I'm trying to use MonetDB in Python to perform some tasks on a huge dataframe. I've installed the suggested API and it has successfully loaded. But when I try to establish the connection, I always get the same error:
[Errno 10061] No connection could be made because the target machine actively refused it
In my research, people have said that I need to set the same port between client and server. But I don't know what this means or how to do it. I've tryed many variations, but the basic structure I've been using is the one provided in the documentation:
connection = pymonetdb.connect(database = 'Main_Database', username="monetdb", password="monetdb", hostname="localhost")
I'd like to get to the point where my CSV dataframe is fully loaded and I can start doing operations with it.
Related
I am trying to connect to my Exasol SaaS database, I tried via these tools(TALEND, DBVISUALIZER, POWERBI) and via python but I cannot connect and I keep getting the same error.
I saw another post on Exasol community https://community.exasol.com/t5/discussion-forum/exaconnectionfailederror/m-p/8049#M1855 of this type of error but it doesn't explain exactly what was done to fix the error. I tried via the ODBC Data Source administrator(64-bit) too but still the same error. Maybe its an connection issue with my pc self but I'm not sure or maybe I am just inserting wrong values I don't know.
Oh the values I inserted are the recommended ones from what Exasol docs states and I have removed anything about proxy or vpn.
I put my errors under. I tried via different devices and I get the same error I really don't know what I can do any more, so any help will be greatly appreciated.
Note: I am using the Exasol SaaS database and I am currently on the trial mode so I am not sure if this is limiting me.
**Errors: **
Error message odbc exasol: [EXASOL][EXASolution driver]connection attempt timed out.
Error message Talend : Connection failure. You must change the Database Settings.
java.lang.RuntimeException: com.exasol.jdbc.ConnectFailed: connect timed out ->
Caused by: com.exasol.jdbc.ConnectFailed: connect timed out
Error message pyexasol : socket.timeout: timed out
Error message dbvisualizer : java.net.SocketTimeoutException: Connect timed out com.exasol.jdbc.ConnectFailed: java.net.SocketTimeoutException: Connect timed out
Error message Power BI desktop : Details: "ODBC: ERROR [HYT00][EXASOL][EXASolution driver]Connection attempt timed out."
My applications versions:
DbVisualizer Free 14.0.1 (build: 3540)
Talend Open Studio Data integration(8.0.1.2021119_1610)
java version -> jdk-16.0.02
Power BI -> Version: 2.110.1085.0 64-bit (October 2022)
ODBC : exasolodbc x64 7.1.14
JDBC : exasoljdbc 7.1.14
Python: python 3.8.10 -> pyexasol : 0.25.1
The error means that the client is not able to reach the host for some reason. Try the following:
Make sure the database is still online (they auto-shutdown after 2 hours if there is no activity by default)
Check that the IP Address of the host you are connecting with is added to the allow list in the SaaS UI. (see the docs)
Check if your host is able to reach the host and port specified in the SaaS UI (for example using telnet on port 8563). Maybe some firewall is preventing access to the database?
So I did more digging. actually I have no idea what the issue was.
Talend:
I made a connection via JDBC in Talend with the help of exasol-support. The DBType Exasol in talend doesn't work for some reason, its not known if it's talend side or Exasol side, maybe this will be updated in the future. Just remember in the jdbc url type this: "jdbc:exa:yourconnectionstring", don't forget the "exa".
PowerBI:
I tried the connection string with fingerprint method that worked for me. Just put the fingerprint with the connection string and it should connect.
https://exasol.my.site.com/s/article/PowerBI-Encryption-Fingerprint-Issue-in-Exasol-7-1?language=en_US
DBvisualizer:
I had a wrong in connection string.
Python:
I had a wrong in connection string.
Hopefully this helps someone.
I am very new to Elasticsearch and want to analyze data in python.
I installed Elasticsearch pip and tried to import data but failed with error messages
es = Elasticsearch([{'hosts':'10.251.0.135', 'port':'5601'}])
es.info()
> ConnectionError: ConnectionError(<urllib3.connection.HTTPConnection object at 0x000001AD21943460>: Failed to establish a new connection: [WinError 10061] caused by: NewConnectionError(<urllib3.connection.HTTPConnection object at 0x000001AD21943460>: Failed to establish a new connection: [WinError 10061]
or
es = Elasticsearch("http://10.251.0.134:5601/")
es.info()
> TransportError: TransportError(302, '')
I looked out some solutions but they kinda assume that I have Elasticsearch in my local machine, which in my case isn't much helpful.
