@Anibal_Linares    Can you please execute below command manually see what exact issue it's facing   'export HIVE_CONF_DIR='/usr/hdp/current/hive-metastore/conf' ; hive --hiveconf hive.metastore.uris=thrift://p-ods-admin-02.transbank.local:9083 --hiveconf hive.metastore.client.connect.retry.delay=1 --hiveconf hive.metastore.failure.retries=1 --hiveconf hive.metastore.connect.retries=1 --hiveconf hive.metastore.client.socket.timeout=14 --hiveconf hive.execution.engine=mr -e 'show databases;   I think is issue with Hive Client, try to reinstall on the node where this command is executing ... View more

@Selene Have each account for each service is more secure because each account have it's own unix groups and privileges. Think of this way if one account got issue, complete ecosystem will in problem and secondly account id's like hdfs, yarn have there own privileges of permissions to execute few commands which can't be shared.  Think of today's modernized applications how each of them are running as macro services.    Technically speaking we can do it but you need to rewrite alot of code if you prefer to do. My suggestion go with service account. ... View more

@Sai2222  Yes, it can be change  globally by adding it in the Oozie properties. export   PIG_HEAPSIZE=2096   My suggestion of making change global for one job failure is not a good reason because it unnecessarily take some memory even though it's not required in each execution.  ... View more

@kumar993498 : A mazon Athena uses Presto, supports a wide variety of data formats like CSV, TSV, JSON, or Textfiles and also supports open source columnar formats such as Apache ORC and Apache Parquet. Athena also supports compressed data in Snappy, Zlib, LZO, and GZIP formats. By compressing, partitioning, and using columnar formats you can improve performance and reduce your costs.   following SerDes: Apache Web Logs: "org.apache.hadoop.hive.serde2.RegexSerDe" CSV: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe" TSV: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe" Custom Delimiters: "org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe" Parquet: "org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe" Orc: "org.apache.hadoop.hive.ql.io.orc.OrcSerde" JSON: “org.apache.hive.hcatalog.data.JsonSerDe” OR org.openx.data.jsonserde.JsonSerDe Hope this helps you.  ... View more

@crisbcw : I can think of one option which I have used around 15months ago: If you are using Ranger, from ranger audit logs we can get the tables which are used for last n days and compare with tables with existing tables.  ... View more

@HadoopHelp    Below links will help to achieve your request, please go check and make appropriate configurations.  https://community.cloudera.com/t5/Community-Articles/How-to-Configure-Authentication-with-WASB/ta-p/246004   https://hadoop.apache.org/docs/stable/hadoop-azure/index.html#Protecting_the_Azure_Credentials_for_WASB_with_Credential_Providers   If you want to move data with HDFS instead of using blob storage, you can configure cross cluster configuration and provide network access on VNET. ... View more

@mdh_raghavendra: I think there is no way to update the existing key with length because the data which is using that 128 length will be invalidate. For best practice you have create a new key with 256 length and copy the data though NN to use the newly created 256 length.   Hope this helps you.   Thanks, Sridhar. ... View more

@PentaReddy: I guess table is not getting dropped. Please run repair statement and the run select statement to retrive the data.    MSCK [REPAIR] TABLE table_name [ADD/DROP/SYNC PARTITIONS];   ... View more

@vishal dutt Yup, you need to create them on all the nodes. If you are using the LDAP, please bind those nodes to LDAP so that if you do id janu all the nodes you should able to see her id. ... View more

@vishal dutt When you run the 1st query it's not triggering any MapReduce program. It's directly reading the data but when you define a logic it's triggering mapreduce program to perform aggregations. When it's running mapreduce program, user id need to be present on all the Resource Managers. Hope this helps you and let me know if you need any further information. ... View more

@John Adams While running ambari-server setup --jdbc-db=mysql --jdbc-driver=/path/to/mysql/mysql-connector-java.jar you need to find where mysql-connector-java.jar is located and point to that directory. Below URL will help you. https://docs.hortonworks.com/HDPDocuments/Ambari-2.6.0.0/bk_ambari-administration/content/using_ambari_with_mysql.html Database Requirements Ambari requires a relational database to store information about the cluster configuration and topology. If you install HDP Stack with Hive or Oozie, they also require a relational database. The following table outlines these database requirements: Component Databases Description Ambari PostgreSQL 9.1.13+,9.3, 9.4*** MariaDB 10.2.9* MySQL 5.7**** Oracle 11gr2 Oracle 12c** By default, Ambari installs an instance of PostgreSQL on the Ambari Server host. Hortonworks supports any version of Postgres that is automatically installed during the Ambari Server installation. Optionally, you can use an existing instance of PostgreSQL, MySQL or Oracle and the versions of supported existing database instances are listed here. Support Versions: https://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.6.5/bk_support-matrices/content/ch_matrices-ambari.html Hope this helps. ... View more

