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All rights reserved | + <a href="#" class="term-links">Apache Software Foundation </a> | <a href="#" class="term-links"> Privacy Policy </a> + </p> + + </div> + <div class="col-md-4 col-sm-4"> + <div class="social-icon"> + <a href="#" class="icons"><i class="fa fa-facebook" aria-hidden="true"></i></a> + <a href="#" class="icons"><i class="fa fa-twitter" aria-hidden="true"></i></a> + <a href="#" class="icons"><i class="fa fa-linkedin" aria-hidden="true"></i></a> + </div> + </div> + </div> + </div> + + </footer>--> + </div> + + </div> + </div> + </div> + </section><!-- End systemblock part --> + + <!-- jQuery (necessary for Bootstrap's JavaScript plugins) --> + + <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.4/jquery.min.js";></script> + <!-- Include all compiled plugins (below), or include individual files as needed --> + <script src="js/bootstrap.min.js"></script> + </body> + </html> \ No newline at end of file http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/a1ad369d/content/docs/overview.md ---------------------------------------------------------------------- diff --git a/content/docs/overview.md b/content/docs/overview.md new file mode 100644 index 0000000..cc078d0 --- /dev/null +++ b/content/docs/overview.md @@ -0,0 +1,177 @@ +<!-- + 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. +--> + + + +This tutorial provides a detailed overview about : + +* CarbonData, +* Working and File Format +* Features +* Supported Data Types +* Compatibility +* Packaging and Interfaces. + +## Introduction + +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, in turn it will help speedup queries an order of magnitude faster over PetaBytes of data. + +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). + +Some of the Salient features of CarbonData are : +* Low-Latency for various types of data access patterns like Sequential,Random and OLAP. +* Allows fast query on fast data. +* Ensures Space Efficiency. +* General format available on Hadoop-ecosystem. + +## CarbonData File Structure + +CarbonData file contains groups of data called blocklet, along with all required information like schema, offsets and indices, etc, in a file footer, co-located in HDFS. + +The file footer can be read once to build the indices in memory, which can be utilized for optimizing the scans and processing for all subsequent queries. + +Each blocklet in the file is further divided into chunks of data called Data Chunks. Each data chunk is organized either in columnar format or row format, and stores the data of either a single column or a set of columns. All blocklets in one file contain the same number and type of Data Chunks. + + + +Each Data Chunk contains multiple groups of data called as Pages. There are three types of pages. +* Data Page: Contains the encoded data of a column/group of columns. +* Row ID Page (optional): Contains the row id mappings used when the Data Page is stored as an inverted index. +* RLE Page (optional): Contains additional metadata used when the Data Page in RLE coded. + + + +## Features + +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: + +* Stores data along with index: it can significantly accelerate query performance and reduces the I/O scans and CPU resources, where there are filters in the query. CarbonData index consists of multiple level of indices, a processing framework can leverage this index to reduce the task it needs to schedule and process, and it can also do skip scan in more finer grain unit (called blocklet) in task side scanning instead of scanning the whole file. +* Operable encoded data :Through supporting efficient compression and global encoding schemes, can query on compressed/encoded data, the data can be converted just before returning the results to the users, which is "late materialized". +* Column group: Allow multiple columns to form a column group that would be stored as row format. This reduces the row reconstruction cost at query time. +* Supports for various use cases with one single Data format : like interactive OLAP-style query, Sequential Access (big scan), Random Access (narrow scan). + +## Data Types + +The following types are supported : + +* Numeric Types + * SMALLINT + * INT/INTEGER + * BIGINT + * DOUBLE + * DECIMAL + +* Date/Time Types + * TIMESTAMP + +* String Types + * STRING + +* Complex Types + * arrays: ARRAY<data_type> + * structs: STRUCT<col_name : data_type [COMMENT col_comment], ...