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01-11-2016
10:37 PM
It looks like Ambari uses headless keytab for Spark history server: Execute['/usr/bin/kinit -kt /dsap/etc/security/keytabs/spark.headless.keytab spark-abc@EXAMPLE.COM; '] {'user': 'spark'} Does anyone know why? Also current documentation suggests that we need to create keytabs on host as described here: http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.3.2/bk_spark-guide/content/ch_installing-kerb-spark.html This is somehow confusing.
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Apache Spark
12-10-2015
10:24 PM
Thanks for comment @Ali Bajwa Did you try Hive ODBC v2.0.5? (just want to double check)
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12-10-2015
04:40 AM
There was a tutorial that covers the configuration with older Knox version and Hive ODBC driver. http://hortonworks.com/hadoop-tutorial/secure-jdbc-odbc-clients-access-hiveserver2-using-apache-knox/ For Hive ODBC v2.0.5, does the same solution work with HDP 2.3.2 (Knox 0.5)? Or, do we have any known issues?
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Apache Hive
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Apache Knox
11-03-2015
11:21 PM
Spout try to query zookeeper to get the state and set the offset to prior location. We have retention policy of three days in kafka. So I guess offset moves back to location which does not exists in kafka and its does not pull anymore data. Already checked that in the spout config, the Zookeeper configuration is pointing to Kafka ZooKeeper. Anything else that we're missing here? Thank you.
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Apache Kafka
10-29-2015
01:12 AM
In the current production environment we have 20 data nodes. We are using Sqoop to import data from Netezza into Hadoop. We opened firewall between the Netezza server and the 20 data nodes for Sqoop to work.
We are planning to add 40 new data nodes. For Sqoop functionality not to break, we need to open new firewall rules for all the new nodes. We are also getting requests to import data from other databases such as Teradata and Oracle into Hadoop.
As we have firewalls in place, it is hard to maintain firewall rules between the databases and individual data nodes.
Are there any alternative solutions to this problem, for example using a gateway node.
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Apache Sqoop
10-19-2015
10:26 PM
2 Kudos
Is there any bug filed? There are quite some users are hitting this issue I think.
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10-19-2015
10:15 PM
2 Kudos
I'm seeing this too. Haven't found any JIRA on this.
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10-15-2015
06:40 AM
The situation is that disk space has been pretty much used up. And we found the data size under HDFS folder '/apps/hbase/data/.hbck' is quite large. We're thinking of removing these data but not sure if it's good or not? I think these data are the backup for offline meta repair. If my understanding is correct, removing the data means we don't have the option to do offline meta repair later on.
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Apache HBase
10-13-2015
09:49 PM
No, there is no per-topic configuration
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10-09-2015
12:18 AM
This is a bit confusing. But reading the configs and logs, I'm not able to understand why the log was deleted at such time point. topic 1_persistent was created on 3rd Oct. A new log segment was rolled once the log size reached above 1 GB on 5th Oct:
[2015-10-05 11:55:08,329] INFO Rolled new log segment for '1_persistent-0' in 31 ms. (kafka.log.Log) However, log shows that the first log segment for 1_persistent got deleted after 4 days (7th Oct). Can anyone help me understand why? Thank you. [server.properties] # Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# see kafka.server.KafkaConfig for additional details and defaults
############################# Server Basics #############################
# The id of the broker. This must be set to a unique integer for each broker.
broker.id=2041775
############################# Socket Server Settings #############################
listeners=PLAINTEXT://:9092
# The port the socket server listens on
#port=9092
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
host.name=10.204.177.5
# Hostname the broker will advertise to producers and consumers. If not set, it uses the
# value for "host.name" if configured. Otherwise, it will use the value returned from
# java.net.InetAddress.getCanonicalHostName().
advertised.host.name=10.204.177.5
# The port to publish to ZooKeeper for clients to use. If this is not set,
# it will publish the same port that the broker binds to.
advertised.port=9092
# The number of threads handling network requests
num.network.threads=3
# The number of threads doing disk I/O
num.io.threads=8
# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=102400
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=102400
# The maximum size of a request that the socket server will accept (protection against OOM)
socket.request.max.bytes=104857600
############################# Log Basics #############################
# A comma seperated list of directories under which to store log files
log.dirs=/var/spool/backup/kafka_logs
# The default number of log partitions per topic. More partitions allow greater
# parallelism for consumption, but this will also result in more files across
# the brokers.
num.partitions=1
# The number of threads per data directory to be used for log recovery at startup and flushing at shutdown.
# This value is recommended to be increased for installations with data dirs located in RAID array.
num.recovery.threads.per.data.dir=1
############################# Log Flush Policy #############################
# Messages are immediately written to the filesystem but by default we only fsync() to sync
# the OS cache lazily. The following configurations control the flush of data to disk.
# There are a few important trade-offs here:
# 1. Durability: Unflushed data may be lost if you are not using replication.
# 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush.
# 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks.
# The settings below allow one to configure the flush policy to flush data after a period of time or
# every N messages (or both). This can be done globally and overridden on a per-topic basis.
# The number of messages to accept before forcing a flush of data to disk
#log.flush.interval.messages=10000
# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=1000
############################# Log Retention Policy #############################
# The following configurations control the disposal of log segments. The policy can
# be set to delete segments after a period of time, or after a given size has accumulated.
# A segment will be deleted whenever *either* of these criteria are met. Deletion always happens
# from the end of the log.
# The minimum age of a log file to be eligible for deletion
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log as long as the remaining
