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new d00af89 Update FAQ and configuration
d00af89 is described below
commit d00af89046bf3252d9c96114bf5ff8e54f3b19dd
Author: GinaZhai <na.z...@kyligence.io>
AuthorDate: Tue Oct 23 16:45:24 2018 +0800
Update FAQ and configuration
---
website/_docs/gettingstarted/faq.md | 35 ++++++++++++++++++-------------
website/_docs/install/configuration.cn.md | 1 +
website/_docs/install/configuration.md | 1 +
3 files changed, 23 insertions(+), 14 deletions(-)
diff --git a/website/_docs/gettingstarted/faq.md
b/website/_docs/gettingstarted/faq.md
index 793ff64..f23ec95 100644
--- a/website/_docs/gettingstarted/faq.md
+++ b/website/_docs/gettingstarted/faq.md
@@ -10,10 +10,6 @@ since: v0.6.x
* No, Kylin is an OLAP engine with SQL interface. The SQL queries need be
matched with the pre-defined OLAP model.
-#### How to compare Kylin with other SQL engines like Hive, Presto, Spark SQL,
Impala?
-
- * They answer a query in different ways. Kylin is not a replacement for
them, but a supplement (query accelerator). Many users run Kylin together with
other SQL engines. For the high frequent query patterns, building Cubes can
greatly improve the performance and also offload cluster workloads. For less
queried patterns or ad-hoc queries, ther MPP engines are more flexible.
-
#### What's a typical scenario to use Apache Kylin?
* Kylin can be the best option if you have a huge table (e.g., >100 million
rows), join with lookup tables, while queries need be finished in the second
level (dashboards, interactive reports, business intelligence, etc), and the
concurrent users can be dozens or hundreds.
@@ -30,6 +26,10 @@ since: v0.6.x
* It depends on a couple of factors, for example, dimension/measure number,
dimension cardinality, cuboid number, compression algorithm, etc. You can
optimize the cube expansion in many ways to control the size.
+#### How to compare Kylin with other SQL engines like Hive, Presto, Spark SQL,
Impala?
+
+ * They answer a query in different ways. Kylin is not a replacement for
them, but a supplement (query accelerator). Many users run Kylin together with
other SQL engines. For the high frequent query patterns, building Cubes can
greatly improve the performance and also offload cluster workloads. For less
queried patterns or ad-hoc queries, ther MPP engines are more flexible.
+
#### How to compare Kylin with Druid?
* Druid is more suitable for real-time analysis. Kylin is more focus on OLAP
case. Druid has good integration with Kafka as real-time streaming; Kylin
fetches data from Hive or Kafka in batches. The real-time capability of Kylin
is still under development.
@@ -82,10 +82,19 @@ But if you do want, there are some workarounds. 1) Add the
primary key as a dime
* Yes, but they are private APIs, incline to change over versions (without
notification). By design, Kylin expects the user to create a new
project/model/cube in Kylin's web GUI.
+#### How to define a snowflake model(with two fact tables)?
+
+ * In the snowflake model, there is only one fact table also. But you could
define lookup table joins with another lookup table.
+ * If the query pattern between your two "fact" tables is fixed, just like
factA left join with factB. You could define factB as a lookup table and skip
the snapshot for this huge lookup table.
+
#### Where does the cube locate, can I directly read cube from HBase without
going through Kylin API?
* Cube is stored in HBase. Each cube segment is an HBase table. The
dimension values will be composed as the row key. The measures will be
serialized in columns. To improve the storage efficiency, both dimension and
measure values will be encoded to bytes. Kylin will decode the bytes to origin
values after fetching from HBase. Without Kylin's metadata, the HBase tables
are not readable.
+#### How to design a cube?
+
+ * Please check:
[https://www.slideshare.net/YangLi43/design-cube-in-apache-kylin]()
+
#### How to encrypt cube data?
* You can enable encryption at HBase side. Refer
https://hbase.apache.org/book.html#hbase.encryption.server for more details.
@@ -94,6 +103,14 @@ But if you do want, there are some workarounds. 1) Add the
primary key as a dime
* Kylin doesn't have a built-in scheduler for this. You can trigger that
through Rest API from external scheduler services, like Linux cron job, Apache
Airflow, etc.
+#### How to export/import cube/project across different Kylin environments?
+
+ * Please check: [http://kylin.apache.org/docs/howto/howto_use_cli.html]()
+
+#### How to view kylin cube's hbase table without encoding?
+
+ * To view the origin data, please use SQL to query Kylin. Kylin will convert
the SQL query to HBase access and then decode the data. You can use Rest API,
JDBC, ODBC drivers to connect with Kylin.
+
#### Does Kylin support Hadoop 3 and HBase 2.0?
* From v2.5.0, Kylin will provide a binary package for Hadoop 3 and HBase 2.
@@ -308,13 +325,3 @@ vi ./tomcat/webapps/kylin/WEB-INF/classes/kylinSecurity.xml
* The data in 'hdfs-working-dir' ('hdfs:///kylin/kylin_metadata/' by
default) includes intermediate files (will be GC) and Cuboid data (won't be
GC). The Cuboid data is kept for the further segments' merge, as Kylin couldn't
merge from HBase. If you're sure those segments won't be merged, you can move
them to other paths or even delete.
* Please pay attention to the "resources" sub-folder under
'hdfs-working-dir', which persists some big metadata files like dictionaries
and lookup tables' snapshots. They shouldn't be moved.
-
-#### How to export/import cube/project across different Kylin environments?
-
- * Please check: [http://kylin.apache.org/docs/howto/howto_use_cli.html]()
-
-#### How to define a snowflake model(with two fact tables)?
-
- * In the snowflake model, there is only one fact table also. But you could
define lookup table joins with another lookup table.
- * If the query pattern between your two "fact" tables is fixed, just like
factA left join with factB. You could define factB as a lookup table and skip
the snapshot for this huge lookup table.
-
diff --git a/website/_docs/install/configuration.cn.md
b/website/_docs/install/configuration.cn.md
index 6fc219d..af9297d 100644
--- a/website/_docs/install/configuration.cn.md
+++ b/website/_docs/install/configuration.cn.md
@@ -236,6 +236,7 @@ Kylin 的主要配置文件。
| kylin.query.statement-cache-max-num | 50000
| Max number for cache query statement | Yes
|
| kylin.query.statement-cache-max-num-per-key | 50
| | Yes
|
| kylin.query.enable-dict-enumerator | false
| Whether enable dict enumerator | Yes
|
+| kylin.query.enable-dynamic-column | false
| | No
|
| kylin.server.mode | all
| Kylin node mode: all\|job\|query. | No
|
| kylin.server.cluster-servers | localhost:7070
| | No
|
| kylin.server.cluster-name |
| | No
|
diff --git a/website/_docs/install/configuration.md
b/website/_docs/install/configuration.md
index a9c6257..0fe2162 100644
--- a/website/_docs/install/configuration.md
+++ b/website/_docs/install/configuration.md
@@ -236,6 +236,7 @@ The main configuration file of Kylin.
| kylin.query.statement-cache-max-num | 50000
| Max number for cache query statement | Yes
|
| kylin.query.statement-cache-max-num-per-key | 50
| | Yes
|
| kylin.query.enable-dict-enumerator | false
| Whether enable dict enumerator | Yes
|
+| kylin.query.enable-dynamic-column | false
| | No
|
| kylin.server.mode | all
| Kylin node mode: all\|job\|query. | No
|
| kylin.server.cluster-servers | localhost:7070
| | No
|
| kylin.server.cluster-name |
| | No
|
