Running batch operations with PartiQL for DynamoDB - Amazon DynamoDB
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Running batch operations with PartiQL for DynamoDB

This section describes how to use batch statements with PartiQL for DynamoDB.

Note
  • The entire batch must consist of either read statements or write statements; you cannot mix both in one batch.

  • BatchExecuteStatement and BatchWriteItem can perform no more than 25 statements per batch.

Syntax

[ { "Statement":" statement ", "Parameters":[ { " parametertype " : " parametervalue " }, ...] } , ... ]

Parameters

statement

(Required) A PartiQL for DynamoDB supported statement.

Note
  • The entire batch must consist of either read statements or write statements; you cannot mix both in one batch.

  • BatchExecuteStatement and BatchWriteItem can perform no more than 25 statements per batch.

parametertype

(Optional) A DynamoDB type, if parameters were used when specifying the PartiQL statement.

parametervalue

(Optional) A parameter value if parameters were used when specifying the PartiQL statement.

Examples

Amazon CLI
  1. Save the following json to a file called partiql.json

    [ { "Statement": "INSERT INTO "Music" value {'Artist':'?','SongTitle':'?'}", "Parameters": [{"S": "Acme Band"}, {"S": "Best Song"}] }, { "Statement": "UPDATE "Music" SET AwardsWon=1 SET AwardDetail={'Grammys':[2020, 2018]} where Artist='Acme Band' and SongTitle='PartiQL Rocks'" } ]
  2. Run the following command in a command prompt.

    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<BatchStatementRequest> statements = getPartiQLBatchStatements(); request.setStatements(statements); return request; } private static List<BatchStatementRequest> getPartiQLBatchStatements() { List<BatchStatementRequest> statements = new ArrayList<BatchStatementRequest>(); 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()); } } }