> + +## Compatibility + + +## Packaging and Interfaces + +### Packaging +Carbon provides following JAR packages: + + + +- **carbon-store.jar or carbondata-assembly.jar:** This is the main Jar for carbon project, the target user of it are both user and developer. + - For MapReduce application users, this jar provides API to read and write carbon files through CarbonInput/OutputFormat in carbon-hadoop module. + - For developer, this jar can be used to integrate carbon with processing engine like spark and hive, by leveraging API in carbon-processing module. + +- **carbon-spark.jar(Currently it is part of assembly jar):** provides support for spark user, spark user can manipulate carbon data files by using native spark DataFrame/SQL interface. Apart from this, in order to leverage carbon's builtin lifecycle management function, higher level concept like Managed Carbon Table, Database and corresponding DDL are introduced. + +- **carbon-hive.jar(not yet provided):** similar to carbon-spark, which provides integration to carbon and hive. + +### Interfaces + +#### API +Carbon can be used in following scenarios: + +1. For MapReduce application user + This User API is provided by carbon-hadoop. In this scenario, user can process carbon files in his MapReduce application by choosing CarbonInput/OutputFormat, and is responsible using it correctly.Currently only CarbonInputFormat is provided and OutputFormat will be provided soon. + +2. For Spark user + This User API is provided by the Spark itself. There are also two levels of APIs + * **Carbon File** + + Similar to parquet, json, or other data source in Spark, carbon can be used with data source API. For example(please refer to DataFrameAPIExample for the more detail): + ``` + // User can create a DataFrame from any data source or transformation. + val df = ... + + // Write data + // User can write a DataFrame to a carbon file + df.write + .format("carbondata") + .option("tableName", "carbontable") + .mode(SaveMode.Overwrite) + .save() + + + // read carbon data by data source API + df = carbonContext.read + .format("carbondata") + .option("tableName", "carbontable") + .load("/path") + + // User can then use DataFrame for analysis + df.count + SVMWithSGD.train(df, numIterations) + + // User can also register the DataFrame with a table name, and use SQL for analysis + df.registerTempTable("t1") // register temporary table in SparkSQL catalog + df.registerHiveTable("t2") // Or, use a implicit funtion to register to Hive metastore + sqlContext.sql("select count(*) from t1").show + ``` + + * **Managed Carbon Table** + + Carbon has in built support for high level concept like Table, Database, and supports full data lifecycle management, instead of dealing with just files, user can use carbon specific DDL to manipulate data in Table and Database level. Please refer [DDL](https://github.com/HuaweiBigData/carbondata/wiki/Language-Manual:-DDL) and [DML](https://github.com/HuaweiBigData/carbondata/wiki/Language-Manual:-DML) + ``` + // Use SQL to manage table and query data + create database db1; + use database db1; + show databases; + create table tbl1 using org.apache.carbondata.spark; + load data into table tlb1 path 'some_files'; + select count(*) from tbl1; + ``` + +3. For developer who want to integrate carbon into a processing engines like spark,hive or flink, use API provided by carbon-hadoop and carbon-processing: + - **Query** : integrate carbon-hadoop with engine specific API, like spark data source API + + - **Data life cycle management** : carbon provides utility functions in carbon-processing to manage data life cycle, like data loading, compact, retention, schema evolution. Developer can implement DDLs of their choice and leverage these utility function to do data life cycle management. + + + + + + + + + + + http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/a1ad369d/content/docs/quick_start.md ---------------------------------------------------------------------- diff --git a/content/docs/quick_start.md b/content/docs/quick_start.md new file mode 100644 index 0000000..5540e05 --- /dev/null +++ b/content/docs/quick_start.md @@ -0,0 +1,140 @@ +<!