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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-      http://www.apache.org/licenses/LICENSE-2.0
-
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
---><h1>Installation Guide</h1><p>This tutorial guides you through the 
installation and configuration
-    of CarbonData in the following two modes :</p>
-<ul>
-    <li><a href="#installing-spark-cluster">Installing and
-        Configuring CarbonData on Standalone Spark Cluster</a></li>
-    <li><a href="#installing-yarn-cluster">Installing and
-        Configuring CarbonData on "Spark on YARN" Cluster</a></li>
-</ul><p>followed by :</p>
-<ul>
-    <li><a href="#query-execution">Query Execution using CarbonData
-        Thrift Server</a></li>
-</ul><h2 id="installing-spark-cluster">Installing and Configuring CarbonData 
on Standalone Spark Cluster</h2><h3>
-    Prerequisites</h3>
-<ul>
-    <li><p>Hadoop HDFS and Yarn should be installed and running.</p></li>
-    <li><p>Spark should be installed and running on all the cluster 
nodes.</p></li>
-    <li><p>CarbonData user should have permission to access HDFS.</p></li>
-</ul><h3>Procedure</h3>
-<ul>
-    <li><p><a
-            
href="https://github.com/apache/incubator-carbondata/blob/master/build/README.md";
 target="_blank">Build
-        the CarbonData</a> project and get the assembly jar from
-        "./assembly/target/scala-2.10/carbondata_xxx.jar" and put in the 
<code>&quot;&lt;SPARK_HOME&gt;/carbonlib&quot;</code>
-        folder.</p>
-        <p>NOTE: Create the carbonlib folder if it does not exists inside 
<code>&quot;&lt;SPARK_HOME&gt;&quot;</code>
-            path.</p></li>
-    <li><p>Add the carbonlib folder path in the Spark classpath. (Edit 
<code>&quot;&lt;SPARK_HOME&gt;/conf/spark-env.sh&quot;</code>
-        file and modify the value of SPARK_CLASSPATH by appending 
<br/><code>&quot;&lt;SPARK_HOME&gt;/carbonlib/*&quot;</code>
-        to the existing value)</p></li>
-    <li><p>Copy the carbon.properties.template to 
<code>&quot;&lt;SPARK_HOME&gt;/conf/carbon.properties&quot;</code>
-        folder from "./conf/" of CarbonData repository.</p></li>
-    <li><p>Copy the "carbonplugins" folder to 
<code>&quot;&lt;SPARK_HOME&gt;/carbonlib&quot;</code>
-        folder from "./processing/" folder of CarbonData repository.</p>
-        <p>NOTE: carbonplugins will contain .kettle folder.</p></li>
-    <li><p>In Spark node, configure the properties mentioned in the following 
table in <code>&quot;&lt;SPARK_HOME&gt;/conf/spark-defaults.conf&quot;</code>
-        file.</p></li>
-</ul>
-<table class="table table-striped table-bordered">
-    <thead>
-    <tr>
-        <th>Property</th>
-        <th>Description</th>
-        <th>Value</th>
-    </tr>
-    </thead>
-    <tbody>
-    <tr>
-        <td>carbon.kettle.home</td>
-        <td>Path that will be used by CarbonData internally to create graph 
for loading the data
-        </td>
-        <td>$SPARK_HOME /carbonlib/carbonplugins</td>
-    </tr>
-    <tr>
-        <td>spark.driver.extraJavaOptions</td>
-        <td>A string of extra JVM options to pass to the driver. For instance, 
GC settings or other
-            logging.
-        </td>
-        
<td>-Dcarbon.properties.filepath=$SPARK_HOME/conf/carbon.properties</td>
-    </tr>
-    <tr>
-        <td>spark.executor.extraJavaOptions</td>
-        <td>A string of extra JVM options to pass to executors. For instance, 
GC settings or other
-            logging. NOTE: You can enter multiple values separated by space.
-        </td>
-        
<td>-Dcarbon.properties.filepath=$SPARK_HOME/conf/carbon.properties</td>
-    </tr>
-    </tbody>
-</table>
-<ul>
-    <li>Add the following properties in 
<code>&quot;&lt;SPARK_HOME&gt;/conf/&quot;
-        carbon.properties</code>:
-    </li>
-</ul>
-<table class="table table-striped table-bordered">
-    <thead>
-    <tr>
-        <th>Property</th>
-        <th>Required</th>
-        <th>Description</th>
-        <th>Example</th>
-        <th>Remark</th>
-    </tr>
-    </thead>
-    <tbody>
-    <tr>
-        <td>carbon.storelocation</td>
-        <td>NO</td>
-        <td>Location where data CarbonData will create the store and write the 
data in its own
-            format.
-        </td>
-        <td>hdfs://HOSTNAME:PORT/Opt/CarbonStore</td>
-        <td>Propose to set HDFS directory</td>
-    </tr>
-    <tr>
-        <td>carbon.kettle.home</td>
-        <td>YES</td>
-        <td>Path that will be used by CarbonData internally to create graph 
for loading the data.
-        </td>
-        <td>$SPARK_HOME/carbonlib/carbonplugins</td>
-        <td></td>
-    </tr>
-    </tbody>
-</table>
-<ul>
-    <li>Verify the installation. For example:</li>
-</ul><p><code>
-    ./spark-shell --master spark://HOSTNAME:PORT --total-executor-cores 2
-    --executor-memory 2G
-</code></p><p>NOTE: Make sure you have permissions for CarbonData JARs and 
files through which
-    driver and executor will start.</p><p>To get started with CarbonData : <a
-        href="mainpage.html?page=quickStart">Quick Start</a> , <a 
href="mainpage.html?page=ddl">DDL
-    Operations on CarbonData</a></p>
-   <h2 id="installing-yarn-cluster">Installing and Configuring CarbonData on 
"Spark on YARN"
-    Cluster</h2><p>This section provides the procedure to install CarbonData 
on "Spark on YARN"
-    cluster.</p><h3>Prerequisites</h3>
-<ul>
-    <li>Hadoop HDFS and Yarn should be installed and running.</li>
-    <li>Spark should be installed and running in all the clients.</li>
-    <li>CarbonData user should have permission to access HDFS.</li>
-</ul><h3>Procedure</h3><p>The following steps are only for Driver Nodes. 
(Driver nodes are the one
-    which starts the spark context.)</p>
-<ul>
-    <li><p><a
-            
href="https://github.com/apache/incubator-carbondata/blob/master/build/README.md";
 target="_blank">Build
-        the CarbonData</a> project and get the assembly jar from
-        "./assembly/target/scala-2.10/carbondata_xxx.jar" and put in the 
<code>&quot;&lt;SPARK_HOME&gt;/carbonlib&quot;</code>
-        folder.</p>
-        <p>NOTE: Create the carbonlib folder if it does not exists inside 
<code>&quot;&lt;SPARK_HOME&gt;&quot;</code>
-            path.</p></li>
-    <li><p>Copy "carbonplugins" folder to 
<code>&quot;&lt;SPARK_HOME&gt;/carbonlib&quot;</code>
-        folder from "./processing/" folder of CarbonData repository. 
carbonplugins will contain
-        .kettle folder.</p></li>
-    <li><p>Copy the "carbon.properties.template" to 
<code>&quot;&lt;SPARK_HOME&gt;/conf/carbon.properties&quot;</code>
-        folder from conf folder of CarbonData repository.</p></li>
-    <li>Modify the parameters in "spark-default.conf" located in the 
<code>&quot;&lt;SPARK_HOME&gt;/conf</code>"
-    </li>
-</ul>
-<table class="table table-striped table-bordered">
-    <thead>
-    <tr>
-        <th>Property</th>
-        <th>Description</th>
-        <th>Value</th>
-    </tr>
-    </thead>
-    <tbody>
-    <tr>
-        <td>spark.master</td>
-        <td>Set this value to run the Spark in yarn cluster mode.</td>
-        <td>Set "yarn-client" to run the Spark in yarn cluster mode.</td>
-    </tr>
-    <tr>
-        <td>spark.yarn.dist.files</td>
-        <td>Comma-separated list of files to be placed in the working 
directory of each executor.
