properties`,`iotdb-confingnode.properties`,`iotdb-datanode.properties`,`iotdb-cluster.properties`)
* 日志配置模块 (`logback.xml`).
diff --git a/src/zh/UserGuide/latest/API/Programming-Python-Native-API.md
b/src/zh/UserGuide/latest/API/Programming-Python-Native-API.md
index 54305b6..c9f6183 100644
--- a/src/zh/UserGuide/latest/API/Programming-Python-Native-API.md
+++ b/src/zh/UserGuide/latest/API/Programming-Python-Native-API.md
@@ -29,9 +29,9 @@
首先下载包：`pip3 install apache-iotdb`
-您可以从这里得到一个使用该包进行数据读写的例子：[Session
Example](https://github.com/apache/iotdb/blob/master/client-py/SessionExample.py)
+您可以从这里得到一个使用该包进行数据读写的例子：[Session
Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionExample.py)
-关于对齐时间序列读写的例子：[Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/client-py/SessionAlignedTimeseriesExample.py)
+关于对齐时间序列读写的例子：[Aligned Timeseries Session
Example](https://github.com/apache/iotdb/blob/master/iotdb-client/client-py/SessionAlignedTimeseriesExample.py)
（您需要在文件的头部添加`import iotdb`）
diff --git a/src/zh/UserGuide/latest/IoTDB-Introduction/Scenario.md
b/src/zh/UserGuide/latest/IoTDB-Introduction/Scenario.md
index 3fad46c..ae104b0 100644
--- a/src/zh/UserGuide/latest/IoTDB-Introduction/Scenario.md
+++ b/src/zh/UserGuide/latest/IoTDB-Introduction/Scenario.md
@@ -86,7 +86,7 @@
某电厂需要对风机锅炉设备、发电机、变电设备等主辅机数万测点进行监控。在以往的供暖供热过程中缺少对于下一阶段的供热量的预判，导致无效供热、过度供热、供热不足等情况。
-使用IoTDB作为存储与分析引擎后，结合气象数据、楼控数据、户控数据、换热站数据、官网数据、热源侧数据等总和评判供热量，所有数据在IoTDB中进行时间对齐，为智慧供热提供可靠的数据依据，实现智慧供热。同时也解决了按需计费、管网、热战等相关供热过程中各重要组成部分的工况监控，减少了人力投入。
+使用IoTDB作为存储与分析引擎后，结合气象数据、楼控数据、户控数据、换热站数据、官网数据、热源侧数据等总和评判供热量，所有数据在IoTDB中进行时间对齐，为智慧供热提供可靠的数据依据，实现智慧供热。同时也解决了按需计费、管网、热站等相关供热过程中各重要组成部分的工况监控，减少了人力投入。
### 架构
diff --git a/src/zh/UserGuide/latest/QuickStart/ClusterQuickStart.md
b/src/zh/UserGuide/latest/QuickStart/ClusterQuickStart.md
index d7dfa5d..af858d9 100644
--- a/src/zh/UserGuide/latest/QuickStart/ClusterQuickStart.md
+++ b/src/zh/UserGuide/latest/QuickStart/ClusterQuickStart.md
@@ -147,7 +147,7 @@ sbin/stop-standalone.sh
# 2. 检查是否还有进程残留
jps
# 或者
-ps -ef|gerp iotdb
+ps -ef|grep iotdb
# 3. 如果有进程残留，则手动kill
kill -9 <pid>
@@ -234,7 +234,7 @@ cd /data/iotdb
sbin/remove-datanode.sh 192.168.132.13:6667
# 方式二：使用节点编号移除, `show cluster`中的 NodeID
-sbin/remove-confignode.sh 7
+sbin/remove-datanode.sh 7
```
### 3.3 验证缩容结果
diff --git a/src/zh/UserGuide/latest/QuickStart/QuickStart.md
b/src/zh/UserGuide/latest/QuickStart/QuickStart.md
index 6e6c385..85eb9f9 100644
--- a/src/zh/UserGuide/latest/QuickStart/QuickStart.md
+++ b/src/zh/UserGuide/latest/QuickStart/QuickStart.md
@@ -67,7 +67,7 @@ Windows 系统启动命令如下：
> sbin\start-standalone.bat
```
-注意：目前，要使用单机模式，你需要保证所有的地址设置为 127.0.0.1，如果需要从非 IoTDB 所在的机器访问此IoTDB，请将配置项
`dn_rpc_address` 修改为 IoTDB 所在的机器 IP。副本数设置为1。并且，推荐使用
SimpleConsensus，因为这会带来额外的效率。这些现在都是默认配置。
+注意：目前，要使用单机模式，你需要保证所有的地址设置为 127.0.0.1，如果需要从非 IoTDB 所在的机器访问此IoTDB，请将配置项
`dn_rpc_address` 修改为 IoTDB 所在的机器 IP。副本数设置为1。并且，推荐使用
IoTConsensus，因为这会带来额外的效率。这些现在都是默认配置。
### 使用 Cli 工具
@@ -268,6 +268,6 @@ Example: IoTDB > ALTER USER root SET PASSWORD 'newpwd';
配置文件在"conf"文件夹下，包括：
- * 环境配置模块 (`datanode-env.bat`, `datanode-env.sh`),
- * 系统配置模块 (`iotdb-datanode.properties`)
- * 日志配置模块 (`logback.xml`).
+ * 环境配置模块 (`datanode-env.bat`,
`datanode-env.sh`,`confignode-env.bat`,`confignode-env.sh`),
+ * 系统配置模块
(`iotdb-datanode.properties`,`iotdb-common.properties`,`iotdb-confingnode.properties`,`iotdb-datanode.properties`,`iotdb-cluster.properties`)
+ * 日志配置模块 (`logback.xml`).
\ No newline at end of file
