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DataX | DataX 是阿里巴巴集团内被广泛使用的离线数据同步工具

 by   alibaba Java Version: Current License: Non-SPDX

 by   alibaba Java Version: Current License: Non-SPDX

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kandi X-RAY | DataX Summary

DataX is a Java library typically used in Big Data, Hadoop, Oracle applications. DataX has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However DataX has a Non-SPDX License. You can download it from GitHub.
DataX 是阿里云 DataWorks数据集成 的开源版本,在阿里巴巴集团内被广泛使用的离线数据同步工具/平台。DataX 实现了包括 MySQL、Oracle、OceanBase、SqlServer、Postgre、HDFS、Hive、ADS、HBase、TableStore(OTS)、MaxCompute(ODPS)、Hologres、DRDS 等各种异构数据源之间高效的数据同步功能。.
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Support
Quality
Quality
Security
Security
License
License
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kandi-support Support

  • DataX has a medium active ecosystem.
  • It has 10885 star(s) with 4001 fork(s). There are 432 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 800 open issues and 169 have been closed. On average issues are closed in 108 days. There are 153 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of DataX is current.
DataX Support
Best in #Java
Average in #Java
DataX Support
Best in #Java
Average in #Java

quality kandi Quality

  • DataX has 0 bugs and 0 code smells.
DataX Quality
Best in #Java
Average in #Java
DataX Quality
Best in #Java
Average in #Java

securitySecurity

  • DataX has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • DataX code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
DataX Security
Best in #Java
Average in #Java
DataX Security
Best in #Java
Average in #Java

license License

  • DataX has a Non-SPDX License.
  • Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
DataX License
Best in #Java
Average in #Java
DataX License
Best in #Java
Average in #Java

buildReuse

  • DataX releases are not available. You will need to build from source code and install.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
DataX Reuse
Best in #Java
Average in #Java
DataX Reuse
Best in #Java
Average in #Java
Top functions reviewed by kandi - BETA

kandi has reviewed DataX and discovered the below as its top functions. This is intended to give you an instant insight into DataX implemented functionality, and help decide if they suit your requirements.

  • Build a single record from a Row
  • Read input stream
  • Create a mapping rule .
  • Get table info .
  • Transport one record from another ResultSet
  • Loads stream reader configuration .
  • Splits a collection .
  • Parse a JSON value from a Java object
  • Generate SQL for split .
  • Set column .

DataX Key Features

DataX是阿里云DataWorks数据集成的开源版本。

开源版DataX企业用户

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长期招聘 联系邮箱:datax@alibabacloud.com
【JAVA开发职位】
职位名称:JAVA资深开发工程师/专家/高级专家
工作年限 : 2年以上
学历要求 : 本科(如果能力靠谱,这些都不是条件)
期望层级 : P6/P7/P8

岗位描述:
    1. 负责阿里云大数据平台(数加)的开发设计。 
    2. 负责面向政企客户的大数据相关产品开发;
    3. 利用大规模机器学习算法挖掘数据之间的联系,探索数据挖掘技术在实际场景中的产品应用 ;
    4. 一站式大数据开发平台
    5. 大数据任务调度引擎
    6. 任务执行引擎
    7. 任务监控告警
    8. 海量异构数据同步

岗位要求:
    1. 拥有3年以上JAVA Web开发经验;
    2. 熟悉Java的基础技术体系。包括JVM、类装载、线程、并发、IO资源管理、网络;
    3. 熟练使用常用Java技术框架、对新技术框架有敏锐感知能力;深刻理解面向对象、设计原则、封装抽象;
    4. 熟悉HTML/HTML5和JavaScript;熟悉SQL语言;
    5. 执行力强,具有优秀的团队合作精神、敬业精神;
    6. 深刻理解设计模式及应用场景者加分;
    7. 具有较强的问题分析和处理能力、比较强的动手能力,对技术有强烈追求者优先考虑;
    8. 对高并发、高稳定可用性、高性能、大数据处理有过实际项目及产品经验者优先考虑;
    9. 有大数据产品、云产品、中间件技术解决方案者优先考虑。

Python Pandas - Vlookup - Update Existing Column in First Data Frame From Second Data Frame

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df1['info'] = pd.merge(df1[['key','info']], df2[['key','info']], on='key', how='left')['info_y']
print(df1)
  dataA  dataB  key   info dataC
0   ABC    123  a1b  infoA   aaa
1   DEF    456  b57    NaN   bbb
2   GHI    789  a22  infoC   ccc
-----------------------
df1['info'] = pd.merge(df1[['key','info']], df2[['key','info']], on='key', how='left')['info_y']
print(df1)
  dataA  dataB  key   info dataC
0   ABC    123  a1b  infoA   aaa
1   DEF    456  b57    NaN   bbb
2   GHI    789  a22  infoC   ccc

