hdfs | A native go client for HDFS

 by   colinmarc Go Version: v2.3.0 License: MIT

kandi X-RAY | hdfs Summary

kandi X-RAY | hdfs Summary

hdfs is a Go library typically used in Web Services applications. hdfs has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

This is a native golang client for hdfs. It connects directly to the namenode using the protocol buffers API. It tries to be idiomatic by aping the stdlib os package, where possible, and implements the interfaces from it, including os.FileInfo and os.PathError.

            kandi-support Support

              hdfs has a medium active ecosystem.
              It has 1243 star(s) with 323 fork(s). There are 37 watchers for this library.
              It had no major release in the last 12 months.
              There are 24 open issues and 146 have been closed. On average issues are closed in 236 days. There are 8 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of hdfs is v2.3.0

            kandi-Quality Quality

              hdfs has no bugs reported.

            kandi-Security Security

              hdfs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              hdfs is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              hdfs releases are available to install and integrate.
              Installation instructions are not available. Examples and code snippets are available.

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            hdfs Key Features

            No Key Features are available at this moment for hdfs.

            hdfs Examples and Code Snippets

            No Code Snippets are available at this moment for hdfs.

            Community Discussions


            Getting java.lang.ClassNotFoundException when I try to do spark-submit, referred other similar queries online but couldnt get it to work
            Asked 2021-Jun-14 at 09:36

            I am new to Spark and am trying to run on a hadoop cluster a simple spark jar file built through maven in intellij. But I am getting classnotfoundexception in all the ways I tried to submit the application through spark-submit.

            My pom.xml:



            Answered 2021-Jun-14 at 09:36

            You need to add scala-compiler configuration to your pom.xml. The problem is without that there is nothing to compile your SparkTrans.scala file into java classes.


            Source https://stackoverflow.com/questions/67934425


            Does RDD re computation on task failure cause duplicate data processing?
            Asked 2021-Jun-12 at 18:37

            When a particular task fails that causes RDD to be recomputed from lineage (maybe by reading input file again), how does Spark ensure that there is no duplicate processing of data? What if the task that failed had written half of the data to some output like HDFS or Kafka ? Will it re-write that part of the data again? Is this related to exactly once processing?



            Answered 2021-Jun-12 at 18:37

            Output operation by default has at-least-once semantics. The foreachRDD function will execute more than once if there’s worker failure, thus writing same data to external storage multiple times. There’re two approaches to solve this issue, idempotent updates, and transactional updates. They are further discussed in the following sections

            Further reading


            Source https://stackoverflow.com/questions/67951826


            awk + how to get latest numbers in file but exclude number until 4 digit
            Asked 2021-Jun-09 at 16:37

            we have file like the following

            more file



            Answered 2021-Jun-09 at 09:41


            diagnostics: User class threw exception: org.apache.spark.sql.AnalysisException: path {PATH} already exists
            Asked 2021-Jun-09 at 14:28

            My code:



            Answered 2021-Jun-09 at 09:22

            Assuming outputFileName is a hdfs path ,could you pls check if that exists and try below

            Source https://stackoverflow.com/questions/67900536


            Hadoop NameNode Web Interface
            Asked 2021-Jun-09 at 14:18

            I have 3 remote computers (servers):

            • computer 1 has internal IP:
            • computer 2 has internal IP:
            • computer 3 has internal IP:

            (The 3 computers above are in the same network, these 3 computers are all using Ubuntu 18.04.5 LTS Operating System)

            (My personal laptop is in another different network, my laptop also uses Ubuntu 18.04.5 LTS Operating System)

            I use my personal laptop to connect to the 3 remote computers using SSH protocol and using user root : (Below ABC is a name)

            • computer 1: ssh root@ABC.University.edu.vn -p 12001
            • computer 2: ssh root@ABC.University.edu.vn -p 12002
            • computer 3: ssh root@ABC.University.edu.vn -p 12003

            I have successfully set up a Hadoop Cluster which contains 3 above computer:

            • computer 1 is the Hadoop Master
            • computer 2 is the Hadoop Slave 1
            • computer 3 is the Hadoop Slave 2


            I starts HDFS of the Hadoop Cluster by using the below command on Computer 1: start-dfs.sh

            Everything is successful:

            • computer 1 (the Master) is running the NameNode
            • computer 2 (the Slave 1) is running the DataNode
            • computer 3 (the Slave 2) is running the DataNode

            I know that the the Web Interface for the NameNode is running on Computer 1, on IP and on port 9870 . Therefore, if I open the web browser on computer 1 (or on computer 2, or on computer 3), I will enter the on the URL bar (address bar) of the web browser to see the Web Interface of the NameNode.


