I cannot start my dropwizard application after add database details in my application configuration file (server.yml).
server.yml (app config file)
server:
applicationConnectors:
- type: http
port: 8080
adminConnectors:
- type: http
port: 9001
database:
# the name of your JDBC driver
driverClass: org.postgresql.Driver
# the username
user: dbuser
# the password
password: pw123
# the JDBC URL
url: jdbc:postgresql://localhost/database
# any properties specific to your JDBC driver:
properties:
charSet: UTF-8
# the maximum amount of time to wait on an empty pool before throwing an exception
maxWaitForConnection: 1s
# the SQL query to run when validating a connection's liveness
validationQuery: "/* MyService Health Check */ SELECT 1"
# the timeout before a connection validation queries fail
validationQueryTimeout: 3s
# the minimum number of connections to keep open
minSize: 8
# the maximum number of connections to keep open
maxSize: 32
# whether or not idle connections should be validated
checkConnectionWhileIdle: false
# the amount of time to sleep between runs of the idle connection validation, abandoned cleaner and idle pool resizing
evictionInterval: 10s
# the minimum amount of time an connection must sit idle in the pool before it is eligible for eviction
minIdleTime: 1 minute
As result of run dropwizard application I can see:
has an error:
* Unrecognized field at: database
Did you mean?:
- metrics
- server
- logging
In addition to code given by dropwizard example you need to add a setter for database property.
#Valid
#NotNull
#JsonProperty("database")
private DataSourceFactory database = new DataSourceFactory();
public DataSourceFactory getDataSourceFactory() {
return database;
}
public void setDatabase(DataSourceFactory database) {
this.database = database;
}
In your application configuration java file, you have to add the matching property for "database". If the properties you're specifying are the standard ones (which they look to be, good!) then you can keep with the DataSourceFactory type:
public class ExampleConfiguration extends Configuration {
#Valid
#NotNull
#JsonProperty
private DataSourceFactory database = new DataSourceFactory();
public DataSourceFactory getDataSourceFactory() {
return database;
}
public void setDatabase(DataSourceFactory database) {
this.database = database;
}
}
Example here: http://www.dropwizard.io/0.9.0/docs/manual/jdbi.html
Related
I have built my job jar using sbt assembly to have all dependencies in one jar. When I try to submit my binary to spark-jobserver I am getting akka.pattern.AskTimeoutException
I modified my configuration to be able to submit large jars (I added parsing.max-content-length = 300m to my configuration) I also increased some of timeouts in configuration but nothing helped.
After I run:
curl --data-binary #matching-ml-assembly-1.0.jar localhost:8090/jars/matching-ml
I am getting:
{
"status": "ERROR",
"result": {
"message": "Ask timed out on [Actor[akka://JobServer/user/binary-manager#1785133213]] after [3000 ms]. Sender[null] sent message of type \"spark.jobserver.StoreBinary\".",
"errorClass": "akka.pattern.AskTimeoutException",
"stack": ["akka.pattern.PromiseActorRef$$anonfun$1.apply$mcV$sp(AskSupport.scala:604)", "akka.actor.Scheduler$$anon$4.run(Scheduler.scala:126)", "scala.concurrent.Future$InternalCallbackExecutor$.unbatchedExecute(Future.scala:601)", "scala.concurrent.BatchingExecutor$class.execute(BatchingExecutor.scala:109)", "scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:599)", "akka.actor.LightArrayRevolverScheduler$TaskHolder.executeTask(LightArrayRevolverScheduler.scala:331)", "akka.actor.LightArrayRevolverScheduler$$anon$4.executeBucket$1(LightArrayRevolverScheduler.scala:282)", "akka.actor.LightArrayRevolverScheduler$$anon$4.nextTick(LightArrayRevolverScheduler.scala:286)", "akka.actor.LightArrayRevolverScheduler$$anon$4.run(LightArrayRevolverScheduler.scala:238)", "java.lang.Thread.run(Thread.java:745)"]
}
My configuration:
# Template for a Spark Job Server configuration file
# When deployed these settings are loaded when job server starts
#
# Spark Cluster / Job Server configuration
spark {
# spark.master will be passed to each job's JobContext
master = "local[4]"
