SparkAzureTable

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1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. final def asInstanceOf[T0]: T0

   

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5. def azureWriterOutputLabel(label: String): String

   

6. def clone(): AnyRef

   

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7. def createIfNotExists(connectionSTR: String, tableName: String): Boolean

   

   Creates azure table if it does not exist.

   Creates azure table if it does not exist.

   connectionSTR

   connection string to Azure storage account

   tableName

   name of the azure table

   returns

   true if table was created, false if it exists

   Exceptions thrown

   StorageException : if table can not be created or other

8. final def eq(arg0: AnyRef): Boolean

   

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9. def equals(arg0: Any): Boolean

   

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10. def finalize(): Unit

    

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11. final def getClass(): Class[_]

    

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12. def hashCode(): Int

    

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13. final def isInstanceOf[T0]: Boolean

    

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14. def isTraceEnabled(): Boolean

    

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15. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    

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16. def logDebug(msg: ⇒ String): Unit

    

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17. def logError(msg: ⇒ String, throwable: Throwable): Unit

    

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18. def logError(msg: ⇒ String): Unit

    

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19. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    

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20. def logInfo(msg: ⇒ String): Unit

    

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21. def logName: String

    

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22. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    

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23. def logTrace(msg: ⇒ String): Unit

    

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24. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    

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25. def logWarning(msg: ⇒ String): Unit

    

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26. final def ne(arg0: AnyRef): Boolean

    

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27. final def notify(): Unit

    

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28. final def notifyAll(): Unit

    

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29. def pushToTable(inputDS: Dataset[_], connectionSTR: String, tableName: String, threadNum: Int, timeoutMs: Long, retryDelayMs: Seq[Long]): Unit

    

    Pushes dataset records into Azure Table, it will spawn multiple parallel push threads from each executor.

    Pushes dataset records into Azure Table, it will spawn multiple parallel push threads from each executor. Each push thread will try to use Azure Table batch operations with insertOrReplace, for best performance the inputDS needs to be already partitioned by '_partition' columns and sorted within partition by '_partition' and '_id' columns.

    inputDS

    input dataset

    connectionSTR

    connection string to Azure storage account

    tableName

    name of the azure table to push into

    threadNum

    number of threads to push with from each executor. Default is 50.

    timeoutMs

    timeout in milliseconds for an Azure Table operation

    retryDelayMs

    delay in milliseconds to wait between successive retries of an Azure Table operation in case of failure or timeout. Number of elements in the sequence indicates how number of retries for the operation.

30. final def synchronized[T0](arg0: ⇒ T0): T0

    

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31. def toString(): String

    

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32. final def wait(): Unit

    

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33. final def wait(arg0: Long, arg1: Int): Unit

    

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34. final def wait(arg0: Long): Unit

    

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