本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。
# 使用 DynamoDB 專用 PartiQL 執行批次操作
本節說明如何搭配 DynamoDB 專用 PartiQL 使用批次陳述式。
**注意**
整個批次必須由讀取陳述式或寫入陳述式所組成；一個批次中不能同時出現這兩種陳述式樣。
`BatchExecuteStatement` 和 `BatchWriteItem` 每個批次不可以執行超過 25 條陳述式。
`BatchExecuteStatement` 會使用 `BatchGetItem`，其會取得個別陳述式中主索引鍵的清單。
**Topics**
+ [語法](#ql-reference.multiplestatements.batching.syntax)
+ [Parameters](#ql-reference.multiplestatements.batching.parameters)
+ [範例](#ql-reference.multiplestatements.batching.examples)
## 語法
```
[
{
"Statement": "SELECT pk FROM ProblemSet WHERE pk = 'p#9StkWHYTxm7x2AqSXcrfu7' AND sk = 'info'"
},
{
"Statement": "SELECT pk FROM ProblemSet WHERE pk = 'p#isC2ChceGbxHgESc4szoTE' AND sk = 'info'"
}
]
```
```
[
{
"Statement":"{{ statement }}",
"Parameters":[
{
"{{ parametertype }}" : "{{ parametervalue }}"
}, ...]
} , ...
]
```
## Parameters
**{{陳述式}}**
(必要) DynamoDB 專用 PartiQL 支援的陳述式。
+ 整個批次必須由讀取陳述式或寫入陳述式所組成；一個批次中不能同時出現這兩種陳述式樣。
+ `BatchExecuteStatement` 和 `BatchWriteItem` 每個批次不可以執行超過 25 條陳述式。
**{{parametertype}}**
(選用) DynamoDB 類型，如果在指定 PartiQL 陳述式時使用了參數。
**{{parametervalue}}**
(選用) 參數值，如果在指定 PartiQL 陳述式時使用了參數。
## 範例
------
#### [ AWS CLI ]
1. 將以下 json 儲存至名為 partiql.json 的檔案
```
[
{
"Statement": "INSERT INTO Music VALUE {'Artist':?,'SongTitle':?}",
"Parameters": [{"S": "Acme Band"}, {"S": "Best Song"}]
},
{
"Statement": "UPDATE Music SET AwardsWon=1, AwardDetail={'Grammys':[2020, 2018]} WHERE Artist='Acme Band' AND SongTitle='PartiQL Rocks'"
}
]
```
1. 在命令提示中執行下列命令。
```
aws dynamodb batch-execute-statement --statements file://partiql.json
```
------
#### [ Java ]
```
public class DynamoDBPartiqlBatch {
public static void main(String[] args) {
// Create the DynamoDB Client with the region you want
AmazonDynamoDB dynamoDB = createDynamoDbClient("us-west-2");
try {
// Create BatchExecuteStatementRequest
BatchExecuteStatementRequest batchExecuteStatementRequest = createBatchExecuteStatementRequest();
BatchExecuteStatementResult batchExecuteStatementResult = dynamoDB.batchExecuteStatement(batchExecuteStatementRequest);
System.out.println("BatchExecuteStatement successful.");
// Handle batchExecuteStatementResult
} catch (Exception e) {
handleBatchExecuteStatementErrors(e);
}
}
private static AmazonDynamoDB createDynamoDbClient(String region) {
return AmazonDynamoDBClientBuilder.standard().withRegion(region).build();
}
private static BatchExecuteStatementRequest createBatchExecuteStatementRequest() {
BatchExecuteStatementRequest request = new BatchExecuteStatementRequest();
// Create statements
List statements = getPartiQLBatchStatements();
request.setStatements(statements);
return request;
}
private static List getPartiQLBatchStatements() {
List statements = new ArrayList();
statements.add(new BatchStatementRequest()
.withStatement("INSERT INTO Music value {'Artist':'Acme Band','SongTitle':'PartiQL Rocks'}"));
statements.add(new BatchStatementRequest()
.withStatement("UPDATE Music set AwardDetail.BillBoard=[2020] where Artist='Acme Band' and SongTitle='PartiQL Rocks'"));
return statements;
}
// Handles errors during BatchExecuteStatement execution. Use recommendations in error messages below to add error handling specific to
// your application use-case.
private static void handleBatchExecuteStatementErrors(Exception exception) {
try {
throw exception;
} catch (Exception e) {
// There are no API specific errors to handle for BatchExecuteStatement, common DynamoDB API errors are handled below
handleCommonErrors(e);
}
}
private static void handleCommonErrors(Exception exception) {
try {
throw exception;
} catch (InternalServerErrorException isee) {
System.out.println("Internal Server Error, generally safe to retry with exponential back-off. Error: " + isee.getErrorMessage());
} catch (RequestLimitExceededException rlee) {
System.out.println("Throughput exceeds the current throughput limit for your account, increase account level throughput before " +
"retrying. Error: " + rlee.getErrorMessage());
} catch (ProvisionedThroughputExceededException ptee) {
System.out.println("Request rate is too high. If you're using a custom retry strategy make sure to retry with exponential back-off. " +
"Otherwise consider reducing frequency of requests or increasing provisioned capacity for your table or secondary index. Error: " +
ptee.getErrorMessage());
} catch (ResourceNotFoundException rnfe) {
System.out.println("One of the tables was not found, verify table exists before retrying. Error: " + rnfe.getErrorMessage());
} catch (AmazonServiceException ase) {
System.out.println("An AmazonServiceException occurred, indicates that the request was correctly transmitted to the DynamoDB " +
"service, but for some reason, the service was not able to process it, and returned an error response instead. Investigate and " +
"configure retry strategy. Error type: " + ase.getErrorType() + ". Error message: " + ase.getErrorMessage());
} catch (AmazonClientException ace) {
System.out.println("An AmazonClientException occurred, indicates that the client was unable to get a response from DynamoDB " +
"service, or the client was unable to parse the response from the service. Investigate and configure retry strategy. "+
"Error: " + ace.getMessage());
} catch (Exception e) {
System.out.println("An exception occurred, investigate and configure retry strategy. Error: " + e.getMessage());
}
}
}
```
------