Tablestore:Write data

Prerequisites

• The OTSClient instance is initialized. For more information, see Initialize an OTSClient instance.
• A data table is created. Data is written to the table.

Write a single row of data

You can call the PutRow operation to write a row of data. If the row exists, Tablestore deletes all versions of data in all columns from the existing row and writes new data.

API operation

// @param PutRowRequest    Encapsulate the parameters required to call the PutRow operation. 
// @return PutRowResponse
PutRow(request *PutRowRequest) (*PutRowResponse, error)                    

Parameters

Examples

The following sample code provides an example on how to write a single row of data:

putRowRequest := new(tablestore.PutRowRequest)
putRowChange := new(tablestore.PutRowChange)
putRowChange.TableName = tableName
putPk := new(tablestore.PrimaryKey)
putPk.AddPrimaryKeyColumn("pk1", "pk1value1")
putPk.AddPrimaryKeyColumn("pk2", int64(2))
putPk.AddPrimaryKeyColumn("pk3", []byte("pk3"))
putRowChange.PrimaryKey = putPk
putRowChange.AddColumn("col1", "col1data1")
putRowChange.AddColumn("col2", int64(3))
putRowChange.AddColumn("col3", []byte("test"))
putRowChange.SetCondition(tablestore.RowExistenceExpectation_IGNORE)
putRowRequest.PutRowChange = putRowChange
_, err := client.PutRow(putRowRequest)

if err != nil {
    fmt.Println("putrow failed with error:", err)
} else {
    fmt.Println("putrow finished")
 }                    

To view the detailed sample code, visit PutRow@GitHub.

Update a single row of data

API operation

// Update a row of data in the table. 
// @param UpdateRowRequest      Encapsulate the parameters required to call the UpdateRow operation. 
// @return UpdateRowResponse    The content of the response to the UpdateRow operation. 
UpdateRow(request *UpdateRowRequest) (*UpdateRowResponse, error)                    

Parameters

Examples

The following sample code provides an example on how to update a single row of data:

updateRowRequest := new(tablestore.UpdateRowRequest)
updateRowChange := new(tablestore.UpdateRowChange)
updateRowChange.TableName = tableName
updatePk := new(tablestore.PrimaryKey)
updatePk.AddPrimaryKeyColumn("pk1", "pk1value1")
updatePk.AddPrimaryKeyColumn("pk2", int64(2))
updatePk.AddPrimaryKeyColumn("pk3", []byte("pk3"))
updateRowChange.PrimaryKey = updatePk
updateRowChange.DeleteColumn("col1")
updateRowChange.PutColumn("col2", int64(77))
updateRowChange.PutColumn("col4", "newcol3")
updateRowChange.SetCondition(tablestore.RowExistenceExpectation_EXPECT_EXIST)
updateRowRequest.UpdateRowChange = updateRowChange
_, err := client.UpdateRow(updateRowRequest)

if err != nil {
    fmt.Println("update failed with error:", err)
} else {
    fmt.Println("update row finished")
}                    

To view the detailed sample code, visit UpdateRow@GitHub.

Write multiple rows of data at the same time

You can call the BatchWriteRow operation to write multiple rows of data to one or more tables at a time.

The BatchWriteRow operation consists of multiple PutRow, UpdateRow, and DeleteRow operations. When you call the BatchWriteRow operation, the process of constructing a suboperation is the same as the process of calling the PutRow, UpdateRow, or DeleteRow operation.

When you call the BatchWriteRow operation, each PutRow, UpdateRow, or DeleteRow operation is separately performed and the response to each operation is separately returned by Tablestore.

Usage notes

• When you call the BatchWriteRow operation to write multiple rows of data at the same time, some rows may fail to be written. In this case, Tablestore does not return exceptions. Tablestore returns BatchWriteRowResponse in which the indexes and error messages of the failed rows are included. Therefore, when you call the BatchWriteRow operation, make sure to check the return values to determine whether all rows are written. If you do not check the return values, the rows that fail to be written may be ignored.

  If the server detects that invalid parameters exist in some operations, an error message may return before the operations of the request are performed.

• You can call the BatchWriteRow operation to write up to 4 MB of data in up to 200 rows at the same time.

API operation

// Add, delete, or update multiple rows of data in multiple tables. 
// @param BatchWriteRowRequest             Encapsulate the parameters required to call the BatchWriteRow operation. 
// @return  BatchWriteRowResponse          The content of the response to the BatchWriteRow operation. 
BatchWriteRow(request *BatchWriteRowRequest) (*BatchWriteRowResponse,error)                  

Examples

The following sample code provides an example on how to write 100 rows of data at the same time:

batchWriteReq := &tablestore.BatchWriteRowRequest{}
for i := 0; i < 100; i++ {
    putRowChange := new(tablestore.PutRowChange)
    putRowChange.TableName = tableName
    putPk := new(tablestore.PrimaryKey)
    putPk.AddPrimaryKeyColumn("pk1", "pk1value1")
    putPk.AddPrimaryKeyColumn("pk2", int64(i))
    putPk.AddPrimaryKeyColumn("pk3", []byte("pk3"))
    putRowChange.PrimaryKey = putPk
    putRowChange.AddColumn("col1", "fixvalue")
    putRowChange.SetCondition(tablestore.RowExistenceExpectation_IGNORE)
    batchWriteReq.AddRowChange(putRowChange)
}

response, err := client.BatchWriteRow(batchWriteReq)
if err != nil {
    fmt.Println("batch request failed with:", response)
} else {
    fmt.Println("batch write row finished")
}                   

To view the detailed sample code, visit BatchWriteRow@GitHub.

FAQ

• What do I do if the Validate PK size fail exception occurs when I use SDKs?

• What do I do if the Validate PK name fail exception occurs when I use SDKs?

• What can I do if errors related to data types supported by primary key columns occur?

• What do I do if OTSParameterInvalid is reported when I use BatchWriteRow to submit 100 data entries at a time?

References

• To update data in a highly concurrent application based on the specified conditions, you can use the conditional update feature. For more information, see Configure conditional update.

• To collect real-time statistics about online applications, such as the number of page views (PVs) on various topics, you can use the atomic counter feature. For more information, see Configure atomic counter.

• To perform atomic operations to write one or more rows of data, you can use the local transaction feature. For more information, see Configure local transaction.

• After data is written to a table, you can read or delete the data in the table based on your business requirements. For more information, see Read data and Delete data.