![]() ![]() Parquet, and other columnar formats handle a common Hadoop situation very efficiently. Other tricks of various formats (especially including compression) involve whether a format can be split - that is, can you read a block of records from anywhere in the dataset and still know it's schema? But here's more detail on columnar formats like Parquet. adding or removing columns from a record. AVRO is slightly cooler than those because it can change schema over time, e.g. Record oriented formats are what we're all used to - text files, delimited formats like CSV, TSV. Option to parse output from command line Standard Output Stream (e.g.I think the main difference I can describe relates to record oriented vs.Allow to cancel infinite pagination on UI Save.Support for Dynamic file path using variable placeholder (e.g. ![]() Support for ignoring blank lines and blank rows (no data for each column). ![]() ![]()
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