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The following commit(s) were added to refs/heads/asf-site by this push:
new bca261d Fix DeltaStreamer args and layout in docker demo page
bca261d is described below
commit bca261d27930577bfb2ec74dc6a09a5d21d1fde6
Author: Balaji Varadarajan <[email protected]>
AuthorDate: Wed Apr 17 17:28:06 2019 -0700
Fix DeltaStreamer args and layout in docker demo page
---
docs/docker_demo.md | 15 ++++++++++-----
1 file changed, 10 insertions(+), 5 deletions(-)
diff --git a/docs/docker_demo.md b/docs/docker_demo.md
index 23a5a4f..c8fc1b3 100644
--- a/docs/docker_demo.md
+++ b/docs/docker_demo.md
@@ -168,8 +168,11 @@ spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
....
2018-09-24 22:20:00 INFO
OutputCommitCoordinator$OutputCommitCoordinatorEndpoint:54 -
OutputCommitCoordinator stopped!
2018-09-24 22:20:00 INFO SparkContext:54 - Successfully stopped SparkContext
+
+
+
# Run the following spark-submit command to execute the delta-streamer and
ingest to stock_ticks_mor dataset in HDFS
-spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
$HUDI_UTILITIES_BUNDLE --storage-type MERGE_ON_READ --source-class
com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts
--target-base-path /user/hive/warehouse/stock_ticks_mor --target-table
stock_ticks_mor --props /var/demo/config/kafka-source.properties
+spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
$HUDI_UTILITIES_BUNDLE --storage-type MERGE_ON_READ --source-class
com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts
--target-base-path /user/hive/warehouse/stock_ticks_mor --target-table
stock_ticks_mor --props /var/demo/config/kafka-source.properties
--schemaprovider-class com.uber.hoodie.utilities.schema.FilebasedSchemaProvider
....
2018-09-24 22:22:01 INFO
OutputCommitCoordinator$OutputCommitCoordinatorEndpoint:54 -
OutputCommitCoordinator stopped!
2018-09-24 22:22:01 INFO SparkContext:54 - Successfully stopped SparkContext
@@ -437,13 +440,15 @@ cat docker/demo/data/batch_2.json | kafkacat -b
kafkabroker -t stock_ticks -P
docker exec -it adhoc-2 /bin/bash
# Run the following spark-submit command to execute the delta-streamer and
ingest to stock_ticks_cow dataset in HDFS
-spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
$HUDI_UTILITIES_BUNDLE --storage-type COPY_ON_WRITE --source-class
com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts
--target-base-path /user/hive/warehouse/stock_ticks_cow --target-table
stock_ticks_cow --props /var/demo/config/kafka-source.properties
+spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
$HUDI_UTILITIES_BUNDLE --storage-type COPY_ON_WRITE --source-class
com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts
--target-base-path /user/hive/warehouse/stock_ticks_cow --target-table
stock_ticks_cow --props /var/demo/config/kafka-source.properties
--schemaprovider-class com.uber.hoodie.utilities.schema.FilebasedSchemaProvider
+
# Run the following spark-submit command to execute the delta-streamer and
ingest to stock_ticks_mor dataset in HDFS
-spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
$HUDI_UTILITIES_BUNDLE --storage-type MERGE_ON_READ --source-class
com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts
--target-base-path /user/hive/warehouse/stock_ticks_mor --target-table
stock_ticks_mor --props /var/demo/config/kafka-source.properties
+spark-submit --class
com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
$HUDI_UTILITIES_BUNDLE --storage-type MERGE_ON_READ --source-class
com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts
--target-base-path /user/hive/warehouse/stock_ticks_mor --target-table
stock_ticks_mor --props /var/demo/config/kafka-source.properties
--schemaprovider-class com.uber.hoodie.utilities.schema.FilebasedSchemaProvider
exit
```
+
With Copy-On-Write table, the second ingestion by DeltaStreamer resulted in a
new version of Parquet file getting created.
See
`http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_cow/2018/08/31`
@@ -600,6 +605,7 @@ exit
With 2 batches of data ingested, lets showcase the support for incremental
queries in Hudi Copy-On-Write datasets
Lets take the same projection query example
+
```
docker exec -it adhoc-2 /bin/bash
beeline -u jdbc:hive2://hiveserver:10000 --hiveconf
hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat --hiveconf
hive.stats.autogather=false
@@ -611,7 +617,6 @@ beeline -u jdbc:hive2://hiveserver:10000 --hiveconf
hive.input.format=org.apache
| 20180924064621 | GOOG | 2018-08-31 09:59:00 | 6330 | 1230.5
| 1230.02 |
| 20180924065039 | GOOG | 2018-08-31 10:59:00 | 9021 | 1227.1993
| 1227.215 |
+----------------------+---------+----------------------+---------+------------+-----------+--+
-
```
As you notice from the above queries, there are 2 commits - 20180924064621 and
20180924065039 in timeline order.
@@ -622,7 +627,7 @@ To show the effects of incremental-query, let us assume
that a reader has alread
ingesting first batch. Now, for the reader to see effect of the second batch,
he/she has to keep the start timestamp to
the commit time of the first batch (20180924064621) and run incremental query
-`Hudi incremental mode` provides efficient scanning for incremental queries by
filtering out files that do not have any
+Hudi incremental mode provides efficient scanning for incremental queries by
filtering out files that do not have any
candidate rows using hudi-managed metadata.
```
