Yes it's a big SIGH!!! I've tried 10s and 20s of different connection strings from trying to install older verison of Python (3.7.4) so I can install sasl and pyhive and basically everything I could find out there but it's still not working yet.    So, basically my setup is HIVE on Azure and the DB connections have server/host something like this "<server>.azurehdinsight.net" with port of 443. I'm using DBeaver to connect to the HIVE db and it's using JDBC URL - complete URL is something like this "jdbc:hive2://<server>.azurehdinsight.net:443/default;transportMode=http;ssl=true;httpPath=/hive2", so can someone please help me out with what packages I need in order for me to successfully query HIVE from Python?    @pudnik26354 - can you please post what worked for you? Thank you so much. ... View more

I know this is a bit late to post but i have a web app that scans the table and gets results based on the rowkey provided in the call so it needs to support multi threading, here's a snip of the scan:     try(ResultScanner scanner = myTable.getScanner(scan)) { for (Result result : scanner) { //logic of result.getValue() and result.getRow() } }     i just saw https://hbase.apache.org/1.2/devapidocs/org/apache/hadoop/hbase/client/Result.html is one of those classes that is not thread-safe among others mentioned in this article. Is there an example of a fully thread-safe hbase app that scans results based on the rowkey provided or anything similar? I'm looking for an efficient and good example i can use for reference. I am now concerned that this piece of code might not yield proper results when i get simultaneous requests. ... View more

Our installation had the password hash in another table.   update ambari.user_authentication set authentication_key='538916f8943ec225d97a9a86a2c6ec0818c1cd400e09e03b660fdaaec4af29ddbb6f2b1033b81b00' where user_id='1'     Note: user_id=1 was the admin in my case.   ... View more

This could be permission issue. you can see  the hive server2 log for the error. Log will be in /var/log/hive on the node to which you connect the hive  ... View more

You can try logging into the admin user and restart datanodes from the actions bar in Dashboard. That worked for me. May work for you too. ... View more

you should install ambari-server and ambari-agent on the first node wich you want to install hdfs service for example . the other nodes install ambari-agent only . dont forget to change (ambari-agent.ini ) hostname and the hosts file with (ip and hostname of all machines. ... View more

The DSN-less connection string below FINALLY worked for me, in windows 10. I created a file DSN, then copy/pasted the string into the python code, as a template.   Three lessons that I learned from this struggle:   1) kerberos is CASE SENSITIVE. Your kerberos realm in the string MUST be uppercase. 2) The Cloudera driver doesn't like spaces in between the semicolons in the string. Avoid them. 3) If you don't need connection pooling, turn it off with a pyodbc.pooling = False statement. import pyodbc strFileDSNAsAstring = "DRIVER=Cloudera ODBC Driver for Apache Hive;USEUNICODESQLCHARACTERTYPES=1; \ SSL=0;SERVICEPRINCIPALCANONICALIZATION=0;SERVICEDISCOVERYMODE=0;SCHEMA=database;PORT=port; \ KRBSERVICENAME=hive;KRBREALM=uppercaserealm;KRBHOSTFQDN=hostfqdndomain;INVALIDSESSIONAUTORECOVER=1; \ HOST=host;HIVESERVERTYPE=2;GETTABLESWITHQUERY=0;ENABLETEMPTABLE=0;DESCRIPTION=Hive; \ DELEGATEKRBCREDS=0;AUTHMECH=1;ASYNCEXECPOLLINTERVAL=100;APPLYSSPWITHQUERIES=1;CAIssuedCertNamesMismatch=1;" try: pyodbc.pooling = False conn = pyodbc.connect(strFileDSNAsAstring, autocommit=True) except: print("failure.") else: conn.close() print("success.") ... View more

with newer versions of spark, the sqlContext is not load by default, you have to specify it explicitly :   scala> val sqlContext = new org.apache.spark.sql.SQLContext(sc) warning: there was one deprecation warning; re-run with -deprecation for details sqlContext: org.apache.spark.sql.SQLContext = org.apache.spark.sql.SQLContext@6179af64 scala> import sqlContext.implicits._ import sqlContext.implicits._ scala> sqlContext.sql("describe mytable") res2: org.apache.spark.sql.DataFrame = [col_name: string, data_type: string ... 1 more field]  I'm working with spark 2.3.2 ... View more

Awesome.It worked for me. ... View more

Okay so I wrote an example nifi process to do it   https://www.datainmotion.dev/2020/01/flank-stack-nifi-processor-for-kafka.html ... View more