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Title | Views | Posted |
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4551 | 09-02-2020 06:46 AM |
03-22-2024
01:48 AM
@nanda_bigdata you can install a newer version of impacket. Also, you will have to installed Rust compiler.
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07-26-2022
04:17 AM
1 Kudo
Hi Team, CDP uses the "org.apache.spark.internal.io.cloud.PathOutputCommitProtocol" OutputCommitter which does not support dynamicPartitionOverwrite. You can set the following parameters into your spark job. code level: spark.conf.set("spark.sql.sources.partitionOverwriteMode", "dynamic")
spark.conf.set("spark.sql.parquet.output.committer.class", "org.apache.parquet.hadoop.ParquetOutputCommitter")
spark.conf.set("spark.sql.sources.commitProtocolClass", "org.apache.spark.sql.execution.datasources.SQLHadoopMapReduceCommitProtocol") spark-submit/spark-shell: --conf spark.sql.sources.partitionOverwriteMode=dynamic --conf spark.sql.parquet.output.committer.class=org.apache.parquet.hadoop.ParquetOutputCommitter --conf spark.sql.sources.commitProtocolClass=org.apache.spark.sql.execution.datasources.SQLHadoopMapReduceCommitProtocol Note: If you are using S3, you can disable it by specifying spark.cloudera.s3_committers.enabled parameter. --conf spark.cloduera.s3_committers.enabled=false
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04-23-2021
07:17 AM
Try to run the command adding " --deploy-mode cluster " It should work, this seems to be a bug https://support.oracle.com/knowledge/Oracle%20Database%20Products/2498643_1.html
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09-02-2020
06:46 AM
Same error, different port (8080): the problem was fixed by deleting the /var/lib/nifi/state directory (you need to stop all Nifi instances first). You can have this problem everytime you switch from TLS to non-secure and viceversa.
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01-10-2020
02:35 AM
As it says in the documentation: Because this option results in increased resource utilization on a single host, it could cause problems due to contention with other Impala statements or high resource usage. Symptoms could include queries running slowly, exceeding the memory limit, or appearing to hang. Use it only in a single-user development/test environment; do not use it in a production environment or in a cluster with a high-concurrency or high-volume or performance-critical workload.
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