@Josh Nicholson If you are storing your Ranger Hive logs to HDFS and running doAs=false, you can build a hive table on to of ranger-hive logs and start querying. Example: select requser,count(*) from ranger_audit_event_json_tmp where TO_DATE(evttime)>='2018-05-10' group by requser; Above query gives you number queries ran by with respective to each user from 2018-05-10. Couple of links for creating tables: https://docs.hortonworks.com/HDPDocuments/Ambari-2.6.0.0/bk_ambari-operations/content/amb_infra_arch_n_purge_command_line_operations.html https://community.hortonworks.com/articles/60802/ranger-audit-in-hive-table-a-sample-approach-1.html This worked for me, hope this helps you ... View more

@Venkat Metastore connection options: Argument Description --meta-connect <jdbc-uri> Specifies the JDBC connect string used to connect to the metastore By default, a private metastore is instantiated in $HOME/.sqoop. If you have configured a hosted metastore with the sqoop-metastore tool, you can connect to it by specifying the --meta-connect argument. This is a JDBC connect string just like the ones used to connect to databases for import. In conf/sqoop-site.xml, you can configure sqoop.metastore.client.autoconnect.url with this address, so you do not have to supply --meta-connect to use a remote metastore. This parameter can also be modified to move the private metastore to a location on your filesystem other than your home directory. If you configure sqoop.metastore.client.enable.autoconnect with the value false, then you must explicitly supply --meta-connect. Hope this helps ... View more

@Mike Wong Yes ... View more

@Mike Wong When you restart the Services, it should automatically get updated if you have added the disk to the same mount. ... View more

@Bharath N Try to perform the following steps on the failed DataNode: Get the list of DataNode directories from /etc/hadoop/conf/hdfs-site.xml using the following command: $ grep -A1 dfs.datanode.data.dir /etc/hadoop/conf/hdfs-site.xml <name>dfs.datanode.data.dir</name> <value>/data0/hadoop/hdfs/data,/data1/hadoop/hdfs/data,/data2/hadoop/hdfs/data, /data3/hadoop/hdfs/data,/data4/hadoop/hdfs/data,/data5/hadoop/hdfs/data,/data6/hadoop/hdfs/data, /data7/hadoop/hdfs/data,/data8/hadoop/hdfs/data,/data9/hadoop/hdfs/data</value> Get datanodeUuid by grepping the DataNode log: $ grep "datanodeUuid=" /var/log/hadoop/hdfs/hadoop-hdfs-datanode-$(hostname).log | head -n 1 | perl -ne '/datanodeUuid=(.*?),/ && print "$1\n"' 1dacef53-aee2-4906-a9ca-4a6629f21347 Copy over a VERSION file from one of the <dfs.datanode.data.dir>/current/ directories of a healthy running DataNode: $ scp <healthy datanode host>:<dfs.datanode.data.dir>/current/VERSION ./ Modify the datanodeUuid in the VERSION file with the datanodeUuid from the above grep search: $ sed -i.bak -E 's|(datanodeUuid)=(.*$)|\1=1dacef53-aee2-4906-a9ca-4a6629f21347|' VERSION Blank out the storageID= property in the VERSION file: $ sed -i.bak -E 's|(storageID)=(.*$)|\1=|' VERSION Copy this modified VERSION file to the current/ path of every directory listed in dfs.datanode.data.dir property of hdfs-site.xml: $ for i in {0..9}; do cp VERSION /data$i/hadoop/hdfs/data/current/; done Change permissions on this VERSION file to be owned by hdfs:hdfs with permissions 644: $ for i in {0..9}; do chown hdfs:hdfs /data$i/hadoop/hdfs/data/current/VERSION; done $ for i in {0..9}; do chmod 664 /data$i/hadoop/hdfs/data/current/VERSION; done One more level down, there is a different VERSION file located under the Block Pool current folder at: /data0/hadoop/hdfs/data/current/BP-*/current/VERSION This file does not need to be modified -- just place then in the appropriate directories. Copy over this particular VERSION file from a healthy DataNode into the current/BP-*/current/ folder for each directory listed in dfs.datanode.data.dir of hdfs-site.xml: $ scp <healthy datanode host>:<dfs.datanode.data.dir>/current/BP-*/current/VERSION ./VERSION2 $ for i in {0..9}; do cp VERSION2 /data$i/hadoop/hdfs/data/current/BP-*/current/VERSION; done Change permissions on this VERSION file to be owned by hdfs:hdfs with permissions 644: $ for i in {0..9}; do chown hdfs:hdfs /data$i/hadoop/hdfs/data/current/BP-*/current/VERSION; done $ for i in {0..9}; do chmod 664 /data$i/hadoop/hdfs/data/current/BP-*/current/VERSION; done Restart DataNode from Ambari. The VERSION file located at <dfs.datanode.data.dir>/current/VERSION will have its storageID repopulated with a regenerated ID. If any data is not an issue (say, for example, the node was previously in a different cluster, or was out of service for an extended time), then delete all data and directories in the dfs.datanode.data.dir (keep that directory, though), restart the data node daemon or servic ... View more

