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Jonathanpro
Jonathanpro commented Jan 2, 2019

Hello everyone,
Recently I tried to set up petastorm on my company's hadoop cluster.
However as the cluster uses Kerberos for authentication using petastorm failed.
I figured out that petastorm relies on pyarrow which actually supports kerberos authentication.

I hacked "petastorm/petastorm/hdfs/namenode.py" line 250
and replaced it with

driver = 'libhdfs'
return pyarrow.hdfs.c
idreeskhan
idreeskhan commented Dec 30, 2019

Over time we've had some things leak into the diff methods that make it more cumbersome to use BigDiffy via code instead of CLI.

For example diffAvro here https://github.com/spotify/ratatool/blob/master/ratatool-diffy/src/main/scala/com/spotify/ratatool/diffy/BigDiffy.scala#L284

User has to manually pass in schema otherwise we they receive a non-informative error regarding null schema, add

A complete example of a big data application using : Kubernetes (kops/aws), Apache Spark SQL/Streaming/MLib, Apache Flink, Scala, Python, Apache Kafka, Apache Hbase, Apache Parquet, Apache Avro, Apache Storm, Twitter Api, MongoDB, NodeJS, Angular, GraphQL

  • Updated Feb 1, 2019
  • TypeScript
lr4d
lr4d commented Sep 2, 2020

Something like:

from kartothek.core.dataset import DatasetMetadata
from kartothek.core.factory import DatasetFactory
from kartothek.io_components.metapartition import SINGLE_TABLE


def get_pyarrow_schema(factory: DatasetFactory, table: str = SINGLE_TABLE):
    dm = DatasetMetadata(uuid=factory.dataset_uuid).load_from_store(
        uuid=factory.dataset_uuid, store=factory.store
tobias-hd
tobias-hd commented Aug 13, 2019

When opening a parquet file, ParquetViewer first launches a popup "Select fields to load", where you either can confirm to load all fields, or select the fields you want.

In all use cases relevant for me, I want to display all fields. Hence I'm wondering if it would be possible to skip this popup all together? It's just inconvenient to always confirm the "All fields...", before you see any data

Apache Spark is a fast, in-memory data processing engine with elegant and expressive development API's to allow data workers to efficiently execute streaming, machine learning or SQL workloads that require fast iterative access to datasets.This project will have sample programs for Spark in Scala language .

  • Updated Jul 1, 2020
  • Scala

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