-        </td>
-        
<td><code>&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/conf/carbon.properties</code></td>
-    </tr>
-    <tr>
-        <td>spark.yarn.dist.archives</td>
-        <td>Comma-separated list of archives to be extracted into the working 
directory of each
-            executor.
-        </td>
-        
<td><code>&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/carbonlib/carbondata_xxx.jar</code></td>
-    </tr>
-    <tr>
-        <td>spark.executor.extraJavaOptions</td>
-        <td>A string of extra JVM options to pass to executors. For instance 
NOTE: You can enter
-            multiple values separated by space.
-        </td>
-        
<td><code>-Dcarbon.properties.filepath=&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/conf/carbon.properties</code>
-        </td>
-    </tr>
-    <tr>
-        <td>spark.executor.extraClassPath</td>
-        <td>Extra classpath entries to prepend to the classpath of executors. 
NOTE: If
-            SPARK_CLASSPATH is defined in spark-env.sh, then comment it and 
append the values in
-            below parameter spark.driver.extraClassPath
-        </td>
-        <td><code>
-            
&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/carbonlib/carbonlib/carbondata_xxx.jar</code>
-        </td>
-    </tr>
-    <tr>
-        <td>spark.driver.extraClassPath</td>
-        <td>Extra classpath entries to prepend to the classpath of the driver. 
NOTE: If
-            SPARK_CLASSPATH is defined in spark-env.sh, then comment it and 
append the value in
-            below parameter spark.driver.extraClassPath.
-        </td>
-        <td><code>
-            
&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/carbonlib/carbonlib/carbondata_xxx.jar</code>
-        </td>
-    </tr>
-    <tr>
-        <td>spark.driver.extraJavaOptions</td>
-        <td>A string of extra JVM options to pass to the driver. For instance, 
GC settings or other
-            logging.
-        </td>
-        
<td><code>-Dcarbon.properties.filepath=&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/conf/carbon.properties</code>
-        </td>
-    </tr>
-    <tr>
-        <td>carbon.kettle.home</td>
-        <td>Path that will be used by CarbonData internally to create graph 
for loading the data.
-        </td>
-        
<td><code>&quot;&lt;YOUR_SPARK_HOME_PATH&gt;&quot;/carbonlib/carbonplugins</code></td>
-    </tr>
-    </tbody>
-</table>
-<ul>
-    <li>Add the following properties in <code>&lt;SPARK_HOME&gt;/conf/ 
carbon.properties</code>:
-    </li>
-</ul>
-<table class="table table-striped table-bordered">
-    <thead>
-    <tr>
-        <th>Property</th>
-        <th>Required</th>
-        <th>Description</th>
-        <th>Example</th>
-        <th>Default Value</th>
-    </tr>
-    </thead>
-    <tbody>
-    <tr>
-        <td>carbon.storelocation</td>
-        <td>NO</td>
-        <td>Location where CarbonData will create the store and write the data 
in its own format.
-        </td>
-        <td>hdfs://HOSTNAME:PORT/Opt/CarbonStore</td>
-        <td>Propose to set HDFS directory</td>
-    </tr>
-    <tr>
-        <td>carbon.kettle.home</td>
-        <td>YES</td>
-        <td>Path that will be used by CarbonData internally to create graph 
for loading the data.
-        </td>
-        <td>$SPARK_HOME/carbonlib/carbonplugins</td>
-        <td></td>
-    </tr>
-    </tbody>
-</table>
-<ul>
-    <li>Verify the installation.</li>
-</ul><p><code>
-    ./bin/spark-shell --master yarn-client --driver-memory 1g
-    --executor-cores 2 --executor-memory 2G
-</code> NOTE: Make sure you have permissions for CarbonData JARs and files 
through which driver and
-    executor will start.</p><p>Getting started with CarbonData :<a
-        href="mainpage.html?page=quickStart">Quick Start</a> , <a 
href="mainpage.html?page=ddl">DDL Operations on CarbonData</a></p>
-
-<h2 id="query-execution">
-    Query Execution Using CarbonData Thrift Server</h2><h3>Starting CarbonData 
Thrift Server</h3><p>
-    a. cd <code>&lt;SPARK_HOME&gt;</code></p><p>b. Run the following command 
to start the CarbonData
-    thrift server.</p><p><code>
-    ./bin/spark-submit --conf spark.sql.hive.thriftServer.singleSession=true
-    --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
-    $SPARK_HOME/carbonlib/$CARBON_ASSEMBLY_JAR &lt;carbon_store_path&gt;
-</code></p>
-<table class="table table-striped table-bordered">
-    <thead>
-    <tr>
-        <th>Parameter</th>
-        <th>Description</th>
-        <th>Example</th>
-    </tr>
-    </thead>
-    <tbody>
-    <tr>
-        <td>CARBON_ASSEMBLY_JAR</td>
-        <td>CarbonData assembly jar name present in the 
<code>&quot;&lt;SPARK_HOME&gt;&quot;/carbonlib/</code>
-            folder.
-        </td>
-        
<td>carbondata_2.10-0.1.0-incubating-SNAPSHOT-shade-hadoop2.7.2.jar</td>
-    </tr>
-    <tr>
-        <td>carbon_store_path</td>
-        <td>This is a parameter to the CarbonThriftServer class. This a HDFS 
path where CarbonData
-            files will be kept. Strongly Recommended to put same as 
carbon.storelocation parameter
-            of carbon.properties.
-        </td>
-        
<td><code>hdfs//&lt;host_name&gt;:54310/user/hive/warehouse/carbon.store</code></td>
-    </tr>
-    </tbody>
-</table><h3>Examples</h3>
-<ul>
-    <li>Start with default memory and executors</li>
-</ul><p><pre><code>
-    ./bin/spark-submit --conf spark.sql.hive.thriftServer.singleSession=true
-    --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
-    $SPARK_HOME/carbonlib
-    /carbondata_2.10-0.1.0-incubating-SNAPSHOT-shade-hadoop2.7.2.jar
-    hdfs://hacluster/user/hive/warehouse/carbon.store
-</code></pre></p>
-<ul>
-    <li>Start with Fixed executors and resources</li>
-</ul><p><pre><code>
-    ./bin/spark-submit --conf spark.sql.hive.thriftServer.singleSession=true
-    --class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
-    --num-executors 3 --driver-memory 20g --executor-memory 250g
-    --executor-cores 32
-    /srv/OSCON/BigData/HACluster/install/spark/sparkJdbc/lib
-    /carbondata_2.10-0.1.0-incubating-SNAPSHOT-shade-hadoop2.7.2.jar
-    hdfs://hacluster/user/hive/warehouse/carbon.store
-</code></pre></p><h3>Connecting to CarbonData Thrift Server Using Beeline</h3>
-<p>
-<pre><code>
-    cd SPARK_HOME
-    ./bin/beeline jdbc:hive2://thriftserver_host:port
-
-    Example:
-    ./bin/beeline jdbc:hive2://10.10.10.10:10000
-</code></pre>
-</p>

http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/4f8753c1/src/main/webapp/docs/latest/mainpage.html
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-<html lang="en">
-  <head>
-    <meta charset="utf-8">
-    <meta http-equiv="X-UA-Compatible" content="IE=edge">
-    <meta name="viewport" content="width=device-width, initial-scale=1">
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-                      <li>
-                          <a 
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-                      <li>
-                          <a 
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-                      <li>
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-                      <li>
-                          <a 
href="https://cwiki.apache.org/confluence/display/CARBONDATA/Releases";
-                             target="_blank">Release Archive</a></li>
-                  </ul>
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-   <section><!-- Dashboard nav -->
-    <div class="container-fluid q">
-        <div class="col-sm-12  col-md-12 maindashboard">
-              <div class="row">
-                <section>
-                  <div style="padding:10px 15px;">
-                    <div class="doc-header">
-                        <div class="doc-toc">
-                            <a href="mainpage.html?page=userguide" class="icon 
toc-icon"></a>
-                        </div>
-                       <img src="images/CarbonData_icon.png" alt="" 
class="logo-print" >
-                       <span>Version: 1.0.0 | Published: 30-01-2017</span>
-                       <i class="fa fa-print print-icon" aria-hidden="true" 
onclick="divPrint(); " title="Print"></i>
