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Repository for setup and analysis of data models, formats, and processing pipelines

License: Apache License 2.0

Makefile 2.49% Shell 7.27% Python 52.55% Scala 8.76% Jupyter Notebook 23.11% R 5.82%

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Comparison of data pipelines

A. Setup tasks:

  • Search pipeline setup (ElasticSearch)
  • Analytics pipeline setup (Spark)
  • ZNG/ZST setup
  • Kafka setup
    • Script to ingest all JSON files (e.g., from zq-sample-data) into Kafka, one type of log per topic
    • Consume data from Kafka and write to Elastic (e.g., using LogStash)
    • Consume data from Kafka and write to Parquet files (e.g., using SparkStreaming)

TBD: check with Z people with their setups

B. Basic experiment tasks to check that everything works:

  • Feed JSON data into Kafka and check that it is automatically fed to Elastic and you can query it there
  • Feed JSON data into Kafka and check that it is automatically fed into Parquet files, which you can query
  • Check that we can query ZNG data
  • Issue 3-5 queries over ElasticSearch, write down how to issue the queries in Elastic and jq and check that the results match
  • Issue 3-5 queries over Parquet data with Spark, write down how to issue the queries in Elastic and jq and check that the results match
  • Replicate the above queries using ZNG/ZST, write them down, and check that results match

C. Lower-priority tasks:

  • Figure out how to take a snapshot of an Elastic instance and use it to populate a different Elastic instance (useful for making experiments reproducible)
  • Network data source setup (pub-sub the zq-sample-data)
  • IoT data source setup (TSDB)

Organize datasets

Create an EBS volume to hold all sample datasets and their transformations:

  • zq-sample-data (link → z-dataset-sample-data volume)
  • zeek dataset (link: shared privately → z-dataset-zeek)
  • suricata dataset (link: shared privately → z-dataset-suricata)
  • baseball dataset (link → z-dataset-baseball); format lineage:
    • csvzngndjson, zst
    • csv → parquet
    • elastic

#HowTos:

Volume creation:

  • Create EBS volume on EC2 console
  • Pick SSD gp2
  • Pick a size based on the dataset size/planned transformations/...
  • Availability zone: us-west-2a
  • Do not encrypt the volume
  • Add a name to the volume (in the Volumes page): z-dataset-[DATASET_NAME]

Use the volume:

  • Attach the volume to your instance
  • Run lsblk on the instance to identify the device
  • Create a directory on the instance (e.g., /data) and mount the device to it;
    (More details can be found on EBS doc)

Note: remember to umount the volume (if it is mounted somewhere) before detach on the EC2 console!

Done!

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