commit	db6150c5ef02a9bc6feaf3f9f4e6cecba9a6a25b	[log] [tgz]
author	Prasanna Rajaperumal <prasanna@uber.com>	Fri May 19 23:47:27 2017 -0700
committer	prazanna <prasanna.raj@gmail.com>	Fri Jun 09 13:06:33 2017 -0700
tree	88ff63847696e4cef9b9650305df0d710defa4e1
parent	c192dd60b4dbf13bbee12e3dbba5cbc39edddd29 [diff]

Refactor hoodie-hive

hoodie-client/src/main/java/com/uber/hoodie/io/storage/HoodieParquetWriter.java[diff]
hoodie-common/src/main/java/com/uber/hoodie/common/table/log/block/HoodieAvroDataBlock.java[diff]
hoodie-common/src/test/java/com/uber/hoodie/common/util/SchemaTestUtil.java[diff]
hoodie-common/src/test/resources/simple-test-evolved.avro[diff]
hoodie-common/src/test/resources/simple-test.avro[diff]
hoodie-hive/pom.xml[diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HiveSyncConfig.java[diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HiveSyncTool.java[diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HoodieHiveClient.java[Added - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HoodieHiveConfiguration.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HoodieHiveDatasetSyncTask.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HoodieHiveSchemaSyncTask.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/HoodieHiveSyncException.java[Renamed from hoodie-hive/src/main/java/com/uber/hoodie/hive/HoodieHiveDatasetException.java - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/PartitionStrategy.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/PartitionValueExtractor.java[Added - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/SchemaDifference.java[Renamed from hoodie-hive/src/main/java/com/uber/hoodie/hive/model/SchemaDifference.java - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/SchemaStrategy.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/SlashEncodedDayPartitionValueExtractor.java[Added - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/client/HoodieFSClient.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/client/HoodieHiveClient.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/example/HoodieHiveSyncExample.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/impl/DayBasedPartitionStrategy.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/impl/ParseSchemaFromDataStrategy.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/model/HoodieDatasetReference.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/model/StoragePartition.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/model/TablePartition.java[Deleted - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/util/ColumnNameXLator.java[Renamed from hoodie-hive/src/main/java/com/uber/hoodie/hive/client/ColumnNameXLator.java - diff]
hoodie-hive/src/main/java/com/uber/hoodie/hive/util/SchemaUtil.java[Renamed from hoodie-hive/src/main/java/com/uber/hoodie/hive/client/SchemaUtil.java - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/DatasetSchemaTest.java[Deleted - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/HDroneDatasetTest.java[Deleted - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/HiveSyncToolTest.java[Added - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/TestUtil.java[Added - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/util/CsvParquetWriter.java[Deleted - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/util/CsvWriteSupport.java[Deleted - diff]
hoodie-hive/src/test/java/com/uber/hoodie/hive/util/TestUtil.java[Deleted - diff]
hoodie-hive/src/test/resources/nation.csv[Deleted - diff]
hoodie-hive/src/test/resources/nation.schema[Deleted - diff]
hoodie-hive/src/test/resources/nation_evolved.csv[Deleted - diff]
hoodie-hive/src/test/resources/nation_evolved.schema[Deleted - diff]
pom.xml[diff]

40 files changed

tree: 88ff63847696e4cef9b9650305df0d710defa4e1

README.md

Hoodie

Hoodie manages storage of large analytical datasets on HDFS and serve them out via two types of tables

Read Optimized Table - Provides excellent query performance via purely columnar storage (e.g. Parquet)
Near-Real time Table (WIP) - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + Avro)

For more, head over here