@vishal dutt Spark driver is not able to find the sqljdbc.jar in class path. When using spark-submit , the application jar along with any jars included with the --jars option will be automatically transferred to the cluster. URLs supplied after --jars must be separated by commas. That list is included in the driver and executor classpaths. Directory expansion does not work with --jars . Else 1) Provide the spark.driver.extraClassPath =/usr/hdp/hive/lib/mysql-connector-java.jar 2) Provide the spark.executor.extraClassPath = /usr/hdp/hive/lib/mysql-connector-java.jar. 3) Add Sqljdbc.jar to the Spark Classpath or add it using -jar option. Hope this helps you. ... View more

@Jorge Florencio Hope this article would help you: https://docs.hortonworks.com/HDPDocuments/Ambari-2.6.1.5/bk_ambari-upgrade-ppc/content/upgrading_log_rotation_configuration.html If you are planning to change through log4j, even below article is good. https://community.hortonworks.com/articles/8882/how-to-control-size-of-log-files-for-various-hdp-c.html Hope this helps you. ... View more

@Alpesh Virani Please try to use Ranger. You should be able to do that: Hope this link helps you : https://hortonworks.com/blog/best-practices-for-hive-authorization-using-apache-ranger-in-hdp-2-2/ ... View more

@Lokesh Mukku Seems like root user doesn't have HDFS home directory. Please create HDFS home for root user and try again. It should work. Below are steps to create home directory: sudo -u hdfs hadoop fs -mkdir /user/root sudo -u hdfs hadoop fs -chown root /user/root ... View more

@Sami Ahmad Using Phoenix: Use Salting to increase read/write performance Salting can significantly increase read/write performance by pre-splitting the data into multiple regions. Although Salting will yield better performance in most scenarios. Example: CREATE TABLE TEST (HOST VARCHAR NOT NULL PRIMARY KEY, DESCRIPTION VARCHAR) SALT_BUCKETS=16 Note: Ideally for a 16 region server cluster with quad-core CPUs, choose salt buckets between 32-64 for optimal performance. Per-split table Salting does automatic table splitting but in case you want to exactly control where table split occurs with out adding extra byte or change row key order then you can pre-split a table. Example: CREATE TABLE TEST (HOST VARCHAR NOT NULL PRIMARY KEY, DESCRIPTION VARCHAR) SPLIT ON ('CS','EU','NA') Use multiple column families Column family contains related data in separate files. If you query use selected columns then it make sense to group those columns together in a column family to improve read performance. Example: Following create table DDL will create two column faimiles A and B. CREATE TABLE TEST (MYKEY VARCHAR NOT NULL PRIMARY KEY, A.COL1 VARCHAR, A.COL2 VARCHAR, B.COL3 VARCHAR) Article: https://hortonworks.com/blog/apache-hbase-region-splitting-and-merging/ ... View more

@pk reddy Seems like it's unable to assign resources. Please check resource utilization. ... View more

@vishal dutt Glad your problem is fixed ... View more