-                    </div>
-                    <div id="viewpage" name="viewpage">   </div>
-                    <div class="doc-footer">
-                         <a href="#top" class="scroll-top">Top</a>
-                    </div>
-                  </div>
-                </section>
-              </div>
-        </div>
-      </div>
-    </section><!-- End systemblock part -->
-
-  <!-- jQuery (necessary for Bootstrap's JavaScript plugins) -->
-
-    <script src="../../js/custom.js"></script>
-    <script src="../../js/mdNavigation.js" type="text/javascript"></script>
-
-    <script type="text/javascript">
-     <!-- $("#leftmenu").load("table-of-content.html");-->
-    </script>
-
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-  </body>
-  </html>

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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-      http://www.apache.org/licenses/LICENSE-2.0
-
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
--->
-<h1>Overview</h1><p>This tutorial provides a detailed overview about :</p>
-<ul>
-  <li><a href="#introduction">Introduction</a></li>
-  <li><a href="#features">Features</a></li>
-</ul>
-
-<div id="introduction"></div>
-<h2>Introduction</h2><p>CarbonData is a fully indexed columnar and Hadoop 
native data-store for processing heavy analytical workloads and detailed 
queries on big data. CarbonData allows faster interactive query using advanced 
columnar storage, index, compression and encoding techniques to improve 
computing efficiency, which helps in speeding up queries by an order of 
magnitude faster over PetaBytes of data.</p><p>In customer benchmarks, 
CarbonData has proven to manage Petabyte of data running on extraordinarily 
low-cost hardware and answers queries around 10 times faster than the current 
open source solutions (column-oriented SQL on Hadoop data-stores).</p><p>Some 
of the salient features of CarbonData are :</p>
-<ul>
-  <li>Low-Latency for various types of data access patterns like Sequential, 
Random and OLAP.</li>
-  <li>Fast query on fast data.</li>
-  <li>Space efficiency.</li>
-  <li>General format available on Hadoop-ecosystem.</li>
-</ul>
-
-<div id="features"></div>
-<h2>Features</h2><p>CarbonData file format is a columnar store in HDFS. It has 
many features that a modern columnar format has, such as splittable, 
compression schema, complex data type etc and CarbonData has following unique 
features:</p>
-<ul>
-  <li><p>Unique Data Organization: Though CarbonData stores data in Columnar 
format, it differs from traditional Columnar formats as the columns in each 
row-group(Data Block) is sorted independent of the other columns. Though this 
arrangement requires CarbonData to store the row-number mapping against each 
column value, it makes it possible to use binary search for faster filtering 
and since the values are sorted, same/similar values come together which yields 
better compression and offsets the storage overhead required by the row number 
mapping.</p></li>
-  <li><p>Advanced Push Down Optimizations: CarbonData pushes as much of query 
processing as possible close to the data to minimize the amount of data being 
read, processed, converted and transmitted/shuffled. Using projections and 
filters it reads only the required columns form the store and also reads only 
the rows that match the filter conditions provided in the query.</p></li>
-  <li><p>Multi Level Indexing: CarbonData uses multiple indices at various 
levels to enable faster search and speed up query processing.</p></li>
-  <li><p>Dictionary Encoding: Most databases and big data SQL data stores 
employ columnar encoding to achieve data compression by storing small integers 
numbers (surrogate value) instead of full string values. However, almost all 
existing databases and data stores divide the data into row groups containing 
anywhere from few thousand to a million rows and employ dictionary encoding 
only within each row group. Hence, the same column value can have different 
surrogate values in different row groups. So, while reading the data, 
conversion from surrogate value to actual value needs to be done immediately 
after the data is read from the disk. But CarbonData employs global surrogate 
key which means that a common dictionary is maintained for the full store on 
one machine/node. So CarbonData can perform all the query processing work such 
as grouping/aggregation, sorting etc on light weight surrogate values. The 
conversion from surrogate to actual values needs to be done only on the final 
res
 ult. This procedure improves performance on two aspects. Conversion from 
surrogate values to actual values is done only for the final result rows which 
are much less than the actual rows read from the store. All query processing 
and computation such as grouping/aggregation, sorting, and so on is done on 
lightweight surrogate values which requires less memory and CPU time compared 
to actual values.</p></li>
-  <li><p>Deep Spark Integration: It has built-in spark integration for Spark 
1.6.2, 2.1 and interfaces for Spark SQL, DataFrame API and query optimization. 
It supports bulk data ingestion and allows saving of spark dataframes as 
CarbonData files.</p></li>
-  <li><p>Update Delete Support: It supports batch updates like daily update 
scenarios for OLAP and Base+Delta file based design.</p></li>
-  <li><p>Bucketing : It is a technique that is used for uniform distribution 
of data across files in CarbonData. It enhances the performance of join 
queries. While loading the data, records are placed into buckets based on 
hashing algorithm. During the execution of join queries the records can be 
fetched from buckets with out need of shuffling.This feature is used to 
distribute/organize the table/partition data into multiple files placing 
similar records in same file.</p></li>
-  <li><p>Global Multi Dimensional Keys(MDK) based B+Tree Index for all non- 
measure columns: Aids in quickly locating the row groups(Data Blocks) that 
contain the data matching search/filter criteria.</p></li>
-  <li><p>Min-Max Index for all columns: Aids in quickly locating the row 
groups(Data Blocks) that contain the data matching search/filter 
criteria.</p></li>
-  <li><p>Data Block level Inverted Index for all columns: Aids in quickly 
locating the rows that contain the data matching search/filter criteria within 
a row group(Data Blocks).</p></li>
-  <li><p>Store data along with index: Significantly accelerates query 
performance and reduces the I/O scans and CPU resources, when there are filters 
in the query. CarbonData index consists of multiple levels of indices. A 
processing framework can leverage this index to reduce the task it needs to 
schedule and process. It can also do skip scan in more finer grain units 
(called blocklet) in task side scanning instead of scanning the whole 
file.</p></li>
-  <li><p>Operable encoded data: It supports efficient compression and global 
encoding schemes and can query on compressed/encoded data. The data can be 
converted just before returning the results to the users, which is "late 
materialized".</p></li>
-  <li><p>Column group: Allows multiple columns to form a column group that 
would be stored as row format. This reduces the row reconstruction cost at 
query time.</p></li>
-  <li><p>Support for various use cases with one single Data format: Examples 
are interactive OLAP-style query, Sequential Access (big scan) and Random 
Access (narrow scan).</p></li>
-</ul>

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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-    
-      http://www.apache.org/licenses/LICENSE-2.0
-    
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
---><h1>Quick Start</h1><p>This tutorial provides a quick introduction to using 
CarbonData.</p><h2>
-    Prerequisites</h2>
-<ul>
-    <li><a 
href="https://github.com/apache/incubator-carbondata/blob/master/build"; 
target="_blank">Installation and
-        building CarbonData</a>.
-    </li>
-    <li>Create a sample.csv file using the following commands. The CSV file is 
required for loading
-        data into CarbonData.
