Is there any standard way to get cloud task count for a queue?
I know we can loop through nextPageToken and achieve this.
Can this be achieved with single request?
By looking at the documentation, QueueStats seems to be the standard way to get task count.
As mentioned in #Sameer comment, cloudtask v2beta3 has a feature to request for stats of a queue:
public long geQueueDepth(String queuePath) {
long depth=-1;
try {
FieldMask.Builder fieldBuilder = FieldMask.newBuilder();
fieldBuilder.addPaths("stats");
com.google.cloud.tasks.v2beta3.GetQueueRequest queueRequest =
com.google.cloud.tasks.v2beta3.GetQueueRequest.newBuilder().setName(queuePath).setReadMask(fieldBuilder).build();;
com.google.cloud.tasks.v2beta3.Queue queue = cloudTasksClientV3.getQueue(queueRequest);
depth=queue.getStats().getTasksCount();
}catch (Exception e){
LOGGER.error("Error while getting queue depth =>{}",e.getMessage());
}
return depth;
}
Related
Below code returned a timeout in client (Elasticsearch Client) when number of records are higher.
CompletableFuture<BulkByScrollResponse> future = new CompletableFuture<>();
client.reindexAsync(request, RequestOptions.DEFAULT, new ActionListener<BulkByScrollResponse>() {
#Override
public void onResponse(BulkByScrollResponse bulkByScrollResponse) {
future.complete(bulkByScrollResponse);
}
#Override
public void onFailure(Exception e) {
future.completeExceptionally(e);
}
});
BulkByScrollResponse response = future.get(10, TimeUnit.MINUTES); // client timeout occured before this timeout
Below is the client config.
connectTimeout: 60000
socketTimeout: 600000
maxRetryTimeoutMillis: 600000
Is there a way to wait indefinitely until the re-indexing complete?
submit the reindex request as a task:
TaskSubmissionResponse task = esClient.submitReindexTask(reindex, RequestOptions.DEFAULT);
acquire the task id:
TaskId taskId = new TaskId(task.getTask());
then check the task status periodically:
GetTaskRequest taskQuery = new GetTaskRequest(taskId.getNodeId(), taskId.getId());
GetTaskResponse taskStatus;
do {
Thread.sleep(TimeUnit.MINUTES.toMillis(1));
taskStatus = esClient.tasks()
.get(taskQuery, RequestOptions.DEFAULT)
.orElseThrow(() -> new IllegalStateException("Reindex task not found. id=" + taskId));
} while (!taskStatus.isCompleted());
Elasticsearch java api doc about task handling just sucks.
Ref
I don't think its a better choice to wait indefinitely to complete the re-indexing process and give very high value for timeout as this is not a proper fix and will cause more harm than good.
Instead you should examine the response, add more debugging logging to find the root-cause and address them. Also please have a look at my tips to improve re-indexing speed, which should fix some of your underlying issues.
I am learning Android, and my task is to retrieve steps data using Google Fit steps API. However, I keep getting "Task is not yet complete" error. I am not sure
This is my code for that part:
private List<Fitness> readHistoryDataFromGoogle() {
DataReadRequest readRequest = createDataReadRequest();
Task<DataReadResponse> response = com.google.android.gms.fitness.Fitness.getHistoryClient(this, GoogleSignIn.getLastSignedInAccount(this)).readData(readRequest);
DataReadResponse responses = response.getResult();
List <Fitness> fitnessItems = parseFitness(responses);
return fitnessItems;
}
private List<Fitness> parseFitness(DataReadResponse dataReadResponse) {
List<com.example.mentalhealthapp.Fitness> fitnessItems = new ArrayList<>();
for (Bucket bucket : dataReadResponse.getBuckets()) {
for (DataSet set : bucket.getDataSets()) {
for (DataPoint dataPoint : set.getDataPoints()) {
int numSteps = dataPoint.getValue(Field.FIELD_STEPS).asInt();
long startDateTime = dataPoint.getStartTime(TimeUnit.MILLISECONDS);
long endDateTime = dataPoint.getEndTime(TimeUnit.MILLISECONDS);
fitnessItems.add(new com.example.mentalhealthapp.Fitness(numSteps, startDateTime, endDateTime));
}
}
}
return fitnessItems;
}
Thank you very much for your help!