# segments don't drop below log.retention.bytes.
#log.retention.bytes=1073741824
# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=1073741824
# The interval at which log segments are checked to see if they can be deleted according
# to the retention policies
log.retention.check.interval.ms=300000
# By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires.
# If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction.
log.cleaner.enable=false
############################# Zookeeper #############################
# Zookeeper connection string (see zookeeper docs for details).
# This is a comma separated host:port pairs, each corresponding to a zk
# server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002".
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=10.204.177.4:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=60000
delete.topic.enable=true
controlled.shutdown.enable=true
log.retention.bytes=1073741824
reserved.broker.max.id=2147483647
[Kafka log] [2015-10-03 17:52:41,580] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent,0] (kafka.server.ReplicaFetcherManager)
[2015-10-03 17:52:41,626] INFO Completed load of log 1_persistent-0 with log end offset 0 (kafka.log.Log)
[2015-10-03 17:52:41,631] INFO Created log for partition [1_persistent,0] in /var/spool/backup/kafka_logs with properties {segment.index.bytes -> 10485760, file.delete.delay.ms -> 60000, segment.bytes -> 1073741824, flush.ms -> 9223372036854775807, delete.retention.ms -> 86400000, index.interval.bytes -> 4096, retention.bytes -> 1073741824, min.insync.replicas -> 1, cleanup.policy -> delete, unclean.leader.election.enable -> true, segment.ms -> 604800000, max.message.bytes -> 1000012, flush.messages -> 9223372036854775807, compression.type -> producer, min.cleanable.dirty.ratio -> 0.5, retention.ms -> 604800000, segment.jitter.ms -> 0}. (kafka.log.LogManager)
[2015-10-03 17:52:41,632] INFO Partition [1_persistent,0] on broker 2041775: No checkpointed highwatermark is found for partition [1_persistent,0] (kafka.cluster.Partition)
[2015-10-03 17:53:02,066] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent,0] (kafka.server.ReplicaFetcherManager)
[2015-10-03 17:53:02,271] INFO Partition [1_persistent,0] on broker 2041775: Expanding ISR for partition [1_persistent,0] from 2041775 to 2041775,2041776 (kafka.cluster.Partition)
[2015-10-03 17:53:02,307] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent,0] (kafka.server.ReplicaFetcherManager)
[2015-10-03 17:53:15,170] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent,0] (kafka.server.ReplicaFetcherManager)
[2015-10-03 17:57:43,288] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent,0] (kafka.server.ReplicaFetcherManager)
[2015-10-03 17:57:43,288] INFO Truncating log 1_persistent-0 to offset 689. (kafka.log.Log)
[2015-10-03 17:57:43,301] INFO [ReplicaFetcherManager on broker 2041775] Added fetcher for partitions List([[1_persistent,0], initOffset 689 to broker BrokerEndPoint(2041776,10.204.177.6,9092)] ) (kafka.server.ReplicaFetcherManager)
[2015-10-05 10:00:15,530] INFO [KafkaApi-2041775] Auto creation of topic 1_persistent_Temp with 1 partitions and replication factor 1 is successful! (kafka.server.KafkaApis)
[2015-10-05 10:00:15,831] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent_Temp,0] (kafka.server.ReplicaFetcherManager)
[2015-10-05 10:00:15,833] INFO Completed load of log 1_persistent_Temp-0 with log end offset 0 (kafka.log.Log)
[2015-10-05 10:00:15,834] INFO Created log for partition [1_persistent_Temp,0] in /var/spool/backup/kafka_logs with properties {segment.index.bytes -> 10485760, file.delete.delay.ms -> 60000, segment.bytes -> 1073741824, flush.ms -> 9223372036854775807, delete.retention.ms -> 86400000, index.interval.bytes -> 4096, retention.bytes -> 1073741824, min.insync.replicas -> 1, cleanup.policy -> delete, unclean.leader.election.enable -> true, segment.ms -> 604800000, max.message.bytes -> 1000012, flush.messages -> 9223372036854775807, compression.type -> producer, min.cleanable.dirty.ratio -> 0.5, retention.ms -> 604800000, segment.jitter.ms -> 0}. (kafka.log.LogManager)
[2015-10-05 10:00:15,836] INFO Partition [1_persistent_Temp,0] on broker 2041775: No checkpointed highwatermark is found for partition [1_persistent_Temp,0] (kafka.cluster.Partition)
[2015-10-05 10:00:22,016] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent_Temp,0] (kafka.server.ReplicaFetcherManager)
[2015-10-05 10:00:22,301] INFO Partition [1_persistent_Temp,0] on broker 2041775: Expanding ISR for partition [1_persistent_Temp,0] from 2041775 to 2041775,2041776 (kafka.cluster.Partition)
[2015-10-05 10:00:22,307] INFO [ReplicaFetcherManager on broker 2041775] Removed fetcher for partitions [1_persistent_Temp,0] (kafka.server.ReplicaFetcherManager)
[2015-10-05 11:55:08,329] INFO Rolled new log segment for '1_persistent-0' in 31 ms. (kafka.log.Log)
[2015-10-07 09:59:22,150] INFO Rolled new log segment for '1_persistent-0' in 9 ms. (kafka.log.Log)
[2015-10-07 10:03:08,055] INFO Scheduling log segment 0 for log 1_persistent-0 for deletion. (kafka.log.Log)
[2015-10-07 10:04:08,067] INFO Deleting segment 0 from log 1_persistent-0. (kafka.log.Log)
[2015-10-07 10:04:09,073] INFO Deleting index /var/spool/backup/kafka_logs/1_persistent-0/00000000000000000000.index.deleted (kafka.log.OffsetIndex)
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Apache Kafka
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