The Hive Server Ip Java

[Gibert Chisholm]

NoI completely disagree with this. Java and bedrock are made from different programs and this can cause crashes and chances of bad anti-cheat. Bedrock and java were meant to be different and not together and it always has been. Java is Java and bedrock is bedrock. This may also shut down MC because both softwares are not meant to be together.

tbh bedrock players could be even more experienced, especially the sweats, i play java and i know

to be honest, adding geysermc to hive could be cool, what about a plugin that allows java players to join hive bedrock

I have been working on creating a new cluster "Cloudera Manager (Trial) 7.4.4". After installing hue I couldn't see hive editor and got to know we need hive on tez. So I installed hive on tex with one hiveserver and deleted hive server on hive. Now when I start the service my hiveserver in hive on tez goes down. Please help me with this.

Just a quick question, I have used CDH 5 and if I just give hive it will open the shell. Now for CDH 7 if I just give hive its opening beeline and says no current connection. But I now open with "beeline -u jdbc:hive2://ip-40-0-21-143.us-west-2.compute.internal:10000 -n hive" which is working I think.

could you please attach complete hiveserver2 logs, it looks hs2 is not able to create zknode, this could be kerberos issue if you running in secure env or there might be zookeeper database inconsisency.

We have a request to bring in data using a Hive (Hadoop) data for our customers. We've been successfully able to import data using a java script and the jar file hive-jdbc-1.2.1-standalone.jar (This is loaded on the mid-server). This method would require us to setup a non-standard way of connecting to a JDBC data source.

As a followup I didn't need to activate the JDBCProbe to get this to work. I had to upload a newer version of the jar file, and it resolve this issue. The existing jar source code was executing a method the data source was invoking with a call to one of the methods. For some reason the Java didn't know how to handle it.

If I have answered your question, please mark my response as correct so that others with the same question in the future can find it quickly and that it gets removed from the Unanswered list.

The java errors go on for as long as the screen goes.

The queries and the tables work fine while querying Hive directly or connecting via JDBC with DBeaver. Also, the health of the HDFS, Hive metastore and server all appear ok from Ambari, in case this matters.

I hope someone has dealt with something like this before and could help a newbie out. Thanks in advance.

It may be possible this could also be an access issue that we report this way. I can take a look at your log file and confirm. But even before that if you sure the logged in user has access to this Hive table, then we had a bug prior to 3.2.6 where we used to cache invalid permissions and even after the user got permission we would fail the query, have you tried to restart the coordinator? Also, good idea to move up to 4.1. Send me the server.log anyways

In branch-1, Hive supports both Hadoop 1.x and 2.x. You will need to specify which version of Hadoop to build against via a Maven profile. To build against Hadoop 1.x use the profile hadoop-1; for Hadoop 2.x use hadoop-2. For example to build against Hadoop 1.x, the above mvn command becomes:

HiveServer2 (introduced in Hive 0.11) has its own CLI called Beeline. HiveCLI is now deprecated in favor of Beeline, as it lacks the multi-user, security, and other capabilities of HiveServer2. To run HiveServer2 and Beeline from shell:

Starting with release 0.7, Hive also supports a mode to run map-reduce jobs in local-mode automatically. The relevant options are hive.exec.mode.local.auto, hive.exec.mode.local.auto.inputbytes.max, and hive.exec.mode.local.auto.tasks.max:

So for queries over small data sets, or for queries with multiple map-reduce jobs where the input to subsequent jobs is substantially smaller (because of reduction/filtering in the prior job), jobs may be run locally.

Note that there may be differences in the runtime environment of Hadoop server nodes and the machine running the Hive client (because of different jvm versions or different software libraries). This can cause unexpected behavior/errors while running in local mode. Also note that local mode execution is done in a separate, child jvm (of the Hive client). If the user so wishes, the maximum amount of memory for this child jvm can be controlled via the option hive.mapred.local.mem. By default, it's set to zero, in which case Hive lets Hadoop determine the default memory limits of the child jvm.

Hive uses log4j for logging. By default logs are not emitted to the console by the CLI. The default logging level is WARN for Hive releases prior to 0.13.0. Starting with Hive 0.13.0, the default logging level is INFO.