You're getting this problem, because API requests (service calls) are Asynchronous, they don't complete and return data immediately and you can't run them line by line like other code. you have to WAIT for that response to complete before you can access the data it returns.
from the documentation it tells you it's a REST api:
Brief look at documentation
https://developers.google.com/android/reference/com/google/android/gms/fitness/RecordingClient suggests you should look at this for displaying data when it becomes available.
We are trying to implement Kafka as our message broker solution. We are deploying our Spring Boot microservices in IBM BLuemix, whose internal message broker implementation is Kafka version 0.10. Since my experience is more on the JMS, ActiveMQ end, I was wondering what should be the ideal way to handle system level errors in the java consumers?
Here is how we have implemented it currently
Consumer properties
enable.auto.commit=false
auto.offset.reset=latest
We are using the default properties for
max.partition.fetch.bytes
session.timeout.ms
Kafka Consumer
We are spinning up 3 threads per topic all having the same groupId, i.e one KafkaConsumer instance per thread. We have only one partition as of now. The consumer code looks like this in the constructor of the thread class
kafkaConsumer = new KafkaConsumer<String, String>(properties);
final List<String> topicList = new ArrayList<String>();
topicList.add(properties.getTopic());
kafkaConsumer.subscribe(topicList, new ConsumerRebalanceListener() {
#Override
public void onPartitionsRevoked(final Collection<TopicPartition> partitions) {
}
#Override
public void onPartitionsAssigned(final Collection<TopicPartition> partitions) {
try {
logger.info("Partitions assigned, consumer seeking to end.");
for (final TopicPartition partition : partitions) {
final long position = kafkaConsumer.position(partition);
logger.info("current Position: " + position);
logger.info("Seeking to end...");
kafkaConsumer.seekToEnd(Arrays.asList(partition));
logger.info("Seek from the current position: " + kafkaConsumer.position(partition));
kafkaConsumer.seek(partition, position);
}
logger.info("Consumer can now begin consuming messages.");
} catch (final Exception e) {
logger.error("Consumer can now begin consuming messages.");
}
}
});
The actual reading happens in the run method of the thread
try {
// Poll on the Kafka consumer every second.
final ConsumerRecords<String, String> records = kafkaConsumer.poll(1000);
// Iterate through all the messages received and print their
// content.
for (final TopicPartition partition : records.partitions()) {
final List<ConsumerRecord<String, String>> partitionRecords = records.records(partition);
logger.info("consumer is alive and is processing "+ partitionRecords.size() +" records");
for (final ConsumerRecord<String, String> record : partitionRecords) {
logger.info("processing topic "+ record.topic()+" for key "+record.key()+" on offset "+ record.offset());
final Class<? extends Event> resourceClass = eventProcessors.getResourceClass();
final Object obj = converter.convertToObject(record.value(), resourceClass);
if (obj != null) {
logger.info("Event: " + obj + " acquired by " + Thread.currentThread().getName());
final CommsEvent event = resourceClass.cast(converter.convertToObject(record.value(), resourceClass));
final MessageResults results = eventProcessors.processEvent(event
);
if ("Success".equals(results.getStatus())) {
// commit the processed message which changes
// the offset
kafkaConsumer.commitSync();
logger.info("Message processed sucessfully");
} else {
kafkaConsumer.seek(new TopicPartition(record.topic(), record.partition()), record.offset());
logger.error("Error processing message : {} with error : {},resetting offset to {} ", obj,results.getError().getMessage(),record.offset());
break;
}
}
}
}
// TODO add return
} catch (final Exception e) {
logger.error("Consumer has failed with exception: " + e, e);
shutdown();
}
You will notice the EventProcessor which is a service class which processes each record, in most cases commits the record in database. If the processor throws an error (System Exception or ValidationException) we do not commit but programatically set the seek to that offset, so that subsequent poll will return from that offset for that group id.