# master = "mesos://vm28-hulk-pub:5050"
# master = "yarn-client"
# Default # of CPUs for jobs to use for Spark standalone cluster
job-number-cpus = 4
jobserver {
port = 8090
context-per-jvm = false
# Note: JobFileDAO is deprecated from v0.7.0 because of issues in
# production and will be removed in future, now defaults to H2 file.
jobdao = spark.jobserver.io.JobSqlDAO
filedao {
rootdir = /tmp/spark-jobserver/filedao/data
}
datadao {
# storage directory for files that are uploaded to the server
# via POST/data commands
rootdir = /tmp/spark-jobserver/upload
}
sqldao {
# Slick database driver, full classpath
slick-driver = slick.driver.H2Driver
# JDBC driver, full classpath
jdbc-driver = org.h2.Driver
# Directory where default H2 driver stores its data. Only needed for H2.
rootdir = /tmp/spark-jobserver/sqldao/data
# Full JDBC URL / init string, along with username and password. Sorry, needs to match above.
# Substitutions may be used to launch job-server, but leave it out here in the default or tests won't pass
jdbc {
url = "jdbc:h2:file:/tmp/spark-jobserver/sqldao/data/h2-db"
user = ""
password = ""
}
# DB connection pool settings
dbcp {
enabled = false
maxactive = 20
maxidle = 10
initialsize = 10
}
}
# When using chunked transfer encoding with scala Stream job results, this is the size of each chunk
result-chunk-size = 1m
}
# Predefined Spark contexts
# contexts {
# my-low-latency-context {
# num-cpu-cores = 1 # Number of cores to allocate. Required.
# memory-per-node = 512m # Executor memory per node, -Xmx style eg 512m, 1G, etc.
# }
# # define additional contexts here
# }
# Universal context configuration. These settings can be overridden, see README.md
context-settings {
num-cpu-cores = 2 # Number of cores to allocate. Required.
memory-per-node = 2G # Executor memory per node, -Xmx style eg 512m, #1G, etc.
# In case spark distribution should be accessed from HDFS (as opposed to being installed on every Mesos slave)
# spark.executor.uri = "hdfs://namenode:8020/apps/spark/spark.tgz"
# URIs of Jars to be loaded into the classpath for this context.
# Uris is a string list, or a string separated by commas ','
# dependent-jar-uris = ["file:///some/path/present/in/each/mesos/slave/somepackage.jar"]
# Add settings you wish to pass directly to the sparkConf as-is such as Hadoop connection
# settings that don't use the "spark." prefix
passthrough {
#es.nodes = "192.1.1.1"
}
}
# This needs to match SPARK_HOME for cluster SparkContexts to be created successfully
# home = "/home/spark/spark"
}
# Note that you can use this file to define settings not only for job server,
# but for your Spark jobs as well. Spark job configuration merges with this configuration file as defaults.
spray.can.server {
# uncomment the next lines for making this an HTTPS example
# ssl-encryption = on
# path to keystore
#keystore = "/some/path/sjs.jks"
#keystorePW = "changeit"
# see http://docs.oracle.com/javase/7/docs/technotes/guides/security/StandardNames.html#SSLContext for more examples
# typical are either SSL or TLS
encryptionType = "SSL"
keystoreType = "JKS"
# key manager factory provider
provider = "SunX509"
# ssl engine provider protocols
enabledProtocols = ["SSLv3", "TLSv1"]
idle-timeout = 60 s
request-timeout = 20 s
connecting-timeout = 5s
pipelining-limit = 2 # for maximum performance (prevents StopReading / ResumeReading messages to the IOBridge)
# Needed for HTTP/1.0 requests with missing Host headers
default-host-header = "spray.io:8765"
# Increase this in order to upload bigger job jars
parsing.max-content-length = 300m
}
akka {
remote.netty.tcp {
# This controls the maximum message size, including job results, that can be sent
# maximum-frame-size = 10 MiB
}
}
I came to the similar issue. The way how to solve it is a bit tricky. First you need to add spark.jobserver.short-timeout to your configuration. Just modify your configuration like this:
jobserver {
port = 8090
context-per-jvm = false
short-timeout = 60s
...