Azure Data Factory copy data from json string nested in a json

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SELECT JSON_VALUE('{"dataX": [1,2,3,4]}', '$.dataX') AS 'Output';
-----------------------
CREATE OR ALTER PROCEDURE dataset_outputs_from_adf
    @json_output_value NVARCHAR(MAX),
    @output_name NVARCHAR(100)
AS
    DECLARE @i INT = 0
    WHILE JSON_VALUE(@json_output_value,CONCAT('$.dataX[',@i,']')) IS NOT NULL
    BEGIN
        INSERT INTO my_table
        VALUES (
            @output_name,
            JSON_VALUE(
                @json_output_value,
                CONCAT('$.dataX[',@i,']')
            ),
            JSON_VALUE(
                @json_output_value,
                CONCAT('$.dataY[',@i,']')
            )
        )
        SET @i = @i + 1
    END
GO
-----------------------
@json(variables('payload')).dataX
@string(json(variables('payload')).dataX)
create procedure dbo.HandleData
  @dataX varchar(4000),
  @dataY varchar(4000)
as

insert dbo.SomeTable(ColumnX, ColumnY)
select x.value, y.value
from OPENJSON(@dataX) x
inner join OPENJSON(@dataY) y
    on y.[key] = x.[key];
-----------------------
@json(variables('payload')).dataX
@string(json(variables('payload')).dataX)
create procedure dbo.HandleData
  @dataX varchar(4000),
  @dataY varchar(4000)
as

insert dbo.SomeTable(ColumnX, ColumnY)
select x.value, y.value
from OPENJSON(@dataX) x
inner join OPENJSON(@dataY) y
    on y.[key] = x.[key];
-----------------------
@json(variables('payload')).dataX
@string(json(variables('payload')).dataX)
create procedure dbo.HandleData
  @dataX varchar(4000),
  @dataY varchar(4000)
as

insert dbo.SomeTable(ColumnX, ColumnY)
select x.value, y.value
from OPENJSON(@dataX) x
inner join OPENJSON(@dataY) y
    on y.[key] = x.[key];

Why Django form.save() returns object(None)?

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class Chart(models.Model):
    id = models.AutoField(primary_key=True)
    type = models.CharField(max_length=10)
    chartname = models.CharField(max_length=20, null=True)
class Chart(models.Model):
    type = models.CharField(max_length=10)
    chartname = models.CharField(max_length=20, null=True)
-----------------------
class Chart(models.Model):
    id = models.AutoField(primary_key=True)
    type = models.CharField(max_length=10)
    chartname = models.CharField(max_length=20, null=True)
class Chart(models.Model):
    type = models.CharField(max_length=10)
    chartname = models.CharField(max_length=20, null=True)

Chart.JS Starting at 00:00am and ending at 23:59pm

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const chart = new Chart('chartJSContainer', {
  type: "line",
  data: {
    labels: [
      new Date(1634847780000), // Last of previous day - Low Tide
      new Date(1634869320000), // High Tide 1
      new Date(1634891880000), // Low Tide 1
      new Date(1634913060000), // High Tide 2
      new Date(1634935560000), // Low Tide 2
      new Date(1634955720000), // First of next day - High Tide
    ],
    datasets: [{
      label: "My First dataset",
      data: [0.7, 5.8, 0.8, 5.8, 0.8, 5.1], // Meters above sea
      tension: 0.5,
      backgroundColor: "#000000",
      fill: {
        target: "origin",
      },
    }, ],
  },
  options: {
    interaction: {
      mode: "point",
    },
    hover: {
      mode: "point",
    },
    onHover: (e) => {
      const canvasPosition = getRelativePosition(e, chart);

      // Substitute the appropriate scale IDs
      const dataX = chart.scales.x.getValueForPixel(canvasPosition.x);
      const dataY = chart.scales.y.getValueForPixel(canvasPosition.y);
      console.log(dataY);
    },
    plugins: {
      tooltip: {
        enabled: true,
      },
      legend: {
        display: false,
      },
    },
    scales: {
      xAxis: {
        type: "time",
        min: new Date(1634853600000), // Should calculate this dynamic, not best way but can use: new Date().setHours(0,0,0,0)
        max: new Date(1634939999000), // Should calculate this dynamic, not best way but can use: new Date().setHours(23,59,59)
        time: {
          unit: "hour",
          displayFormats: {
            hour: "HH:mm",
          },