The doubt now is that, is this the right approach? If we get an error and we set the offset then until that is fixed no other message is processed. This might work for system errors like not able to connect to DB, but if the problem is only with that event and not others to process this one record we wont be able to process any other record. We thought of the concept of ErrorTopic where when we get an error the consumer will publish that event to the ErrorTopic and in the meantime it will keep on processing other subsequent events. But it looks like we are trying to bring in the design concepts of JMS (due to my previous experience) into kafka and there may be better way to solve error handling in kafka. Also reprocessing it from error topic may change the sequence of messages which we don't want for some scenarios
Please let me know how anyone has handled this scenario in their projects following the Kafka standards.
-Tatha
if the problem is only with that event and not others to process this one record we wont be able to process any other record
that's correct and your suggestion to use an error topic seems a possible one.
I also noticed that with your handling of onPartitionsAssigned you essentially do not use the consumer committed offset, as you seem you'll always seek to the end.
If you want to restart from the last succesfully committed offset, you should not perform a seek
Finally, I'd like to point out, though it looks like you know that, having 3 consumers in the same group subscribed to a single partition - means that 2 out of 3 will be idle.
HTH
Edo
I try to re-index an ES index with Java:
// reindex all documents from the old into the new index
QueryBuilder qb = QueryBuilders.matchAllQuery();
SearchResponse scrollResp = client.prepareSearch("my_index").setSearchType(SearchType.SCAN).setScroll(new TimeValue(600000)).setQuery(qb).setSize(100).execute().actionGet();
while (true) {
scrollResp = client.prepareSearchScroll(scrollResp.getScrollId()).setScroll(new TimeValue(600000)).execute().actionGet();
final int documentFoundCount = scrollResp.getHits().getHits().length;
// Break condition: No hits are returned
if (documentFoundCount == 0) {
break;
}
// otherwise add all documents which are found (in this scroll-search) to a bulk operation for reindexing.
logger.info("Found {} documents in the scroll search, re-indexing them via bulk now.", documentFoundCount);
BulkRequestBuilder bulk = client.prepareBulk();
for (SearchHit hit : scrollResp.getHits()) {
bulk.add(new IndexRequest(newIndexName, hit.getType()).source(hit.getSource()));
}
bulk.execute(new ActionListener<BulkResponse>() {
#Override public void onResponse(BulkResponse bulkItemResponses) {
logger.info("Reindexed {} documents from '{}' to '{}'.", bulkItemResponses.getItems().length, currentIndexName, newIndexName);
}
#Override public void onFailure(Throwable e) {
logger.error("Could not complete the index re-aliasing.", e);
}
});
}
// these following lines should only be executed if the re-indexing was successful for _all_ documents.
logger.info("Finished re-indexing all documents, now setting the aliases from the old to the new index.");
try {
client.admin().indices().aliases(new IndicesAliasesRequest().removeAlias(currentIndexName, "my_index").addAlias("my_index", newIndexName)).get();
// finally, delete the old index
client.admin().indices().delete(new DeleteIndexRequest(currentIndexName)).actionGet();
} catch (InterruptedException | ExecutionException e) {
logger.error("Could not complete the index re-aliasing.", e);
}
In general, this works, but the approach has one problem:
If there is a failure during re-indexing, e.g. it takes too long and is stopped by some transaction watch (it runs during EJB startup), the alias is re-set and the old index is nevertheless removed.
How can I do that alias-re-setting if and only if all bulk requests were successful?
You're not waiting until the bulk request finishes. If you call execute() without actionGet(), you end up running asynchronously. Which means you will start changing aliases and deleting indexes before the new index is completely built.
Also:
client.admin().indices().aliases(new IndicesAliasesRequest().removeAlias(currentIndexName, "my_index").addAlias("my_index", newIndexName)).get();
This should be ended with execute().actionGet() and not get(). that is probably why your alias is not getting set
I have multiple messages in SQS. The following code always returns only one, even if there are dozens visible (not in flight). setMaxNumberOfMessages I thought would allow multiple to be consumed at once .. have i misunderstood this?