-    </li>
-</ul><p><code>
-    cd carbondata
-    cat &gt; sample.csv &lt;&lt; EOF
-    id,name,city,age
-    1,david,shenzhen,31
-    2,eason,shenzhen,27
-    3,jarry,wuhan,35
-    EOF
-</code></p><h2>Interactive Analysis with Spark Shell Version 2.1</h2><p>Apache 
Spark Shell provides
-    a simple way to learn the API, as well as a powerful tool to analyze data 
interactively. Please
-    visit <a href="http://spark.apache.org/docs/latest/"; 
target="_blank">Apache Spark Documentation</a> for more
-    details on Spark shell.</p><h4>Basics</h4><p>Start Spark shell by running 
the following command
-    in the Spark directory:</p><p><code>
-    ./bin/spark-shell --jars &lt;carbondata assembly jar path&gt;
-</code></p><p>In this shell, SparkSession is readily available as 'spark' and 
Spark context is
-    readily available as 'sc'.</p><p>In order to create a CarbonSession we 
will have to configure it
-    explicitly in the following manner :</p>
-<ul>
-    <li>Import the following :</li>
-</ul><p><code>
-    import org.apache.spark.sql.SparkSession
-    import org.apache.spark.sql.CarbonSession._
-</code></p>
-<ul>
-    <li>Create a CarbonSession :</li>
-</ul>
-<pre><code>val carbon = SparkSession
-            .builder()
-            .config(sc.getConf)
-            .getOrCreateCarbonSession(&quot;&lt;hdfs store path&gt;&quot;)
-</code></pre>
-<p>NOTE: By default metastore location is pointed to 
“…/carbon.metastore”, user can provide own metastore location to 
CarbonSession like</p>
-<pre><code>`SparkSession.builder().config(sc.getConf).getOrCreateCarbonSession(&quot;&lt;hdfs
 store path&gt;&quot;, &quot;&lt;local metastore path&gt;&quot;)`
-</code></pre>
-<h4>Executing Queries</h4><h5>Creating a Table</h5><p><code>
-    scala&gt;carbon.sql(&quot;CREATE TABLE IF NOT EXISTS test_table(id string, 
name string, city string, age Int) STORED BY &#39;carbondata&#39;&quot;)
-</code></p><h5>Loading Data to a Table</h5><p><code>
-    scala&gt;carbon.sql(&quot;LOAD DATA INPATH &#39;sample.csv file path&#39; 
INTO TABLE test_table&quot;)
-</code> NOTE:Please provide the real file path of sample.csv for the above 
script.</p><h6>Query Data
-    from a Table</h6><p><code>scala&gt;carbon.sql("SELECT * FROM 
test_table").show()</code></p><p><code>scala&gt;carbon.sql("SELECT
-    city, avg(age), sum(age) FROM test_table GROUP BY city").show()</code></p>
-<h2>Interactive Analysis with Spark Shell Version 1.6</h2>
-<h4>Basics</h4><p>Start Spark shell by running the following
-    command in the Spark directory:</p><p><code>
-    ./bin/spark-shell --jars &lt;carbondata assembly jar path&gt;
-</code></p><p>NOTE: In this shell, SparkContext is readily available as sc.</p>
-<ul>
-    <li>In order to execute the Queries we need to import CarbonContext:</li>
-</ul><p><code>
-    import org.apache.spark.sql.CarbonContext
-</code></p>
-<ul>
-    <li>Create an instance of CarbonContext in the following manner :</li>
-</ul><p><code>
-    val cc = new CarbonContext(sc)
-</code></p><p>NOTE: By default store location is pointed to "../carbon.store", 
user can provide own
-    store location to CarbonContext like new CarbonContext(sc, 
storeLocation).</p><h4>Executing
-    Queries</h4>
-<h5>Creating a Table</h5><p><code>
-    scala&gt;cc.sql(&quot;CREATE TABLE IF NOT EXISTS test_table (id string, 
name string, city
-    string, age Int) STORED BY &#39;carbondata&#39;&quot;)
-</code>
-</p>To see the table created :<p><code>
-    scala&gt;cc.sql(&quot;SHOW TABLES&quot;).show()
-</code></p><h5>Loading Data to a Table</h5><p><code>
-    scala&gt;cc.sql(&quot;LOAD DATA INPATH &#39;sample.csv file path&#39; INTO 
TABLE test_table&quot;)
-</code><br/>
-<p>NOTE:Please provide the real file path of sample.csv for the above 
script.</p><h5>Query
-    Data from a Table</h5><p><code>
-    scala&gt;cc.sql(&quot;SELECT * FROM test_table&quot;).show()
-    scala&gt;cc.sql(&quot;SELECT city, avg(age), sum(age) FROM test_table 
GROUP BY city&quot;).show()
-</code></p>
\ No newline at end of file

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-<h1>Data Types</h1><h4>CarbonData supports the following data types:</h4>
-<ul>
-  Numeric Types
-  <li>SMALLINT</li>
-  <li>INT/INTEGER</li>
-  <li>BIGINT</li>
-  <li>DOUBLE</li>
-  <li>DECIMAL</li>
-</ul>
-<ul>
-  Date/Time Types
-  <li>DATE</li>
-  <li>TIMESTAMP</li>
-</ul>
-
-<ul>
-  String Types
-  <li>STRING</li>
-</ul>
-<ul>
-  Complex Types
-  <li>arrays: ARRAY<code>&lt;data_type&gt;</code></li>
-  <li>structs: STRUCT<code>&lt;col_name : data_type COMMENT col_comment, 
...&gt;</code></li>
-</ul>
-

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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-      http://www.apache.org/licenses/LICENSE-2.0
-
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
---><h1>Troubleshooting</h1>
-<p>This tutorial is designed to provide troubleshooting for end users and 
developers
-    who are building, deploying, and using CarbonData.</p>
-<h2 id="failed-to-load-thrift-libraries">Failed to load thrift libraries</h2>
-<p><strong>Symptom</strong></p>
-<p>Thrift throws following exception :</p>
-<pre><code>thrift: error while loading shared libraries:
-libthriftc.so.0: cannot open shared object file: No such file or directory
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The complete path to the directory containing the libraries is not 
configured correctly.</p>
-<p><strong>Procedure</strong></p>
-<p>Follow the steps below to ensure loading of libraries appropriately :</p>
-<ol>
-    <li>
-        <p>For ubuntu you have to add a custom.conf file to 
/etc/ld.so.conf.d<br>
-            For example,</p>
-        <pre><code>sudo gedit /etc/ld.so.conf.d/randomLibs.conf
-</code></pre>
-        <p>Inside this file you are supposed to configure the complete path to 
the directory that
-            contains all the libraries that you wish to add to the system, let 
us say
-            /home/ubuntu/localLibs</p>
-    </li>
-    <li>
-        <p>To ensure your library location ,check for existence of <a 
href="http://libthrift.so";>libthrift.so</a>
-        </p>
-    </li>
-    <li>
-        <p>Save and run the following command to update the system with this 
libs.</p>
-        <pre><code>sudo ldconfig
-</code></pre>
-    </li>
-</ol>
-Note : Remember to add only the path to the directory, not the full path for 
that file, all the libraries inside that path will be automatically indexed.
-<h2 id="failed-to-launch-the-spark-shell">Failed to launch the Spark Shell</h2>
-<p><strong>Symptom</strong></p>
-<p>The shell prompts the following error :</p>
-<pre><code>org.apache.spark.sql.CarbonContext$$anon$$apache$spark$sql$catalyst$analysis
-$OverrideCatalog$_setter_$org$apache$spark$sql$catalyst$analysis
-$OverrideCatalog$$overrides_$e
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The Spark Version and the selected Spark Profile do not match.</p>
-<p><strong>Procedure</strong></p>
-<ol>
-    <li>
-        <p>Ensure your spark version and selected profile for spark are 
correct.</p>
-    </li>
-    <li>
-        <p>Use the following command :</p>
-    </li>
-</ol>
-<pre><code>
- &quot;mvn -Pspark-2.1 -Dspark.version {yourSparkVersion} clean package&quot;
-
-</code></pre>
-Note :  Refrain from using &quot;mvn clean package&quot; without specifying 
the profile.
-<h2 id="failed-to-execute-load-query-on-cluster">Failed to execute load query 
on cluster.
-</h2>
-<p><strong>Symptom</strong></p>
-<p>Load query failed with the following exception:</p>
-<pre><code>Dictionary file is locked for updation.