          // minUnit: moment(1634860800000).format("HH:mm"),
        },
      },
      yAxis: {
        ticks: {
          callback: function(value, index, values) {
            return value + "m";
          },
        },
      },
    },
  },
});
<body>
  <canvas id="chartJSContainer" width="600" height="400"></canvas>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/3.5.1/chart.js"></script>
  <script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns/dist/chartjs-adapter-date-fns.bundle.min.js"></script>
</body>
-----------------------
const chart = new Chart('chartJSContainer', {
  type: "line",
  data: {
    labels: [
      new Date(1634847780000), // Last of previous day - Low Tide
      new Date(1634869320000), // High Tide 1
      new Date(1634891880000), // Low Tide 1
      new Date(1634913060000), // High Tide 2
      new Date(1634935560000), // Low Tide 2
      new Date(1634955720000), // First of next day - High Tide
    ],
    datasets: [{
      label: "My First dataset",
      data: [0.7, 5.8, 0.8, 5.8, 0.8, 5.1], // Meters above sea
      tension: 0.5,
      backgroundColor: "#000000",
      fill: {
        target: "origin",
      },
    }, ],
  },
  options: {
    interaction: {
      mode: "point",
    },
    hover: {
      mode: "point",
    },
    onHover: (e) => {
      const canvasPosition = getRelativePosition(e, chart);

      // Substitute the appropriate scale IDs
      const dataX = chart.scales.x.getValueForPixel(canvasPosition.x);
      const dataY = chart.scales.y.getValueForPixel(canvasPosition.y);
      console.log(dataY);
    },
    plugins: {
      tooltip: {
        enabled: true,
      },
      legend: {
        display: false,
      },
    },
    scales: {
      xAxis: {
        type: "time",
        min: new Date(1634853600000), // Should calculate this dynamic, not best way but can use: new Date().setHours(0,0,0,0)
        max: new Date(1634939999000), // Should calculate this dynamic, not best way but can use: new Date().setHours(23,59,59)
        time: {
          unit: "hour",
          displayFormats: {
            hour: "HH:mm",
          },

          // minUnit: moment(1634860800000).format("HH:mm"),
        },
      },
      yAxis: {
        ticks: {
          callback: function(value, index, values) {
            return value + "m";
          },
        },
      },
    },
  },
});
<body>
  <canvas id="chartJSContainer" width="600" height="400"></canvas>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/3.5.1/chart.js"></script>
  <script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns/dist/chartjs-adapter-date-fns.bundle.min.js"></script>
</body>

How do I get data as JSON format from the IBM Cloud with a HTTP Request using JavaScript?

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var xhr = new XMLHttpRequest();
xhr.open( "GET", "https://<orgID>...");
xhr.setRequestHeader("Authorization", `Basic ${btoa('username:password')}`);    
xhr.send();

How to fix Memory Error while training model?

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model = Sequential(
    [
        #Conv1D(32, 3, input_shape=datax.shape, activation="relu"),
        Flatten(input_shape=datax.shape),
        Dense(750, activation='relu'),
        Dropout(0.2),
        Dense(750, activation='relu'),
        Dropout(0.2),
        Dense(2, activation='sigmoid')
    ]

Rust: TCP Stream read POST file not works well in Edge or Chrome browsers

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        if n<1024 {
            datax.extend_from_slice(&el_buffer[..n]);
            break;
        } else {
-----------------------
[dependencies]  
buf_redux = "0.8.4"
    use buf_redux::BufReader;

    // ....

    let mut datax = Vec::new();
    let mut el_buffer = [0; 4096];
    
    // A 10 MBytes aprox.:
    let mut lector = BufReader::with_capacity(10240000, &mut stream);

    loop {
        let n = lector.read(&mut el_buffer).unwrap();
        println!("Bytes : {:?}", n);
        if n<4096 {
            datax.extend_from_slice(&el_buffer[..n]);
            break;
        } else {
            datax.extend_from_slice(&el_buffer[..n]);
        }
    }

-----------------------
[dependencies]  
buf_redux = "0.8.4"
    use buf_redux::BufReader;

    // ....

    let mut datax = Vec::new();
    let mut el_buffer = [0; 4096];
    
    // A 10 MBytes aprox.:
    let mut lector = BufReader::with_capacity(10240000, &mut stream);

    loop {
        let n = lector.read(&mut el_buffer).unwrap();
        println!("Bytes : {:?}", n);
        if n<4096 {
            datax.extend_from_slice(&el_buffer[..n]);
            break;
        } else {
            datax.extend_from_slice(&el_buffer[..n]);
        }
    }

Problem with dimensionality in Keras RNN - reshape isn't working?

