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Posted to commits@predictionio.apache.org by sh...@apache.org on 2018/09/20 05:44:01 UTC
[4/7] predictionio git commit: [PIO-165] Update Spark and ES version
[PIO-165] Update Spark and ES version
Project: http://git-wip-us.apache.org/repos/asf/predictionio/repo
Commit: http://git-wip-us.apache.org/repos/asf/predictionio/commit/844486a4
Tree: http://git-wip-us.apache.org/repos/asf/predictionio/tree/844486a4
Diff: http://git-wip-us.apache.org/repos/asf/predictionio/diff/844486a4
Branch: refs/heads/develop
Commit: 844486a4481c753f2d389d6a792df763a2e0ccb8
Parents: 3909a6f
Author: Donald Szeto <do...@apache.org>
Authored: Mon Sep 17 13:35:48 2018 -0700
Committer: Donald Szeto <do...@apache.org>
Committed: Mon Sep 17 13:35:48 2018 -0700
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docs/manual/source/system/index.html.md | 38 +++++++++++++++++++---------
1 file changed, 26 insertions(+), 12 deletions(-)
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http://git-wip-us.apache.org/repos/asf/predictionio/blob/844486a4/docs/manual/source/system/index.html.md
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diff --git a/docs/manual/source/system/index.html.md b/docs/manual/source/system/index.html.md
index 1030fec..b4fe884 100644
--- a/docs/manual/source/system/index.html.md
+++ b/docs/manual/source/system/index.html.md
@@ -19,27 +19,41 @@ See the License for the specific language governing permissions and
limitations under the License.
-->
-During the [installation](/install), you have installed the latest stable versions of the following software:
+During the [installation](/install), you have installed the latest stable
+versions of the following software:
* Apache Hadoop up to 2.7.2 (required only if YARN and HDFS are needed)
* Apache HBase up to 1.2.4
-* Apache Spark up to 1.6.3 for Hadoop 2.6 (not Spark 2.x version)
-* Elasticsearch up to 1.7.5 (not the Elasticsearch 2.x version)
+* Apache Spark up to 1.6.3, or up to 2.3.1
+* Elasticsearch up to 1.7.5, or up to 5.6.11
-This section explains general rules-of-thumb for how they are used in PredictionIO. The actual implementation of the Template will define how much of this applies. PredictionIO is flexible about much of this configuration but its Templates generally fit the Lambda model for integrating real-time serving with background periodic model updates.
+This section explains general rules-of-thumb for how they are used in
+PredictionIO. The actual implementation of the Template will define how much of
+this applies. PredictionIO is flexible about much of this configuration but its
+Templates generally fit the Lambda model for integrating real-time serving with
+background periodic model updates.
-**HBase**: Event Server uses Apache HBase (or JDBC DB for small data) as the data store. It stores imported
-events. If you are not using the PredictionIO Event Server, you do not need to
-install HBase.
+**HBase**: Event Server uses Apache HBase (or JDBC DB for small data) as the
+data store. It stores imported events. If you are not using the PredictionIO
+Event Server, you do not need to install HBase.
-**Apache Spark**: Spark is a large-scale data processing engine that powers the data preparation and input to the algorithm, training, and sometimes the serving processing. PredictionIO allows for different engines to be used in training but many algorithms come from Spark's MLlib.
+**Apache Spark**: Spark is a large-scale data processing engine that powers the
+data preparation and input to the algorithm, training, and sometimes the
+serving processing. PredictionIO allows for different engines to be used in
+training but many algorithms come from Spark's MLlib.
-**HDFS**: is a distributed filesystem from Hadoop. It allows storage to be shared among clustered machines. It is used to stage data for batch import into PIO, for export of Event Server datasets, and for storage of some models (see your template for details).
+**HDFS**: is a distributed filesystem from Hadoop. It allows storage to be
+shared among clustered machines. It is used to stage data for batch import into
+PredictionIO, for export of Event Server datasets, and for storage of some
+models (see your template for details).
-The output of training has two parts: a model and its meta-data. The
-model is then stored in HDFS, a local file system, or Elasticsearch. See the details of your algorithm.
+The output of training has two parts: a model and its meta-data. The model is
+then stored in HDFS, a local file system, or Elasticsearch. See the details of
+your algorithm.
-**Elasticsearch**: stores metadata such as model versions, engine versions, access key and app id mappings, evaluation results, etc. For some templates it may store the model.
+**Elasticsearch**: stores metadata such as model versions, engine versions,
+access key and app ID mappings, evaluation results, etc. For some templates it
+may store the model.