}
The second (tricky) part is you can't fix it without modifying code of the spark-job-application. The attribute which cause timeout is in class BinaryManager:
implicit val daoAskTimeout = Timeout(3 seconds)
The default is set to 3 second which apparently for big jar is not enough. You can increase it to for example 60 second which solve problem for me.
implicit val daoAskTimeout = Timeout(60 seconds)
Actually you can bring down the size of the jars easily. Also some of the dependent jars can be passed using dependent-jar-uris instead of assembling into one big fat jar.
I'm currently facing an issue where Eureka does not unregister a registered service. I've pulled the Eureka server example straight from git hub and made only one change, eureka.enableSelfPreservation = false. My application.yml looks like this:
server:
port: 8761
eureka:
enableSelfPreservation: false
client:
registerWithEureka: false
fetchRegistry: false
server:
waitTimeInMsWhenSyncEmpty: 0
I've read that if 85% of the registered services stop delivering heartbeats within 15 minutes, Eureka assumes the issue is network related and does not de-register the services that are not responding. In my case I have only one service running, so I disabled self-preservation mode. I am abruptly killing the process and Eureka leaves the service registered for what seems like an indefinite amount of time.
My client's application.yml looks like this:
eureka:
instance:
leaseRenewalIntervalInSeconds: 3
client:
healthcheck:
enabled: true
serviceUrl:
defaultZone: http://localhost:8761/eureka/
appInfo:
replicate:
interval: 3
initial:
replicate:
time: 3
spring:
rabbitmq:
addresses: ${vcap.services.${PREFIX:}rabbitmq.credentials.uri:amqp://${RABBITMQ_HOST:localhost}:${RABBITMQ_PORT:5672}}
My goal is to create a demo where Eureka quickly detects the service is no longer running and another service that is started can quickly register itself.
As of now, once the eureka client is started, it registers in 3 seconds. It just never un-registers when the service is abruptly terminated. After I kill the service, the Eureka dashboard reads:
EMERGENCY! EUREKA MAY BE INCORRECTLY CLAIMING INSTANCES ARE UP WHEN THEY'RE NOT. RENEWALS ARE LESSER THAN THRESHOLD AND HENCE THE INSTANCES ARE NOT BEING EXPIRED JUST TO BE SAFE.
How can I prevent this behavior?
I realized that self preservation mode was never actually being disabled. It turns out the actual property is
eureka.server.enableSelfPreservation=false
(See DefaultEurekaServerConfig Code), which I haven't found documented anywhere. This resolved my issue.
I made service de-registration work by setting the below values
Eureka server application.yml
eureka:
server:
enableSelfPreservation: false
Service application.yml
eureka:
instance:
leaseRenewalIntervalInSeconds: 1
leaseExpirationDurationInSeconds: 2
The full example is here https://github.com/ExampleDriven/spring-cloud-eureka-example
After struggling a lot, finally I got solution if any service unregistered from Eureka server due to some issue. It will notify to the Admin by extending the HealthCallback of Eureka-Server APIs.
Let Say Service-A register with Eureka. Hence Eureka Client is integrate with Service-A and Implement following Callbacks in Service A.
Service-A [Eureka-Client]
Add following properties in properties files.
#Eureka Configuration
eureka.client.eureka-server-port=8761
eureka.client.register-with-eureka=true
eureka.client.healthcheck.enabled=false
eureka.client.prefer-same-zone-eureka=true
eureka.client.fetchRegistry=true
eureka.client.serviceUrl.defaultZone=${eurekaServerURL1}, ${eurekaServerURL2}
eureka.client.eureka.service-url.defaultZone=${eurekaServerURL1}, ${eurekaServerURL2}
eureka.instance.hostname=${hostname}
eureka.client.lease.duration=30
eureka.instance.lease-renewal-interval-in-seconds=30
eureka.instance.lease-expiration-duration-in-seconds=30
Add following java files.