CreateQueueRequest createQueueRequest = new CreateQueueRequest().withQueueName(queueName);
String queueUrl = sqs.createQueue(createQueueRequest).getQueueUrl();
ReceiveMessageRequest receiveMessageRequest = new ReceiveMessageRequest(queueUrl);
receiveMessageRequest.setMaxNumberOfMessages(10);
List<Message> messages = sqs.receiveMessage(receiveMessageRequest).getMessages();
for (Message message : messages) {
// i'm a message from SQS
}
I've also tried using withMaxNumberOfMessages without any such luck:
receiveMessageRequest.withMaxNumberOfMessages(10);
How do I know there are messages in the queue? More than 1?
Set<String> attrs = new HashSet<String>();
attrs.add("ApproximateNumberOfMessages");
CreateQueueRequest createQueueRequest = new CreateQueueRequest().withQueueName(queueName);
GetQueueAttributesRequest a = new GetQueueAttributesRequest().withQueueUrl(sqs.createQueue(createQueueRequest).getQueueUrl()).withAttributeNames(attrs);
Map<String,String> result = sqs.getQueueAttributes(a).getAttributes();
int num = Integer.parseInt(result.get("ApproximateNumberOfMessages"));
The above always is run prior and gives me an int that is >1
Thanks for your input
AWS API Reference Guide: Query/QueryReceiveMessage
Due to the distributed nature of the queue, a weighted random set of machines is sampled on a ReceiveMessage call. That means only the messages on the sampled machines are returned. If the number of messages in the queue is small (less than 1000), it is likely you will get fewer messages than you requested per ReceiveMessage call. If the number of messages in the queue is extremely small, you might not receive any messages in a particular ReceiveMessage response; in which case you should repeat the request.
and
MaxNumberOfMessages: Maximum number of messages to return. SQS never returns more messages than this value but might return fewer.
There is a comprehensive explanation for this (arguably rather idiosyncratic) behaviour in the SQS reference documentation.
SQS stores copies of messages on multiple servers and receive message requests are made to these servers with one of two possible strategies,
Short Polling : The default behaviour, only a subset of the servers (based on a weighted random distribution) are queried.
Long Polling : Enabled by setting the WaitTimeSeconds attribute to a non-zero value, all of the servers are queried.
In practice, for my limited tests, I always seem to get one message with short polling just as you did.
I had the same problem. What is your Receive Message Wait Time for your queue set to? When mine was at 0, it only returned 1 message even if there were 8 in the queue. When I increased the Receive Message Wait Time, then I got all of them. Seems kind of buggy to me.
I was just trying the same and with the help of these two attributes setMaxNumberOfMessages and setWaitTimeSeconds i was able to get 10 messages.
ReceiveMessageRequest receiveMessageRequest = new ReceiveMessageRequest(myQueueUrl);
receiveMessageRequest.setMaxNumberOfMessages(10);
receiveMessageRequest.setWaitTimeSeconds(20);
Snapshot of o/p:
Receiving messages from TestQueue.
Number of messages:10
Message
MessageId: 31a7c669-1f0c-4bf1-b18b-c7fa31f4e82d
...
receiveMessageRequest.withMaxNumberOfMessages(10);
Just to be clear, the more practical use of this would be to add to your constructor like this:
ReceiveMessageRequest receiveMessageRequest = new ReceiveMessageRequest(queueUrl).withMaxNumberOfMessages(10);
Otherwise, you might as well just do:
receiveMessageRequest.setMaxNumberOfMessages(10);
That being said, changing this won't help the original problem.
Thanks Caoilte!
I faced this issue also. Finally solved by using long polling follow the configuration here:
https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-configure-long-polling-for-queue.html
Unfortunately, to use long polling, you must create your queue as FIFO one. I tried standard queue with no luck.
