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new ac70b37 Docs: Fix spelling errors in hive.md (#1990)
ac70b37 is described below
commit ac70b370c7bb1a2626bf4792693f101b32bd7993
Author: RickyMa <[email protected]>
AuthorDate: Tue Dec 29 02:38:45 2020 +0800
Docs: Fix spelling errors in hive.md (#1990)
---
site/docs/hive.md | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/site/docs/hive.md b/site/docs/hive.md
index b7b335d..655b11a 100644
--- a/site/docs/hive.md
+++ b/site/docs/hive.md
@@ -28,10 +28,10 @@ Regardless of the table type, the
`HiveIcebergStorageHandler` and supporting cla
```sql
add jar /path/to/iceberg-hive-runtime.jar;
```
-There are many others ways to achieve this including adding the jar file to
Hive's auxillary classpath (so it is available by default) - please refer to
Hive's documentation for more information.
+There are many others ways to achieve this including adding the jar file to
Hive's auxiliary classpath (so it is available by default) - please refer to
Hive's documentation for more information.
#### Using Hadoop Tables
-Iceberg tables created using `HadoopTables` are stored entirely in a directory
in a filesytem like HDFS.
+Iceberg tables created using `HadoopTables` are stored entirely in a directory
in a filesystem like HDFS.
##### Create an Iceberg table
The first step is to create an Iceberg table using the Spark/Java/Python API
and `HadoopTables`. For the purposes of this documentation we will assume that
the table is called `table_a` and that the table location is
`hdfs://some_path/table_a`.
@@ -85,7 +85,7 @@ SELECT * from table_b;
```
#### Using Hadoop Catalog
-Iceberg tables created using `HadoopCatalog` are stored entirely in a
directory in a filesytem like HDFS.
+Iceberg tables created using `HadoopCatalog` are stored entirely in a
directory in a filesystem like HDFS.
##### Create an Iceberg table
The first step is to create an Iceberg table using the Spark/Java/Python API
and `HadoopCatalog`. For the purposes of this documentation we will assume that
the fully qualified table identifier is `database_a.table_c` and that the
Hadoop Catalog warehouse location is
`hdfs://some_bucket/path_to_hadoop_warehouse`. Iceberg will therefore create
the table at the location
`hdfs://some_bucket/path_to_hadoop_warehouse/database_a/table_c`.
