webhdfs | c library and fuse file

It is possible, you will need to use some mutate filters and some conditionals.

First you need to get the value of the minute from the @timestamp of the event and add the value into a new field, you can use the [@metadata] object, which can be use to filtering, but it will not be present in the output event.

You get a \r (carriage return) back in $destination. You can remove it with tr -d '\r'

The getSchema() method that works is:

json does not support a time type, that is the reason for the error. What you need to do is to change that into a type json can use. That might be a string that represents the time (choose the formating yourself, so you are sure, that when reading it out again you have consistent data) or easier you just keep the long value used.

Here you cansee what json can use: https://www.json.org/json-en.html

You can use the exact same logic as the first solution, but this time, use a StringBuilder to get the full response which you then need to parse using a JSON library.

I had jdk15.0.2 installed and it had some sort of problem with hadoop 3.1.0. Later I installed jdk8 and changed java_home. It went all fine!

About secondary node manager, I had hadoop1:9000 for both fs.defaultFS and dfs.namenode.secondary.http-address, and therefore created a conflict. I changed secondary into 9001 and it went all fine!

You are getting this error "This query does not support recovering from checkpoint location" because a socket readStream is not a re-playable source and hence does not allow any usage of checkpointing. You need to make sure not to use the option checkpointLocation at all in your writeStream.

Typically, you differentiate between local file system and an hdfs location by using either file:///path/to/dir or hdfs:///path/to/dir.

Make sure that you application user has all the rights to write and read these locations. Also, you may have changes the code base in which case the application cannot recover from the checkpoint files. You can read about the allowed and not allowed changes in a Structured Streaming job in the Structured Streaming Programming Guid on Recovery Semantics after Changes in a Streaming Query.

In order to make Spark aware of your HDFS you need to include two Hadoop configration files on Spark's classpath:

• hdfs-site.xml which provides default behaviors for the HDFS client; and
• core-site.xml which sets the default file system name.

Usually, they are stored in "/etc/hadoop/conf". To make these files visible to Spark, you need to set HADOOP_CONF_DIR in $SPARK_HOME/spark-env.sh to a location containing the configuration files.

[Source from the book "Spark - The definitive Guide"]

"Do we need to provide checkpoint in every df.writeStream options, i.e. We can also pass in spark.sparkContext.setCheckpointDir(checkpointLocation) right?"

Theroetically, you could set the checkpoint location centrally for all queries in your SQLContext but it is highly recommend to set a unique checkpoint location for every single Stream. The Databricks blog on Structured Streaming in Production says:

"This checkpoint location preserves all of the essential information that uniquely identifies a query. Hence, each query must have a different checkpoint location, and multiple queries should never have the same location.

"As a best practice, we recommend that you always specify the checkpointLocation option."

If your Hadoop services are not on localhost, you will need to update the Hue configuration to point to them.

Azure Data Lake Storage Gen1 uses Azure Active Directory for authentication. Before authoring an application that works with Data Lake Storage Gen1, you must decide how to authenticate your application with Azure Active Directory (Azure AD).

The following table illustrates how end-user and service-to-service authentication mechanisms are supported for Data Lake Storage Gen1.

Reference: Authentication with Azure Data Lake Storage Gen1 using Azure Active Directory

Check out this Service-to-service authentication with Azure Data Lake Storage Gen1 using .NET SDK - to learn about how to use the .NET SDK to do service-to-service authentication with Azure Data Lake Storage Gen1.

For end-user authentication with Data Lake Storage Gen1 using .NET SDK, see End-user authentication with Data Lake Storage Gen1 using .NET SDK.