And when receiving, need also set MaxNumberOfMessages. So my code is like:
ReceiveMessageRequest receive_request = new ReceiveMessageRequest()
.withQueueUrl(QUEUE_URL)
.withWaitTimeSeconds(20)
.withMaxNumberOfMessages(10);
Although solved, still feel too wired. AWS should definitely provide a more neat API for this kind of basic receiving operation.
From my point, AWS has many many cool features but not good APIs. Like those guys are rushing out all the time.
For small task list I use FIFO queue like stackoverflow.com/a/55149351/13678017
for example modified AWS tutorial
// Create a queue.
System.out.println("Creating a new Amazon SQS FIFO queue called " + "MyFifoQueue.fifo.\n");
final Map<String, String> attributes = new HashMap<>();
// A FIFO queue must have the FifoQueue attribute set to true.
attributes.put("FifoQueue", "true");
/*
* If the user doesn't provide a MessageDeduplicationId, generate a
* MessageDeduplicationId based on the content.
*/
attributes.put("ContentBasedDeduplication", "true");
// The FIFO queue name must end with the .fifo suffix.
final CreateQueueRequest createQueueRequest = new CreateQueueRequest("MyFifoQueue4.fifo")
.withAttributes(attributes);
final String myQueueUrl = sqs.createQueue(createQueueRequest).getQueueUrl();
// List all queues.
System.out.println("Listing all queues in your account.\n");
for (final String queueUrl : sqs.listQueues().getQueueUrls()) {
System.out.println(" QueueUrl: " + queueUrl);
}
System.out.println();
// Send a message.
System.out.println("Sending a message to MyQueue.\n");
for (int i = 0; i < 4; i++) {
var request = new SendMessageRequest()
.withQueueUrl(myQueueUrl)
.withMessageBody("message " + i)
.withMessageGroupId("userId1");
;
sqs.sendMessage(request);
}
for (int i = 0; i < 6; i++) {
var request = new SendMessageRequest()
.withQueueUrl(myQueueUrl)
.withMessageBody("message " + i)
.withMessageGroupId("userId2");
;
sqs.sendMessage(request);
}
// Receive messages.
System.out.println("Receiving messages from MyQueue.\n");
var receiveMessageRequest = new ReceiveMessageRequest(myQueueUrl);
receiveMessageRequest.setMaxNumberOfMessages(10);
receiveMessageRequest.setWaitTimeSeconds(20);
// what receive?
receiveMessageRequest.withMessageAttributeNames("userId2");
final List<Message> messages = sqs.receiveMessage(receiveMessageRequest).getMessages();
for (final Message message : messages) {
System.out.println("Message");
System.out.println(" MessageId: "
+ message.getMessageId());
System.out.println(" ReceiptHandle: "
+ message.getReceiptHandle());
System.out.println(" MD5OfBody: "
+ message.getMD5OfBody());
System.out.println(" Body: "
+ message.getBody());
for (final Entry<String, String> entry : message.getAttributes()
.entrySet()) {
System.out.println("Attribute");
System.out.println(" Name: " + entry
.getKey());
System.out.println(" Value: " + entry
.getValue());
}
}
Here's a workaround, you can call receiveMessageFromSQS method asynchronously.
bulkReceiveFromSQS (queueUrl, totalMessages, asyncLimit, batchSize, visibilityTimeout, waitTime, callback) {
batchSize = Math.min(batchSize, 10);
let self = this,
noOfIterations = Math.ceil(totalMessages / batchSize);
async.timesLimit(noOfIterations, asyncLimit, function(n, next) {
self.receiveMessageFromSQS(queueUrl, batchSize, visibilityTimeout, waitTime,
function(err, result) {
if (err) {
return next(err);
}
return next(null, _.get(result, 'Messages'));
});
}, function (err, listOfMessages) {
if (err) {
return callback(err);
}
listOfMessages = _.flatten(listOfMessages).filter(Boolean);
return callback(null, listOfMessages);
});
}
It will return you an array with a given number of messages