            Now, I am using the web browser of my personal laptop.

            How could I access to the Web Interface of the NameNode ?



            Answered 2021-Jun-08 at 17:56

            Unless you expose port 9870, your personal laptop on another network will not be able to access the web interface.

            You can check to see if it is exposed by trying :9870 to see if it is exposed. IP-address here has to be the global IP-address, not the local (10.* ) address.

            To get the NameNode's IP address, ssh into the NameNode server, and type ifconfig (sudo apt install ifconfig if not already installed - I'm assuming Ubuntu/Linux here). ifconfig should give you a global IP address (not the 255.* - that is a mask).

            Source https://stackoverflow.com/questions/67891388


            RDD in Spark: where and how are they stored?
            Asked 2021-Jun-09 at 09:45

            I've always heard that Spark is 100x faster than classic Map Reduce frameworks like Hadoop. But recently I'm reading that this is only true if RDDs are cached, which I thought was always done but instead requires the explicit cache () method.

            I would like to understand how all produced RDDs are stored throughout the work. Suppose we have this workflow:

            1. I read a file -> I get the RDD_ONE
            2. I use the map on the RDD_ONE -> I get the RDD_TWO
            3. I use any other transformation on the RDD_TWO


            if I don't use cache () or persist () is every RDD stored in memory, in cache or on disk (local file system or HDFS)?

            if RDD_THREE depends on RDD_TWO and this in turn depends on RDD_ONE (lineage) if I didn't use the cache () method on RDD_THREE Spark should recalculate RDD_ONE (reread it from disk) and then RDD_TWO to get RDD_THREE?

            Thanks in advance.



            Answered 2021-Jun-09 at 06:13

            In spark there are two types of operations: transformations and actions. A transformation on a dataframe will return another dataframe and an action on a dataframe will return a value.

            Transformations are lazy, so when a transformation is performed spark will add it to the DAG and execute it when an action is called.

            Suppose, you read a file into a dataframe, then perform a filter, join, aggregate, and then count. The count operation which is an action will actually kick all the previous transformation.

            If we call another action(like show) the whole operation is executed again which can be time consuming. So, if we want not to run the whole set of operation again and again we can cache the dataframe.

            Few pointers you can consider while caching:

            1. Cache only when the resulting dataframe is generated from significant transformation. If spark can regenerate the cached dataframe in few seconds then caching is not required.
            2. Cache should be performed when the dataframe is used for multiple actions. If there are only 1-2 actions on the dataframe then it is not worth saving that dataframe in memory.

            Source https://stackoverflow.com/questions/67894971


            Drop a hive table named "union"
            Asked 2021-Jun-08 at 20:19

            I am trying to drop a table names "union" but I keep getting an error. I am not sure who and how created that table, but nothing works on it, including describe or select. Using "hdfs dfs -ls" outside of hive, I can see that table exists and there is data in it, but cannot drop the table. I am assuming there may be a problem because the table is called "union" and the error I get is

            "cannot recognize input near 'union'".

            How can I drop the table?



            Answered 2021-Jun-08 at 20:18

            to escape in hive you can use bakctick:

            Source https://stackoverflow.com/questions/67893915


            query spark dataframe on max column value
            Asked 2021-Jun-08 at 12:06

            I have a hive external partitioned table with following data structure:



            Answered 2021-Jun-08 at 12:06

            max_version is of type org.apache.spark.sql.DataFrame its not Double. You have to extract value from the DataFrame.

            Check below code.

            Source https://stackoverflow.com/questions/67885952


            Hive load multiple partitioned HDFS file to table
            Asked 2021-Jun-08 at 08:04

            I have some twice-partitioned files in HDFS with the following structure:



            Answered 2021-Jun-08 at 08:04

            Typical solution is to build external partitioned table on top of hdfs directory:

            Source https://stackoverflow.com/questions/67879595


            Transfer files from one table to another in impala
            Asked 2021-Jun-05 at 13:32

            I have two tables in impala and I want to move the data from one to another. Both tables have hdfs path like



            Answered 2021-Jun-05 at 13:32

            It happens automatically and done by hive. When you do INSERT INTO table1 SELECT * FROM table2, hive copies data from /user/hive/db/table1 to table2/partitiona/partitionb/partitionc/file.
            You do not have to move anything. You may need to analyze table1 for better performance.

            Answer to your second question, if you use sort by while creating table1, then data will be automatically sorted by in table1 irrespective of data sorted or unsorted in table2.

            Source https://stackoverflow.com/questions/67847819

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install hdfs

            You can download it from GitHub.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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