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The carbon.properties file is not identical in all the nodes of the 
cluster.</p>
-<p><strong>Procedure</strong></p>
-<p>Follow the steps to ensure the carbon.properties file is consistent across 
all the nodes:</p>
-<ol>
-    <li>
-        <p>Copy the carbon.properties file from the master node to all the 
other nodes in the
-            cluster.<br>
-            For example, you can use ssh to copy this file to all the 
nodes.</p>
-    </li>
-    <li>
-        <p>For the changes to take effect, restart the Spark cluster.</p>
-    </li>
-</ol>
-<h2 id="failed-to-execute-insert-query-on-cluster">Failed to execute insert 
query on
-    cluster.</h2>
-<p><strong>Symptom</strong></p>
-<p>Load query failed with the following exception:</p>
-<pre><code>Dictionary file is locked for updation.
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The carbon.properties file is not identical in all the nodes of the 
cluster.</p>
-<p><strong>Procedure</strong></p>
-<p>Follow the steps to ensure the carbon.properties file is consistent across 
all the nodes:</p>
-<ol>
-    <li>
-        <p>Copy the carbon.properties file from the master node to all the 
other nodes in the
-            cluster.<br>
-            For example, you can use scp to copy this file to all the 
nodes.</p>
-    </li>
-    <li>
-        <p>For the changes to take effect, restart the Spark cluster.</p>
-    </li>
-</ol>
-<h2 id="failed-to-connect-to-hiveuser-with-thrift">Failed to connect to 
hiveuser with
-    thrift</h2>
-<p><strong>Symptom</strong></p>
-<p>We get the following exception :</p>
-<pre><code>Cannot connect to hiveuser.
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The external process does not have permission to access.</p>
-<p><strong>Procedure</strong></p>
-<p>Ensure that the Hiveuser in mysql must allow its access to the external 
processes.</p>
-<h2 id="failure-to-read-the-metastore-db-during-table-creation">Failure to 
read the
-    metastore db during table creation.</h2>
-<p><strong>Symptom</strong></p>
-<p>We get the following exception on trying to connect :</p>
-<pre><code>Cannot read the metastore db
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The metastore db is dysfunctional.</p>
-<p><strong>Procedure</strong></p>
-<p>Remove the metastore db from the carbon.metastore in the Spark 
Directory.</p>
-<h2 id="failed-to-load-data-on-the-cluster">Failed to load data on the 
cluster</h2>
-<p><strong>Symptom</strong></p>
-<p>Data loading fails with the following exception :</p>
-<pre><code>Data Load failure exeception
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The following issue can cause the failure :</p>
-<ol>
-    <li>
-        <p>The core-site.xml, hive-site.xml, yarn-site and carbon.properties 
are not consistent
-            across all nodes of the cluster.</p>
-    </li>
-    <li>
-        <p>Path to hdfs ddl is not configured correctly in the 
carbon.properties.</p>
-    </li>
-</ol>
-<p><strong>Procedure</strong></p>
-<p>Follow the steps to ensure the following configuration files are consistent 
across all the
-    nodes:</p>
-<ol>
-    <li>
-        <p>Copy the core-site.xml, hive-site.xml, yarn-site,carbon.properties 
files from the master
-            node to all the other nodes in the cluster.<br>
-            For example, you can use scp to copy this file to all the 
nodes.</p>
-        <p>Note : Set the path to hdfs ddl in carbon.properties in the master 
node.</p>
-    </li>
-    <li>
-        <p>For the changes to take effect, restart the Spark cluster.</p>
-    </li>
-</ol>
-<h2 id="failed-to-insert-data-on-the-cluster">Failed to insert data on the 
cluster</h2>
-<p><strong>Symptom</strong></p>
-<p>Insertion fails with the following exception :</p>
-<pre><code>Data Load failure exeception
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>The following issue can cause the failure :</p>
-<ol>
-    <li>
-        <p>The core-site.xml, hive-site.xml, yarn-site and carbon.properties 
are not consistent
-            across all nodes of the cluster.</p>
-    </li>
-    <li>
-        <p>Path to hdfs ddl is not configured correctly in the 
carbon.properties.</p>
-    </li>
-</ol>
-<p><strong>Procedure</strong></p>
-<p>Follow the steps to ensure the following configuration files are consistent 
across all the
-    nodes:</p>
-<ol>
-    <li>
-        <p>Copy the core-site.xml, hive-site.xml, yarn-site,carbon.properties 
files from the master
-            node to all the other nodes in the cluster.<br>
-            For example, you can use scp to copy this file to all the 
nodes.</p>
-        <p>Note : Set the path to hdfs ddl in carbon.properties in the master 
node.</p>
-    </li>
-    <li>
-        <p>For the changes to take effect, restart the Spark cluster.</p>
-    </li>
-</ol>
-<h2 id="failed-to-execute-concurrent-operations">Failed to execute Concurrent 
Operations.
-</h2>
-<p><strong>Symptom</strong></p>
-<p>Execution of Concurrent Operations (Load,Insert,Update) on table by 
multiple workers fails with
-    the following exception :</p>
-<pre><code>Table is locked for updation.
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>Concurrency not supported.</p>
-<p><strong>Procedure</strong></p>
-<p>Worker must wait for the query execution to complete and the table to 
release the lock for
-    another query execution to succeed…</p>
-<h2 id="failed-to-create-a-table-with-a-single-numeric-column">Failed to 
create a table
-    with a single numeric column.</h2>
-<p><strong>Symptom</strong></p>
-<p>Execution fails with the following exception :</p>
-<pre><code>Table creation fails.
-</code></pre>
-<p><strong>Possible Cause</strong></p>
-<p>Behavior not supported.</p>
-<p><strong>Procedure</strong></p>
-<p>A single column that can be considered as dimension is mandatory for table 
creation.</p>
-

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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-      http://www.apache.org/licenses/LICENSE-2.0
-
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
---><h1>Useful Tips</h1><p>This tutorial guides you to create CarbonData Tables 
and optimize performance. The following sections will elaborate on the above 
topics :</p>
-<ul>
-  <li><a href="#carbondata-table">Suggestions to create CarbonData 
Table</a></li>
-  <li><a href="#carbondata-performance">Configurations For Optimizing 
CarbonData Performance</a></li>
-</ul><h2 id="carbondata-table">Suggestions to Create CarbonData 
Table</h2><p>Recently CarbonData was used to analyze performance of 
Telecommunication field. The results of the analysis for table creation with 
dimensions ranging from 10 thousand to 10 billion rows and 100 to 300 columns 
have been summarized below. </p><p>The following table describes some of the 
columns from the table used.</p><p><strong>Table Column Description</strong></p>
-<table class="table table-striped table-bordered">
-  <thead>
-    <tr>
-      <th>Column Name </th>
-      <th>Data Type </th>
-      <th>Cardinality </th>
-      <th>Attribution </th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <td>msisdn </td>
-      <td>String </td>
-      <td>30 million </td>
-      <td>Dimension </td>
-    </tr>
-    <tr>
-      <td>BEGIN_TIME </td>
-      <td>BigInt </td>
-      <td>10 Thousand </td>
-      <td>Dimension </td>
-    </tr>
-    <tr>
-      <td>HOST </td>
-      <td>String </td>
-      <td>1 million </td>
-      <td>Dimension </td>
-    </tr>
-    <tr>
-      <td>Dime_1 </td>
-      <td>String </td>
-      <td>1 Thousand </td>
-      <td>Dimension </td>
-    </tr>
-    <tr>
-      <td>counter_1 </td>
-      <td>Numeric(20,0) </td>
-      <td>NA </td>
-      <td>Measure </td>
-    </tr>
-    <tr>
-      <td>... </td>
-      <td>... </td>
-      <td>NA </td>
-      <td>Measure </td>
-    </tr>
-    <tr>
-      <td>counter_100 </td>
-      <td>Numeric(20,0) </td>
-      <td>NA </td>
-      <td>Measure </td>
-    </tr>
-  </tbody>
-</table><p>CarbonData has more than 50 test cases, on the basis of these we 
have following suggestions to enhance the query performance :</p>
-<ul>
-  <li><strong>Put the frequently-used column filter in the 
beginning</strong></li>
-</ul><p>For example, MSISDN filter is used in most of the query then we must 
put the MSISDN in the first column. The create table command can be modified as 
suggested below :</p><p><code>
-  create table carbondata_table(
-  msisdn String,
-  ...