#Component
public class EurekaHealthCheckHandler implements HealthCheckHandler, ApplicationContextAware, InitializingBean {
static Logger logger = LoggerFactory.getLogger(EurekaHealthCheckHandler.class);
private static final Map<Status, InstanceInfo.InstanceStatus> healthStatuses = new HashMap<Status, InstanceInfo.InstanceStatus>() {{
put(Status.UNKNOWN, InstanceInfo.InstanceStatus.UNKNOWN);
put(Status.OUT_OF_SERVICE, InstanceInfo.InstanceStatus.OUT_OF_SERVICE);
put(Status.DOWN, InstanceInfo.InstanceStatus.DOWN);
put(Status.UP, InstanceInfo.InstanceStatus.UP);
}};
#Autowired
ComunocationService comunocationService ;
private final CompositeHealthIndicator healthIndicator;
private ApplicationContext applicationContext;
public EurekaHealthCheckHandler(HealthAggregator healthAggregator) {
Assert.notNull(healthAggregator, "HealthAggregator must not be null");
this.healthIndicator = new CompositeHealthIndicator(healthAggregator);
Health health = healthIndicator.health();
logger.info(" =========== Testing =========== {}", health.toString() );
}
#Override
public void setApplicationContext(ApplicationContext applicationContext) throws BeansException {
this.applicationContext = applicationContext;
}
#Override
public void afterPropertiesSet() throws Exception {
final Map<String, HealthIndicator> healthIndicators = applicationContext.getBeansOfType(HealthIndicator.class);
for (Map.Entry<String, HealthIndicator> entry : healthIndicators.entrySet()) {
logger.info("======"+ entry.getKey() +"============= "+entry.getValue());
healthIndicator.addHealthIndicator(entry.getKey(), entry.getValue());
}
}
#Override
public InstanceInfo.InstanceStatus getStatus(InstanceInfo.InstanceStatus instanceStatus) {
logger.info("============== Custome Eureka Implementation ==================="+ getHealthStatus());
return getHealthStatus();
}
protected InstanceInfo.InstanceStatus getHealthStatus() {
final Status status = healthIndicator.health().getStatus();
return mapToInstanceStatus(status);
}
protected InstanceInfo.InstanceStatus mapToInstanceStatus(Status status) {
logger.info("============== Test Custome Eureka Implementation ==================={}", status);
if(status.equals(InstanceInfo.InstanceStatus.UP)) {
// Send mail after configured times
comunocationService.sendEmail("ServiceName");
}
if(!healthStatuses.containsKey(status)) {
return InstanceInfo.InstanceStatus.UNKNOWN;
}
return healthStatuses.get(status);
}
public void getstatusChangeListner() {
ApplicationInfoManager.StatusChangeListener statusChangeListener = new ApplicationInfoManager.StatusChangeListener() {
#Override
public String getId() {
return "statusChangeListener";
}
#Override
public void notify(StatusChangeEvent statusChangeEvent) {
if (InstanceStatus.DOWN == statusChangeEvent.getStatus() ||
InstanceStatus.DOWN == statusChangeEvent.getPreviousStatus()) {
// log at warn level if DOWN was involved
logger.warn("Saw local status change event {}", statusChangeEvent);
} else {
logger.info("Saw local status change event {}", statusChangeEvent);
}
}
};
}
}
and
#Configuration
public class EurekaHealthCheckHandlerConfiguration {
#Autowired(required = false)
private HealthAggregator healthAggregator = new OrderedHealthAggregator();
#Bean
#ConditionalOnMissingBean
public EurekaHealthCheckHandler eurekaHealthCheckHandler() {
return new EurekaHealthCheckHandler(healthAggregator);
}
}
This is absolutely working and well tested code
i'm part of a team that is developing an application that uses the Fiware GE's has part of the Smart-AgriFood accelerator.
We are using the Orion Context Broker for gathering the data provided by the sensor network, and we intend to use the Pep-Proxy to authenticate the sensor node for access the Orion instance. We have tried the following pepProxy's:
https://github.com/telefonicaid/fiware-orion-pep
https://github.com/ging/fi-ware-pep-proxy
We only have success implementing the second (fi-ware-pep-proxy) implementation of the proxy. With the fiware-orion-pep we haven't been able to connect to the Keystone Global instance (account.lab.fi-ware.org), we have tried the account.lab... and the cloud.lab..., my question are:
1) is the keystone (IDM) instance for authentication the account.lab or the cloud.lab?? and what port's to use or address's?