I don't think I am not authorized to access the data as I can access to data through web-hosting Kibana app. Hope to know what would be the problem.
Thanks to leandrojmp, I manage to find the answer.
My situation was:
At work, needed to retrieve Elasticsearch server data to python.
I was the only analyst and others see data through kibana(5601).
No Elasticsearch or Kibana installed on my local machine, so the advice like change configuration doesn't seems to match.
The error was as stated on the question
How I manage to figure out:
I went to port 9200 on the browser, which is direct access to Elasticsearch DB and find out that I only have access to port 5601, not 9200.
Asked Server manager to disable the firewall, and everything works find :)
I am writing an app with wxPython that incorporates pyodbc to access SQL Server. A user must first establish a VPN connection before they can establish a connection with the SQL server. In cases where a user forgets to establish a VPN connection or is simply not authorized to access a particular server, the app will freeze for up to 60+ seconds before it produces an error message. Often, users will get impatient and force-close the app before the error message pops up.
I wonder if there is a way to test whether it's possible to connect to the server without freezing up. I thought about using timeout, but it seems that timeout can be used only after I establish a connection
A sample connection string I use is below:
connection = pyodbc.connect(r'DRIVER={SQL Server};SERVER=ServerName;database=DatabaseName;Trusted_Connection=True;unicode_results=True')
See https://code.google.com/archive/p/pyodbc/wikis/Connection.wiki under timeout
Note: This attribute only affects queries. To set the timeout for the
actual connection process, use the timeout keyword of the
pyodbc.connect function.
So change your connection string to:
connection = pyodbc.connect(r'DRIVER={SQL Server};SERVER=ServerName;database=DatabaseName;Trusted_Connection=True;unicode_results=True', timeout=3)
should work
took a while before it threw an error message about server not existing or access being denied
Your comment conflates two very different kinds of errors:
server not existing is a network error. Either the name has no address, or the address is unreachable. No connection can be made.
access being denied is a response from the server. For the server to respond, a connection must exist. This is not to be confused with connection refused (ECONNREFUSED), which means the remote is not accepting connections on the port.
SQL Server uses TCP/IP. You can use standard network functions to determine if the network hostname of the machine running SQL Server can be found, and if the IP address is reachable. One advantage to using them to "pre-test" the connection is that any error you'll get will be much more specific than the typical there was a problem connecting to the server.
Note that not all delay-inducing errors can be avoided. For example, if the DNS server is not responding, the resolver will typically wait 30 seconds before giving up. If an IP address is valid, but there's no machine with that address, attempting a connection will take a long time to fail. There's no way for the client to know there's no such machine; it could just be taking a long time to get a response.
An error is repeatedly being thrown at this line:
client = MongoClient('ec2-12-345-67-89.us-east-2.compute.amazonaws.com', 27017,
ssl=True, ssl_keyfile='C:\\mongo.pem')
(Paths and instance name changed for obvious reasons)
The port (27017) for mongo is allowed inbound connections from my AWS security group. First, I allowed only my IP, now I'm allowing all via that port. I have tried preceding the connection string with "mongodb://" and removing the SSL arguments (I'm fairly certain I don't need it).
The error IntelliJ keeps throwing me is:
pymongo.errors.ConnectionFailure: [WinError 10061] No connection could be made because the target machine actively refused it
It works if I transport the script to the AWS instance and replace the DNS with 'localhost' and remove SSL parameters, but I need this to work remotely.
Three ideas:
Ensure "bind_ip" is set to "0.0.0.0" in your mongod.conf and restart mongod, as #ajduke suggests.
Make sure mongod is running.
Try to connect to the mongod from your client machine using the "mongo" shell to see if it gives you a more informative error.
I am using redisbayes library in python to implement naive bayes classification. But when I write -
rb = redisbayes.RedisBayes(redis=redis.Redis())
rb.train('good', 'sunshine drugs love sex lobster sloth')
It gives the following error -
ConnectionError: Error 10061 connecting localhost:6379.
No connection could be made because the target machine actively refused it.
I tried doing it this way -
pool = redis.ConnectionPool(host='localhost', port=6379, db=0)
rb = redisbayes.RedisBayes(redis=redis.Redis(connection_pool=pool))
But it gives the same error. I am not being able to find a solution to this. How can I establish a connection to redis using python, or this any other way to do naive bayes classification in python using training data from MySQL?
You do realise you need to have a Redis server running locally to be able to connect to it, take a look in your process list for redis-server if its not there and you don't have a registered service you might need to install it. Take a look at the installation instructions on the redis homepage