-  )STORED BY &#39;org.apache.carbondata.format&#39; 
-  TBLPROPERTIES ( &#39;DICTIONARY_EXCLUDE&#39;=&#39;MSISDN,..&#39;,
-  &#39;DICTIONARY_INCLUDE&#39;=&#39;...&#39;);
-</code></p><p>Now the query with MSISDN in the filter will be more 
efficient.</p>
-<ul>
-  <li><strong>Put the frequently-used columns in the order of low to high 
cardinality</strong></li>
-</ul><p>If the table in the specified query has multiple columns which are 
frequently used to filter the results, it is suggested to put  the columns in 
the order of cardinality low to high. This ordering of frequently used columns 
improves the compression ratio and  enhances the performance of queries with 
filter on these columns.</p><p>For example if MSISDN, HOST and Dime_1 are 
frequently-used columns, then the column order of table is suggested as  
Dime_1&gt;HOST&gt;MSISDN as Dime_1 has the lowest cardinality.  The create 
table command can be modified as suggested below :</p><p><code>
-  create table carbondata_table(
-  Dime_1 String,
-  HOST String,
-  MSISDN String,
-  ...
-  )STORED BY &#39;org.apache.carbondata.format&#39; 
-  TBLPROPERTIES ( &#39;DICTIONARY_EXCLUDE&#39;=&#39;MSISDN,HOST..&#39;,
-  &#39;DICTIONARY_INCLUDE&#39;=&#39;Dime_1..&#39;);
-</code></p>
-<ul>
-  <li><strong>Put the Dimension type columns in order of low to high 
cardinality</strong></li>
-</ul><p>If the columns used to filter are not frequently used, then it is 
suggested to order all the columns of dimension type in order of low to high 
cardinality. The create table command can be modified as below :</p><p><code>
-  create table carbondata_table(
-  Dime_1 String,
-  BEGIN_TIME bigint
-  HOST String,
-  MSISDN String,
-  ...
-  )STORED BY &#39;org.apache.carbondata.format&#39; 
-  TBLPROPERTIES ( &#39;DICTIONARY_EXCLUDE&#39;=&#39;MSISDN,HOST,IMSI..&#39;,
-  &#39;DICTIONARY_INCLUDE&#39;=&#39;Dime_1,END_TIME,BEGIN_TIME..&#39;);
-</code></p>
-<ul>
-  <li><strong>For measure type columns with non high accuracy, replace 
Numeric(20,0) data type with Double data type</strong></li>
-</ul><p>For columns of measure type, not requiring high accuracy, it is 
suggested to replace Numeric data type with Double to enhance query 
performance. The create table command can be modified as below :</p><p><code>
-  create table carbondata_table(
-  Dime_1 String,
-  BEGIN_TIME bigint
-  HOST String,
-  MSISDN String,
-  counter_1 double,
-  counter_2 double,
-  ...
-  counter_100 double
-  )STORED BY &#39;org.apache.carbondata.format&#39; 
-  TBLPROPERTIES ( &#39;DICTIONARY_EXCLUDE&#39;=&#39;MSISDN,HOST,IMSI&#39;,
-  &#39;DICTIONARY_INCLUDE&#39;=&#39;Dime_1,END_TIME,BEGIN_TIME&#39;);
-</code>  The result of performance analysis of test-case shows reduction in 
query execution time from 15 to 3 seconds, thereby improving performance by 
nearly 5 times.</p>
-<ul>
-  <li><strong>Columns of incremental character should be re-arranged at the 
end of dimensions</strong></li>
-</ul><p>Consider the following scenario where data is loaded each day and the 
start_time is incremental for each load, it is suggested to put start_time at 
the end of dimensions. </p><p>Incremental values are efficient in using min/max 
index. The create table command can be modified as below :</p><p><code>
-  create table carbondata_table(
-  Dime_1 String,
-  HOST String,
-  MSISDN String,
-  counter_1 double,
-  counter_2 double,
-  BEGIN_TIME bigint,
-  ...
-  counter_100 double
-  )STORED BY &#39;org.apache.carbondata.format&#39; 
-  TBLPROPERTIES ( &#39;DICTIONARY_EXCLUDE&#39;=&#39;MSISDN,HOST,IMSI&#39;,
-  &#39;DICTIONARY_INCLUDE&#39;=&#39;Dime_1,END_TIME,BEGIN_TIME&#39;); 
-</code></p>
-<ul>
-  <li><strong>Avoid adding high cardinality columns to dictionary</strong></li>
-</ul><p>If the system has low memory configuration, then it is suggested to 
exclude high cardinality columns from the dictionary to enhance load 
performance. Creation of dictionary for high cardinality columns at time of 
load will degrade load performance due to excessive memory usage. </p><p>By 
default CarbonData determines the cardinality at the first data load and allows 
for dictionary creation only if the cardinality is less than 1 million.</p>
-<h2 id="carbondata-performance">Configurations for Optimizing CarbonData 
Performance</h2><p>Recently we did some performance POC on CarbonData for 
Finance and telecommunication Field. It involved detailed queries and 
aggregation scenarios. After the completion of POC, some of the configurations 
impacting the performance have been identified and tabulated below :</p>
-<table class="table table-striped table-bordered">
-  <thead>
-    <tr>
-      <th>Parameter </th>
-      <th>Location </th>
-      <th>Used For </th>
-      <th>Description </th>
-      <th>Tuning </th>
-    </tr>
-  </thead>
-  <tbody>
-    <tr>
-      <td>carbon.sort.intermediate.files.limit </td>
-      <td>spark/carbonlib/carbon.properties </td>
-      <td>Data loading </td>
-      <td>During the loading of data, local temp is used to sort the data. 
This number specifies the minimum number of intermediate files after which the 
merge sort has to be initiated. </td>
-      <td>Increasing the parameter to a higher value will improve the load 
performance. For example, when we increase the value from 20 to 100, it 
increases the data load performance from 35MB/S to more than 50MB/S. Higher 
values of this parameter consumes more memory during the load. </td>
-    </tr>
-    <tr>
-      <td>carbon.number.of.cores.while.loading </td>
-      <td>spark/carbonlib/carbon.properties </td>
-      <td>Data loading </td>
-      <td>Specifies the number of cores used for data processing during data 
loading in CarbonData. </td>
-      <td>If you have more number of CPUs, then you can increase the number of 
CPUs, which will increase the performance. For example if we increase the value 
from 2 to 4 then the CSV reading performance can increase about 1 times </td>
-    </tr>
-    <tr>
-      <td>carbon.compaction.level.threshold </td>
-      <td>spark/carbonlib/carbon.properties </td>
-      <td>Data loading and Querying </td>
-      <td>For minor compaction, specifies the number of segments to be merged 
in stage 1 and number of compacted segments to be merged in stage 2. </td>
-      <td>Each CarbonData load will create one segment, if every load is small 
in size it will generate many small file over a period of time impacting the 
query performance. Configuring this parameter will merge the small segment to 
one big segment which will sort the data and improve the performance. For 
Example in one telecommunication scenario, the performance improves about 2 
times after minor compaction. </td>
-    </tr>
-    <tr>
-      <td>spark.sql.shuffle.partitions </td>
-      <td>spark/con/spark-defaults.conf </td>
-      <td>Querying </td>
-      <td>The number of task started when spark shuffle. </td>
-      <td>The value can be 1 to 2 times as much as the executor cores. In an 
aggregation scenario, reducing the number from 200 to 32 reduced the query time 
from 17 to 9 seconds. </td>
-    </tr>
-    <tr>
-      <td>num-executors/executor-cores/executor-memory </td>
-      <td>spark/con/spark-defaults.conf </td>
-      <td>Querying </td>
-      <td>The number of executors, CPU cores, and memory used for CarbonData 
query. </td>
-      <td>In the bank scenario, we provide the 4 CPUs cores and 15 GB for each 
executor which can get good performance. This 2 value does not mean more the 
better. It needs to be configured properly in case of limited resources. For 
example, In the bank scenario, it has enough CPU 32 cores each node but less 
memory 64 GB each node. So we cannot give more CPU but less memory. For 
example, when 4 cores and 12GB for each executor. It sometimes happens GC 
during the query which impact the query performance very much from the 3 second 
to more than 15 seconds. In this scenario need to increase the memory or 
decrease the CPU cores. </td>
-    </tr>
-    <tr>
-      <td>carbon.detail.batch.size </td>
-      <td>spark/carbonlib/carbon.properties </td>
-      <td>Data loading </td>
-      <td>The buffer size to store records, returned from the block scan. </td>