2) is the fiware-orion-pep prepared for authenticate at the account.lab.fi-ware.org?? here is way i ask this:
This one works with the curl command at >> cloud.lab.fiware.org:4730/v2.0/tokens
{
"auth": {
"passwordCredentials": {
"username": "<my_user>",
"password": "<my_password>"
}
}
}'
This one does't work with the curl comand at >> account.lab.fi-ware.org:5000/v3/auth/tokens
{
"auth": {
"identity": {
"methods": [
"password"
],
"password": {
"user": {
"domain": {
"name": "<my_domain>"
},
"name": "<my_user>",
"password": "<my_password>"
}
}
}
} }'
3) what is the implementation that i should be using for authenticate the devices or other calls to the Orion instance???
Here are the configuration that i used:
fiware-orion-pep
config.authentication = {
checkHeaders: true,
module: 'keystone',
user: '<my_user>',
password: '<my_password>',
domainName: '<my_domain>',
retries: 3,
cacheTTLs: {
users: 1000,
projectIds: 1000,
roles: 60
},
options: {
protocol: 'http',
host: 'account.lab.fiware.org',
port: 5000,
path: '/v3/role_assignments',
authPath: '/v3/auth/tokens'
}
};
fi-ware-pep-proxy (this one works), i have set the listing port to 1026 at the source code
var config = {};
config.account_host = 'https://account.lab.fiware.org';
config.keystone_host = 'cloud.lab.fiware.org';
config.keystone_port = 4731;
config.app_host = 'localhost';
config.app_port = '10026';
config.username = 'pepProxy';
config.password = 'pepProxy';
// in seconds
config.chache_time = 300;
config.check_permissions = false;
config.magic_key = undefined;
module.exports = config;
Thanks in advance for the time ... :)
The are currently some differences in how both PEP Proxies authenticate and validate against the global instances, so they do not behave in exactly the same way.
The one in telefonicaid/fiware-orion-pep was developed to fulfill the PEP Proxy requirements (authentication and validation against a Keystone and Access Control) in individual projects with their own Keystone and Keypass (a flavour of Access Control) installations, and so it evolved faster than the one in ging/fi-ware-pep-proxy and in a slightly different direction. As an example, the former supports multitenancy using the fiware-service and fiware-servicepath headers, while the latter is transparent to those mechanisms. This development direction meant also that the functionality slightly differs from time to time from the one in the global instance.
That being said, the concrete answer:
- Both PEP Proxies should be able to contact the global instance. If one doesn't, please, fill a bug in the issues of the Github repository and we will fix it as soon as possible.
- The ging/fi-ware-pep-proxy was specifically designed for accessing the global instance, so you should be able to use it as expected.
Please, if you try to proceed with the telefonicaid/fiware-orion-pep take note also that:
- the configuration flag authentication.checkHeaders should be false, as the global instance does not currently support multitenancy.
- current stable release (0.5.0) is about to change to next version (probably today) so maybe some of the problems will solve with the update.
Hope this clarify some of your doubts.
[EDIT]
1) I have already install the telefonicaid/fiware-orion-pep (v 0.6.0) from sources and from the rpm package created following the tutorial available in the github. When creating the rpm package, this is created with the following name pep-proxy-0.4.0_next-0.noarch.rpm.
2) Here is the configuration that i used:
/opt/fiware-orion-pep/config.js
var config = {};
config.resource = {
original: {
host: 'localhost',
port: 10026
},
proxy: {
port: 1026,
adminPort: 11211
} };
config.authentication = {
checkHeaders: false,
module: 'keystone',
user: '<##################>',
password: '<###################>',
domainName: 'admin_domain',
retries: 3,
cacheTTLs: {
users: 1000,
projectIds: 1000,
roles: 60
},
options: { protocol: 'http',
host: 'cloud.lab.fiware.org',
port: 4730,
path: '/v3/role_assignments',
authPath: '/v3/auth/tokens'
} };
config.ssl = {
active: false,
keyFile: '',
certFile: '' }
config.logLevel = 'DEBUG'; // List of component
config.middlewares = {
require: 'lib/plugins/orionPlugin',
functions: [
'extractCBAction'
] };
config.componentName = 'orion';
config.resourceNamePrefix = 'fiware:';
config.bypass = false;
config.bypassRoleId = '';
module.exports = config;
/etc/sysconfig/pepProxy