Hive also stores query logs on a per Hive session basis in /tmp//, but can be configured in hive-site.xml with the hive.querylog.location property. Starting with Hive 1.1.0, EXPLAIN EXTENDED output for queries can be logged at the INFO level by setting the hive.log.explain.output property to true.

Logging during Hive execution on a Hadoop cluster is controlled by Hadoop configuration. Usually Hadoop will produce one log file per map and reduce task stored on the cluster machine(s) where the task was executed. The log files can be obtained by clicking through to the Task Details page from the Hadoop JobTracker Web UI.

From Hive 2.1.0 onwards (with HIVE-13027), Hive uses Log4j2's asynchronous logger by default. Setting hive.async.log.enabled to false will disable asynchronous logging and fallback to synchronous logging. Asynchronous logging can give significant performance improvement as logging will be handled in a separate thread that uses the LMAX disruptor queue for buffering log messages. Refer to for benefits and drawbacks.

An audit log has the function and some of the relevant function arguments logged in the metastore log file. It is logged at the INFO level of log4j, so you need to make sure that the logging at the INFO level is enabled (see HIVE-3505). The name of the log entry is "HiveMetaStore.audit".

In order to obtain the performance metrics via the PerfLogger, you need to set DEBUG level logging for the PerfLogger class (HIVE-12675). This can be achieved by setting the following in the log4j properties file.

creates a table called invites with two columns and a partition column called ds. The partition column is a virtual column. It is not part of the data itself but is derived from the partition that a particular dataset is loaded into.

Note that REPLACE COLUMNS replaces all existing columns and only changes the table's schema, not the data. The table must use a native SerDe. REPLACE COLUMNS can also be used to drop columns from the table's schema:

Metadata is in an embedded Derby database whose disk storage location is determined by the Hive configuration variable named javax.jdo.option.ConnectionURL. By default this location is ./metastore_db (see conf/hive-default.xml).

Metastore can be stored in any database that is supported by JPOX. The location and the type of the RDBMS can be controlled by the two variables javax.jdo.option.ConnectionURL and javax.jdo.option.ConnectionDriverName. Refer to JDO (or JPOX) documentation for more details on supported databases. The database schema is defined in JDO metadata annotations file package.jdo at src/contrib/hive/metastore/src/model.

Loads a file that contains two columns separated by ctrl-a into pokes table. 'LOCAL' signifies that the input file is on the local file system. If 'LOCAL' is omitted then it looks for the file in HDFS.

The above command will load data from an HDFS file/directory to the table.

Note that loading data from HDFS will result in moving the file/directory. As a result, the operation is almost instantaneous.

selects all rows from partition ds=2008-08-15 of the invites table into an HDFS directory. The result data is in files (depending on the number of mappers) in that directory.

NOTE: partition columns if any are selected by the use of *. They can also be specified in the projection clauses.

"[Cloudera][HiveJDBCDriver](500164) Error initialized or created transport for authentication: [Cloudera][HiveJDBCDriver](500169) Unable to connect to server: Failure to initialize security context."

We are using the Cloudera Hive JDBC v2.6.5 driver. It has all the dependencies bundled into one jar as I understand it. We placed this into the DB Connect driver directory. We then created the "db_connection_types.conf" file in the local directory and added a stanza for the new driver.

DB Connect recognizes the driver however when we attempt to save the connection we receive a failure. If we try to move past saving the connection and try to retrieve data we receive a connection error.

If I were to start the process again I would install the newest version of DB Connect compatible with existing version of Splunk. Download OpenJDK v8, extract and copy it into a directory (C:\Program Files\Java\java-se-8u41-ri). Then create a JAVA_HOME system environment variable and place that directory inside as the value. Reboot the server. You may then need to manually update the "JRE Installation Path" field in DB Connects Configuration -> Settings -> General tab and Save. Then reboot Splunk web via Settings -> Server Controls. Once there are no more errors popping up, download the Cloudera driver and move it into the DB Connect "drivers" directory (\splunk_app_db_connect\drivers). Go to the Configuration -> Settings -> Drivers tab and click reload. The driver should now exist on the page and have a green check mark next to it along with the version. Install Kerberos MIT. Create a connection in DB Connect and setup a connection string in the "JDBC URL" field with something like...

3a8082e126