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subdata = dataset[i:len(dataset) - lags + i]

# with lags = 1 you have just one
# iteration in range(1): i = 0
subdata = dataset[0:50 - 1 + 0]
subdata = dataset[0:49] # which is a 1x49 vector

# In order to create the right vector
# you need to change your function:

def create_dataset(dataset, lags = 1):
    dataX, dataY = [], []
    # iterate to a max of (50 - lags - 1) times
    # because we need "lags" element in each vector
    for i in range(len(dataset) - lags - 1):
        # get "lags" elements from the dataset
        subdata = dataset[i:i + lags]
        dataX.append(subdata)
        # get only the last label representing
        # the current element iteration
        dataY.append(dataset[i + lags])
    return np.array(dataX), np.array(dataY)
model.add(SimpleRNN(1, input_shape=(1, 1)))

# you should use lags in the input shape
model.add(SimpleRNN(1, input_shape=(1, LAGS)))
-----------------------
subdata = dataset[i:len(dataset) - lags + i]

# with lags = 1 you have just one
# iteration in range(1): i = 0
subdata = dataset[0:50 - 1 + 0]
subdata = dataset[0:49] # which is a 1x49 vector

# In order to create the right vector
# you need to change your function:

def create_dataset(dataset, lags = 1):
    dataX, dataY = [], []
    # iterate to a max of (50 - lags - 1) times
    # because we need "lags" element in each vector
    for i in range(len(dataset) - lags - 1):
        # get "lags" elements from the dataset
        subdata = dataset[i:i + lags]
        dataX.append(subdata)
        # get only the last label representing
        # the current element iteration
        dataY.append(dataset[i + lags])
    return np.array(dataX), np.array(dataY)
model.add(SimpleRNN(1, input_shape=(1, 1)))

# you should use lags in the input shape
model.add(SimpleRNN(1, input_shape=(1, LAGS)))

Why is the inferred type like this ?

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const test3 = Component({
    properties: { propA: '' },
    data: (prop: { propA: string }) => { return { dataA: '' } },
    computed: {
        ccc(AllData) {                      
            return AllData.propA
        }
    }
})

Saving with SQL

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energyX.Add(XX);

Community Discussions

Trending Discussions on DataX
  • /bin/sh: 1 : conda: not found error when executing a conda run command through a nodejs script using pm2
  • Python Pandas - Vlookup - Update Existing Column in First Data Frame From Second Data Frame
  • Azure Data Factory copy data from json string nested in a json
  • How to fix &quot;Boolean value of Tensor with more than one value is ambiguous&quot;?
  • Why Django form.save() returns object(None)?
  • Chart.JS Starting at 00:00am and ending at 23:59pm
  • Using Swift with URLSession works with GET and PUT, but it gives error 405 Method Not Allowed when I use POST
  • How do I get data as JSON format from the IBM Cloud with a HTTP Request using JavaScript?
  • How to apply one label to a NumPy dimension for a Keras Neural Network?
  • How to fix Memory Error while training model?
Trending Discussions on DataX

QUESTION

/bin/sh: 1 : conda: not found error when executing a conda run command through a nodejs script using pm2

Asked 2022-Apr-02 at 22:03

Introduction

I am running a nodejs server in the production environment using pm2. The javascript file a python script upon a prompt using the conda run method. This command errors out with the following message: /bin/sh: 1: conda: not found. However, running the same js file using npx nodemon or simply node works well without any errors.

Detailed Description

The javascript file is as follows

...
command = "conda run -n p2vois python  path_to_python_script_file.py "+variable_with_arguments_for_the_python_script;
...
var pyProcess = cmd.get(command,
                (err, datax, stderr)=> {
                        console.log("here datax: %s", datax)
                        if(err){
                            console.log("python script cmd error: " + err)
                        }
                        else{
                            ...
                        }

This code upon running using the sudo pm2 start server.js command gives an error as follows:

python script cmd error: Error: Command failed: conda run -n p2vois python path_to_python_script_file.py arguments_for_the_python_script
/bin/sh: 1: conda: not found

However, running the same javascript file server.js with npx nodemon or node does not give any error.

Possible causes of error

I believe the cause should be conda trying to run the command through /bin/sh instead of /bin/bash. Another reason could be an underlying path issue while running with pm2. I do not know how to fix this error, so any help would be appreciated.

ANSWER

Answered 2022-Apr-02 at 19:42

Solution

Just removed the sudo privilege for the pm2 command and the code started working again.

Source https://stackoverflow.com/questions/71692744

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install DataX

You can download it from GitHub.
You can use DataX like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the DataX component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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