# General Configuration
############################################################################
# Port where the proxy will listen for requests
PROXY_PORT=1026
# User to execute the PEP Proxy with
PROXY_USER=pepproxy
# Host where the target Context Broker is located
# TARGET_HOST=localhost
# Port where the target Context Broker is listening
# TARGET_PORT=10026
# Maximum level of logs to show (FATAL, ERROR, WARNING, INFO, DEBUG)
LOG_LEVEL=DEBUG
# Indicates what component plugin should be loaded with this PEP: orion, keypass, perseo
COMPONENT_PLUGIN=orion
#
# Access Control Configuration
############################################################################
# Host where the Access Control (the component who knows the policies for the incoming requests) is located
# ACCESS_HOST=
# Port where the Access Control is listening
# ACCESS_PORT=
# Host where the authentication authority for the Access Control is located
# AUTHENTICATION_HOST=
# Port where the authentication authority is listening
# AUTHENTICATION_PORT=
# User name of the PEP Proxy in the authentication authority
PROXY_USERNAME=XXXXXXXXXXXXX
# Password of the PEP Proxy in the Authentication authority
PROXY_PASSWORD=XXXXXXXXXXXXX
In the files above i have tried the following parameters:
Keystone instance: account.lab.fiware.org or cloud.lab.fiware.org
User: pep or pepProxy or "user from fiware account"
Pass: pep or pepProxy or "user password from account"
Port: 4730, 4731, 5000
The result it's the same as before... the telefonicaid/fiware-orion-pep is unable to authenticate:
log file at /var/log/pepProxy/pepProxy
time=2015-04-13T14:49:24.718Z | lvl=ERROR | corr=71a34c8b-10b3-40a3-be85-71bd3ce34c8a | trans=71a34c8b-10b3-40a3-be85-71bd3ce34c8a | op=/v1/updateContext | msg=VALIDATION-GEN-003] Error connecting to Keystone authentication: KEYSTONE_AUTHENTICATION_ERROR: There was a connection error while authenticating to Keystone: 500
time=2015-04-13T14:49:24.721Z | lvl=DEBUG | corr=71a34c8b-10b3-40a3-be85-71bd3ce34c8a | trans=71a34c8b-10b3-40a3-be85-71bd3ce34c8a | op=/v1/updateContext | msg=response-time: 50745 statusCode: 500
result from the client console
{
"message": "There was a connection error while authenticating to Keystone: 500",
"name": "KEYSTONE_AUTHENTICATION_ERROR"
}
I'm doing something wrong here??
I know that this question was already made in this post: Send email when error occurs in console command of Symfony2 app, but answers do not provide a complete solution to the problem at hand and I can't comment on original post.
I need to send a monolog error email in command. E-mail is correctly enqueued in a file spooler; unfortunately I'm forced to use a memory spool.
Strangely enough the code snipper provided to manually flush the spool does work for emails generated in my code, not for monolog.
Does anybody know why this is happening and wether it would be possible to use a memory spool?
config.yml:
# Swiftmailer Configuration
swiftmailer:
transport: %mailer_transport%
host: %mailer_host%
username: %mailer_user%
password: %mailer_password%
spool: { type: memory }
# Monolog Configuration
monolog:
channels: ["account.create"]
handlers:
account.create.group:
type: group
members: [account.create.streamed, account.create.buffered]
channels: [account.create]
account.create.streamed:
type: stream
path: %kernel.logs_dir%/accounts_creation.log
level: info
account.create.buffered:
type: buffer
handler: account.create.swift
account.create.swift:
type: swift_mailer
from_email: xxx#yyy.com
to_email: aaa#gmail.com
subject: 'An Error Occurred while managing zzz!'
level: critical
config_prod.yml:
monolog:
handlers:
main:
type: fingers_crossed
action_level: error
handler: nested
nested:
type: stream
path: %kernel.logs_dir%/%kernel.environment%.log
level: debug
channels: [!account.create]
usage example:
try
{
//code that could block
}
catch(ManageUserBlockingExceptionInterface $e)
{
$exitCode = self::EXIT_CODE_ERROR_BLOCKING;
//le eccezioni bloccanti vengono loggate e non si conferma che
//il messaggio รจ stato utilizzato ma si termina la coda
if(!\is_null($this->logger))
{
$this->logger->crit($e->getMessage());
}
}
the logger is injected in service by dependency injection as a service:
...
<argument type="service" id="monolog.logger.account.create" on-invalid="null" />
...
and it works because critical errors are streamed in file log; but also email is created if swiftmailer is configured with a file spool.