-      <td>In limit scenario this parameter is very important. For example your 
query limit is 1000. But if we set this value to 3000 that means we get 3000 
records from scan but spark will only take 1000 rows. So the 2000 remaining are 
useless. In one Finance test case after we set it to 100, in the limit 1000 
scenario the performance increase about 2 times in comparison to if we set this 
value to 12000. </td>
-    </tr>
-    <tr>
-      <td>carbon.use.local.dir </td>
-      <td>spark/carbonlib/carbon.properties </td>
-      <td>Data loading </td>
-      <td>Whether use YARN local directories for multi-table load disk load 
balance </td>
-      <td>If this is set it to true CarbonData will use YARN local directories 
for multi-table load disk load balance, that will improve the data load 
performance. </td>
-    </tr>
-  </tbody>
-</table>
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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License atin  
-
-      http://www.apache.org/licenses/LICENSE-2.0
-
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
---><h1>User Guide</h1><p>Welcome to Apache CarbonData. Apache 
CarbonData(incubating) is a new big data file format for faster interactive 
query using advanced columnar storage, index, compression and encoding 
techniques to improve computing efficiency, which helps in speeding up queries 
by an order of magnitude faster over PetaBytes of data. This user guide 
provides a detailed description about the CarbonData and its 
features.</p><p>Let's get started !</p>
-<ul>
-  <li><a href="quick-start-guide.html">Quick Start</a></li>
-  <li><a href="overview-of-carbondata.html">Overview</a>
-  <ul>
-    <li><a href="overview-of-carbondata.html">Introduction</a></li>
-    <li><a href="overview-of-carbondata.html">Features</a></li>
-    <li><a href="supported-data-types-in-carbondata.html">Data Types</a></li>
-    <li><a href="file-structure-of-carbondata.html">CarbonData File 
Structure</a></li>
-  </ul></li>
-  <li><a href="installation-guide.html">Installation Guide</a>
-  <ul>
-    <li><a href="installation-guide.html">Installing and Configuring 
CarbonData on Standalone Spark Cluster</a></li>
-    <li><a href="installation-guide.html">Installing and Configuring 
CarbonData on "Spark on YARN Cluster</a></li>
-  </ul></li>
-  <li><a href="configuration-parameters.html">Configuring CarbonData</a>
-  <ul>
-    <li><a href="configuration-parameters.html">System Configuration</a></li>
-    <li><a href="configuration-parameters.html">Performance 
Configuration</a></li>
-    <li><a href="configuration-parameters.html">Miscellaneous 
Configuration</a></li>
-    <li><a href="configuration-parameters.html">Spark Configuration</a></li>
-  </ul></li>
-  <li><a href="using-carbondata.html">Using CarbonData</a>
-  <ul>
-    <li><a href="data-management.html">Data Management</a></li>
-    <li><a href="ddl-operation-on-carbondata.html">DDL Operations on 
CarbonData</a></li>
-    <li><a href="dml-operation-on-carbondata.html">DML Operations on 
CarbonData</a></li>
-  </ul></li>
-  <li><a href="useful-tips-on-carbondata.html">Useful Tips</a> </li>
-  <li><a href="troubleshooting.html">Troubleshooting</a> </li>
-  <li><a href="faq.html">FAQs</a> </li>
-
-</ul>
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-<!--
-    Licensed to the Apache Software Foundation (ASF) under one
-    or more contributor license agreements.  See the NOTICE file
-    distributed with this work for additional information
-    regarding copyright ownership.  The ASF licenses this file
-    to you under the Apache License, Version 2.0 (the
-    "License"); you may not use this file except in compliance
-    with the License.  You may obtain a copy of the License at
-
-      http://www.apache.org/licenses/LICENSE-2.0
-
-    Unless required by applicable law or agreed to in writing,
-    software distributed under the License is distributed on an
-    "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
-    KIND, either express or implied.  See the License for the
-    specific language governing permissions and limitations
-    under the License.
--->
-<script src="../../js/mdNavigation.js" type="text/javascript"></script>
-<h1>Using CarbonData</h1><p>This tutorial discusses the disciplines related to 
management of data in Apache CarbonData. Following below each section is a 
brief introduction to respective disciplines related to data 
management.</p><h2>Data Management</h2><p>This section shall be dealing with 
the disciplines related to managing data in the application, focusing on 
conceptual details related to operations like load data, delete data, update 
data and Compacting Data.</p><p>For complete details refer to Data 
Management</p><h2>Data Definition Language Support</h2><p>This section deals 
with the aspects related to creation and modification of the structure of 
database. It shall discuss in detail about</p>
-<ul>
-  <li>Table creation</li>
-  <li>Table deletion</li>
-  <li>Table description</li>
-  <li>Compaction</li>
-</ul><p>For complete details refer to <a 
href="ddl-operation-on-carbondata.html">DDL Operations on 
CarbonData</a></p><h2>Data Manipulation Language Support</h2><p>This section 
deals with the aspects related to data manipulation in database. It shall 
discuss in detail about selecting, loading and deleting in a database. This 
manipulation comprises of</p>
-<ul>
-  <li>Loading data into database tables</li>
-  <li>Retrieving existing data</li>
-  <li>Deleting data from existing tables</li>
-  <li>Deleting segments from existing tables</li>
-  <li>Updating data in existing tables</li>
-</ul><p>For complete details refer to <a 
href="dml-operation-on-carbondata.html">DML Operations on CarbonData</a></p>
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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="utf-8">
+    <meta http-equiv="X-UA-Compatible" content="IE=edge">
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <link href='images/favicon.ico' rel='shortcut icon' type='image/x-icon'>
+    <!-- The above 3 meta tags *must* come first in the head; any other head 
content must come *after* these tags -->
+    <title>CarbonData</title>
+    <style>
+
+    </style>
+    <!-- Bootstrap -->
+
+    <link rel="stylesheet" href="css/bootstrap.min.css">
+    <link href="css/style.css" rel="stylesheet">
+    <!-- HTML5 shim and Respond.js for IE8 support of HTML5 elements and media 
queries -->
+    <!-- WARNING: Respond.js doesn't work if you view the page via file:// -->
+    <!--[if lt IE 9]>
+    <script 
src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js";></script>
+    <script 
src="https://oss.maxcdn.scom/respond/1.4.2/respond.min.js";></script>
+    <![endif]-->
+    <script src="js/jquery.min.js"></script>
+    <script src="js/bootstrap.min.js"></script>
+
+
+</head>
+<body>
+<header>
+    <nav class="navbar navbar-default navbar-custom cd-navbar-wrapper">
+        <div class="container">
+            <div class="navbar-header">
+                <button aria-controls="navbar" aria-expanded="false" 
data-target="#navbar" data-toggle="collapse"
+                        class="navbar-toggle collapsed" type="button">
+                    <span class="sr-only">Toggle navigation</span>
+                    <span class="icon-bar"></span>
+                    <span class="icon-bar"></span>
+                    <span class="icon-bar"></span>
+                </button>
+                <a href="index.html" class="logo">
+                    <img src="images/CarbonDataLogo.png" alt="CarbonData logo" 
title="CarbocnData logo"/>
+                </a>
+            </div>
+            <div class="navbar-collapse collapse cd_navcontnt" id="navbar">
+                <ul class="nav navbar-nav navbar-right navlist-custom">
+                    <li><a href="index.html" class="hidden-xs"><i class="fa 
fa-home" aria-hidden="true"></i> </a>
+                    </li>
+                    <li><a href="index.html" class="hidden-lg hidden-md 
hidden-sm">Home</a></li>
+                    <li class="dropdown">
+                        <a href="#" class="dropdown-toggle " 
data-toggle="dropdown" role="button" aria-haspopup="true"
