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Posted to dev@parquet.apache.org by "Gabor Szadovszky (JIRA)" <ji...@apache.org> on 2018/04/21 12:39:04 UTC
[jira] [Updated] (PARQUET-423) Make writing Avro to Parquet less
noisy
[ https://issues.apache.org/jira/browse/PARQUET-423?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Gabor Szadovszky updated PARQUET-423:
-------------------------------------
Fix Version/s: 1.8.2
> Make writing Avro to Parquet less noisy
> ---------------------------------------
>
> Key: PARQUET-423
> URL: https://issues.apache.org/jira/browse/PARQUET-423
> Project: Parquet
> Issue Type: Improvement
> Components: parquet-avro
> Affects Versions: 1.8.0
> Reporter: Niels Basjes
> Assignee: Niels Basjes
> Priority: Minor
> Fix For: 1.10.0, 1.8.2
>
>
> When writing Avro files to disk using the AvroParquetWriter for each column in the file some statistics are written to the Logging system.
> When writing files based on a large Avro schema often the output of this logging is no longer useful and becomes a hassle.
> Because the logging level is hardcoded (why?) into the parquet library I would like to introduce a switch that allows to enable/disable this type of logging.
> {code}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 90B for [IPAddress] BINARY: 60 values, 26B raw, 47B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 7 entries, 77B raw, 7B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 102B for [country] BINARY: 60 values, 26B raw, 47B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 7 entries, 119B raw, 7B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 152B for [windowid] BINARY: 60 values, 33B raw, 51B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 12 entries, 480B raw, 12B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 77B for [customerId] BINARY: 58 values, 22B raw, 42B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 7 entries, 49B raw, 7B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 86B for [sessionId] BINARY: 58 values, 28B raw, 43B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 10 entries, 110B raw, 10B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 93B for [sessionEventNr] INT64: 58 values, 34B raw, 48B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 14 entries, 112B raw, 14B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 114B for [visitId] BINARY: 58 values, 28B raw, 43B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 10 entries, 250B raw, 10B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 90B for [visitEventNr] INT64: 58 values, 34B raw, 45B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 11 entries, 88B raw, 11B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 112B for [timestamp] INT64: 58 values, 50B raw, 66B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 46 entries, 368B raw, 46B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 85B for [IPAddress] BINARY: 58 values, 22B raw, 42B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 7 entries, 77B raw, 7B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 97B for [country] BINARY: 58 values, 22B raw, 42B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 7 entries, 119B raw, 7B comp}
> Jan 12, 2016 1:43:00 PM INFO: org.apache.parquet.hadoop.ColumnChunkPageWriteStore: written 144B for [windowid] BINARY: 58 values, 28B raw, 43B comp, 1 pages, encodings: [RLE_DICTIONARY, PLAIN], dic { 10 entries, 400B raw, 10B comp}
> {code}
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