Finally, the code to manually flush memory spool is as folllow:
protected function flushMailSpool()
{
$mailer = $this->container->get('mailer');
$spool = $mailer->getTransport()->getSpool();
$transport = $this->container->get('swiftmailer.transport.real');
$spool->flushQueue($transport);
}
it is called immediately after a service purposedly sends an email; I noticed that the same code, put in command and adapted to command environment i.e. $this->container becomes $this->getContainer() does not work, maybe due to a scope change?
I am connecting to MongoDB while using the Scala Play! framework. I end up getting this timeout error:
! #6j672dke5 - Internal server error, for (GET) [/accounts] ->
play.api.Application$$anon$1: Execution exception[[MongoTimeoutException: Timed out while waiting to connect after 10000 ms]]
at play.api.Application$class.handleError(Application.scala:293) ~[play_2.10-2.2.1.jar:2.2.1]
at play.api.DefaultApplication.handleError(Application.scala:399) [play_2.10-2.2.1.jar:2.2.1]
at play.core.server.netty.PlayDefaultUpstreamHandler$$anonfun$12$$anonfun$apply$1.applyOrElse(PlayDefaultUpstreamHandler.scala:165) [play_2.10-2.2.1.jar:2.2.1]
at play.core.server.netty.PlayDefaultUpstreamHandler$$anonfun$12$$anonfun$apply$1.applyOrElse(PlayDefaultUpstreamHandler.scala:162) [play_2.10-2.2.1.jar:2.2.1]
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33) [scala-library-2.10.4.jar:na]
at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:185) [scala-library-2.10.4.jar:na]
Caused by: com.mongodb.MongoTimeoutException: Timed out while waiting to connect after 10000 ms
at com.mongodb.BaseCluster.getDescription(BaseCluster.java:131) ~[mongo-java-driver-2.12.3.jar:na]
at com.mongodb.DBTCPConnector.getClusterDescription(DBTCPConnector.java:396) ~[mongo-java-driver-2.12.3.jar:na]
at com.mongodb.DBTCPConnector.getType(DBTCPConnector.java:569) ~[mongo-java-driver-2.12.3.jar:na]
at com.mongodb.DBTCPConnector.isMongosConnection(DBTCPConnector.java:370) ~[mongo-java-driver-2.12.3.jar:na]
at com.mongodb.Mongo.isMongosConnection(Mongo.java:645) ~[mongo-java-driver-2.12.3.jar:na]
at com.mongodb.DBCursor._check(DBCursor.java:454) ~[mongo-java-driver-2.12.3.jar:na]
Here is my Scala code for connecting to the database:
//models.scala
package models.mongodb
//imports
package object mongoContext {
//context stuff
val client = MongoClient(current.configuration.getString("mongo.host").toString())
val database = client(current.configuration.getString("mongo.database").toString())
}
Here is the actual model that is making the connection:
//google.scala
package models.mongodb
//imports
case class Account(
id: ObjectId = new ObjectId,
name: String
)
object AccountDAO extends SalatDAO[Account, ObjectId](
collection = mongoContext.database("accounts")
)
object Account {
def all(): List[Account] = AccountDAO.find(MongoDBObject.empty).toList
}
Here's the Play! framework MongoDB conf information:
# application.conf
# mongodb connection details
mongo.host="localhost"
mongo.port=27017
mongo.database="advanced"
Mongodb is running on my local machine. I can connect to it by typing mongo at the terminal window. Here's the relevant part of the conf file:
# mongod.conf
# Where to store the data.
# Note: if you run mongodb as a non-root user (recommended) you may
# need to create and set permissions for this directory manually,
# e.g., if the parent directory isn't mutable by the mongodb user.
dbpath=/var/lib/mongodb
#where to log
logpath=/var/log/mongodb/mongod.log
logappend=true
#port = 27017
# Listen to local interface only. Comment out to listen on all interfaces.
#bind_ip = 127.0.0.1
So what's causing this timeout error and how do I fix it? Thanks!
I figured out that I needed to change:
val client = MongoClient(current.configuration.getString("mongo.host").toString())
val database = client(current.configuration.getString("mongo.database").toString())
to:
val client = MongoClient(conf.getString("mongo.host"))
val database = client(conf.getString("mongo.database"))