+                           aria-expanded="false"> Download <span 
class="caret"></span></a>
+                        <ul class="dropdown-menu">
+                            <li>
+                                <a 
href="https://www.apache.org/dyn/closer.lua/incubator/carbondata/1.0.0-incubating";
+                                   target="_blank">Apache CarbonData 
1.0.0</a></li>
+                            <li>
+                                <a 
href="https://www.apache.org/dyn/closer.lua/incubator/carbondata/0.2.0-incubating";
+                                   target="_blank">Apache CarbonData 
0.2.0</a></li>
+                            <li>
+                                <a 
href="https://www.apache.org/dyn/closer.lua/incubator/carbondata/0.1.1-incubating";
+                                   target="_blank">Apache CarbonData 
0.1.1</a></li>
+                            <li>
+                                <a 
href="https://www.apache.org/dyn/closer.lua/incubator/carbondata/0.1.0-incubating";
+                                   target="_blank">Apache CarbonData 
0.1.0</a></li>
+                            <li>
+                                <a 
href="https://cwiki.apache.org/confluence/display/CARBONDATA/Releases";
+                                   target="_blank">Release Archive</a></li>
+                        </ul>
+                    </li>
+                    <li><a href="mainpage.html" class="">Documentation</a></li>
+                    <li class="dropdown">
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+                                <a 
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+                                    <input type="submit" value="Search"/></td>
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+                                <td align="left" style="font-size:75%" 
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+                                    <input type="checkbox" name="sitesearch" 
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+                                    Only search for CarbonData
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+                        <div id="viewpage" name="viewpage">
+                            <div class="row">
+                                <div class="col-sm-12  col-md-12">
+                                    <div>
+
+<h1>
+<a id="faqs" class="anchor" href="#faqs" aria-hidden="true"><span 
aria-hidden="true" class="octicon octicon-link"></span></a>FAQs</h1>
+
+<ul>
+<li><a href="#what-are-bad-records">What are Bad Records?</a></li>
+<li><a href="#where-are-bad-records-stored-in-carbondata">Where are Bad 
Records Stored in CarbonData?</a></li>
+<li><a href="#how-to-enable-bad-record-logging">How to enable Bad Record 
Logging?</a></li>
+<li><a href="#how-to-ignore-the-bad-records">How to ignore the Bad 
Records?</a></li>
+<li><a href="#how-to-specify-store-location-while-creating-carbon-session">How 
to specify store location while creating carbon session?</a></li>
+<li><a href="#what-is-carbon-lock-type">What is Carbon Lock Type?</a></li>
+<li><a href="#how-to-resolve-abstract-method-error">How to resolve Abstract 
Method Error?</a></li>
+</ul>
+
+<h2>
+<a id="what-are-bad-records" class="anchor" href="#what-are-bad-records" 
aria-hidden="true"><span aria-hidden="true" class="octicon 
octicon-link"></span></a>What are Bad Records?</h2>
+
+<p>Records that fail to get loaded into the CarbonData due to data type 
incompatibility or are empty or have incompatible format are classified as Bad 
Records.</p>
+
+<h2>
+<a id="where-are-bad-records-stored-in-carbondata" class="anchor" 
href="#where-are-bad-records-stored-in-carbondata" aria-hidden="true"><span 
aria-hidden="true" class="octicon octicon-link"></span></a>Where are Bad 
Records Stored in CarbonData?</h2>
+
+<p>The bad records are stored at the location set in 
carbon.badRecords.location in carbon.properties file.
+By default <strong>carbon.badRecords.location</strong> specifies the following 
location <code>/opt/Carbon/Spark/badrecords</code>.</p>
+
+<h2>
+<a id="how-to-enable-bad-record-logging" class="anchor" 
href="#how-to-enable-bad-record-logging" aria-hidden="true"><span 
aria-hidden="true" class="octicon octicon-link"></span></a>How to enable Bad 
Record Logging?</h2>
+
+<p>While loading data we can specify the approach to handle Bad Records. In 
order to analyse the cause of the Bad Records the parameter 
<code>BAD_RECORDS_LOGGER_ENABLE</code> must be set to value <code>TRUE</code>. 
There are multiple approaches to handle Bad Records which can be specified  by 
the parameter <code>BAD_RECORDS_ACTION</code>.</p>
+
+<ul>
+<li>To pad the incorrect values of the csv rows with NULL value and load the 
data in CarbonData, set the following in the query :</li>
+</ul>
+
+<pre><code>'BAD_RECORDS_ACTION'='FORCE'
+</code></pre>
+
+<ul>
+<li>To write the Bad Records without padding incorrect values with NULL in the 
raw csv (set in the parameter <strong>carbon.badRecords.location</strong>), set 
the following in the query :</li>
+</ul>
+
+<pre><code>'BAD_RECORDS_ACTION'='REDIRECT'
+</code></pre>
+
+<h2>
+<a id="how-to-ignore-the-bad-records" class="anchor" 
href="#how-to-ignore-the-bad-records" aria-hidden="true"><span 
aria-hidden="true" class="octicon octicon-link"></span></a>How to ignore the 
Bad Records?</h2>
+
+<p>To ignore the Bad Records from getting stored in the raw csv, we need to 
set the following in the query :</p>
+
+<pre><code>'BAD_RECORDS_ACTION'='IGNORE'
+</code></pre>
+
+<h2>
+<a id="how-to-specify-store-location-while-creating-carbon-session" 
class="anchor" 
href="#how-to-specify-store-location-while-creating-carbon-session" 
aria-hidden="true"><span aria-hidden="true" class="octicon 
octicon-link"></span></a>How to specify store location while creating carbon 
session?</h2>
+
+<p>The store location specified while creating carbon session is used by the 
CarbonData to store the meta data like the schema, dictionary files, dictionary 
meta data and sort indexes.</p>
+
+<p>Try creating <code>carbonsession</code> with <code>storepath</code> 
specified in the following manner :</p>
+
+<pre><code>val carbon = 
SparkSession.builder().config(sc.getConf).getOrCreateCarbonSession(&lt;store_path&gt;)
+</code></pre>
+
+<p>Example:</p>
+
+<pre><code>val carbon = 
SparkSession.builder().config(sc.getConf).getOrCreateCarbonSession("hdfs://localhost:9000/carbon/store
 ")
+</code></pre>
+
+<h2>
+<a id="what-is-carbon-lock-type" class="anchor" 
href="#what-is-carbon-lock-type" aria-hidden="true"><span aria-hidden="true" 
class="octicon octicon-link"></span></a>What is Carbon Lock Type?</h2>
+
+<p>The Apache CarbonData acquires lock on the files to prevent concurrent 
operation from modifying the same files. The lock can be of the following types 
depending on the storage location, for HDFS we specify it to be of type 
HDFSLOCK. By default it is set to type LOCALLOCK.
+The property carbon.lock.type configuration specifies the type of lock to be 
acquired during concurrent operations on table. This property can be set with 
the following values :</p>
+
+<ul>
+<li>
+<strong>LOCALLOCK</strong> : This Lock is created on local file system as 
file. This lock is useful when only one spark driver (thrift server) runs on a 
machine and no other CarbonData spark application is launched concurrently.</li>
+<li>
+<strong>HDFSLOCK</strong> : This Lock is created on HDFS file system as file. 
This lock is useful when multiple CarbonData spark applications are launched 
and no ZooKeeper is running on cluster and the HDFS supports, file based 
locking.</li>
+</ul>
+
+<h2>
+<a id="how-to-resolve-abstract-method-error" class="anchor" 
href="#how-to-resolve-abstract-method-error" aria-hidden="true"><span 
aria-hidden="true" class="octicon octicon-link"></span></a>How to resolve 
Abstract Method Error?</h2>
+
+<p>In order to build CarbonData project it is necessary to specify the spark 
profile. The spark profile sets the Spark Version. You need to specify the 
<code>spark version</code> while using Maven to build project.</p>
+</div>
+</div>
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