-- + 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. +--> + + +# Quick Start +This tutorial provides a quick introduction to using CarbonData. + +## Getting started with Apache CarbonData + +* [Installation](#installation) +* [Interactive Analysis with Carbon-Spark Shell](#InteractiveAnalysis-with-Carbon-Spark-Shell) + * [Basics](#basics) + * [Executing Queries](#executing-queries) + * [Prerequisites](#prerequisites) + * [Create Table](#create-table) + * [Load data to Table](#load-data-to-table) + * [Query data from table](#query-data-from-table) +* [Carbon SQL CLI](#carbon-sql-cli) + * [Basics](#basics) + * [Execute Queries in CLI](#execute-queries-in-cli) +* [Building CarbonData]() + + +## Installation +* Download released package of [Spark 1.5.0 to 1.6.2](http://spark.apache.org/downloads.html) +* Download and install [Apache Thrift 0.9.3](http://thrift-tutorial.readthedocs.io/en/latest/installation.html), make sure thrift is added to system path. +* Download [Apache CarbonData code](https://github.com/apache/incubator-carbondata) and build it. Please visit [Building CarbonData And IDE Configuration](Installing-CarbonData-And-IDE-Configuartion.md) for more information. + +## Interactive Analysis with Carbon-Spark Shell +Carbon Spark shell is a wrapper around Apache Spark Shell, it provides a simple way to learn the API, as well as a powerful tool to analyze data interactively. Please visit [Apache Spark Documentation](http://spark.apache.org/docs/latest/) for more details on Spark shell. + +#### Basics +Start Spark shell by running the following in the Carbon directory: +``` +./bin/carbon-spark-shell +``` +*Note*: In this shell SparkContext is readily available as sc and CarbonContext is available as cc. + +CarbonData stores and writes the data in its specified format at the default location on the hdfs. +By default carbon.storelocation is set as : +``` +hdfs://IP:PORT/Opt/CarbonStore +``` +And you can provide your own store location by providing configuration using --conf option like: +``` +./bin/carbon-spark-sql --conf spark.carbon.storepath=<storelocation> +``` + +#### Executing Queries + +**Prerequisites** + +Create sample.csv file in CarbonData directory. The CSV is required for loading data into Carbon. +``` +$ cd carbondata +$ cat > sample.csv << EOF + id,name,city,age + 1,david,shenzhen,31 + 2,eason,shenzhen,27 + 3,jarry,wuhan,35 + EOF +``` + +**Create table** + +``` +scala>cc.sql("create table if not exists test_table (id string, name string, city string, age Int) STORED BY 'carbondata'") +``` + +**Load data to table** +``` +scala>val dataFilePath = new File("../carbondata/sample.csv").getCanonicalPath +scala>cc.sql(s"load data inpath '$dataFilePath' into table test_table") +``` + +**Query data from table** + +``` +scala>cc.sql("select * from test_table").show +scala>cc.sql("select city, avg(age), sum(age) from test_table group by city").show +``` + +## Carbon SQL CLI +The Carbon Spark SQL CLI is a wrapper around Apache Spark SQL CLI. It is a convenient tool to execute queries input from the command line. Please visit [Apache Spark Documentation](http://spark.apache.org/docs/latest/) for more information Spark SQL CLI. + +#### Basics +Start the Carbon Spark SQL CLI, run the following in the Carbon directory : + +``` +./bin/carbon-spark-sql +``` +CarbonData stores and writes the data in its specified format at the default location on the hdfs. +By default carbon.storelocation is set as : +``` +hdfs://IP:PORT/Opt/CarbonStore +``` + +And you can provide your own store location by providing configuration using --conf option like: +``` +./bin/carbon-spark-sql --conf spark.carbon.storepath=/home/root/carbonstore +``` + +#### Execute Queries in CLI +``` +spark-sql> create table if not exists test_table (id string, name string, city string, age Int) STORED BY 'carbondata' +spark-sql> load data inpath '../sample.csv' into table test_table +spark-sql> select city, avg(age), sum(age) from test_table group by city +``` +## Building CarbonData + +To get started, get CarbonData from the [downloads]() on the [http://carbondata.incubator.apache.org.](http://carbondata.incubator.apache.org.) +CarbonData uses Hadoopâs client libraries for HDFS and YARN and Spark's libraries. Downloads are pre-packaged for a handful of popular Spark versions. + +If youâd like to build CarbonData from source, Please visit [Building CarbonData And IDE Configuration]() + + + + + + + + + + http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/a1ad369d/content/docs/troubleshooting.md ---------------------------------------------------------------------- diff --git a/content/docs/troubleshooting.md b/content/docs/troubleshooting.md new file mode 100644 index 0000000..d13de95 --- /dev/null +++ b/content/docs/troubleshooting.md @@ -0,0 +1,32 @@ +<!-- + 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. +--> + +# Troubleshooting +This tutorial is designed to provide troubleshooting for end users and developers +who are building, deploying, and using CarbonData. + +* ## Prerequisites for Developers + +* ## Prerequisites for End Users + +* ## General Prevention and Best Practices + +* ## Procedure(s) + +* ## References http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/a1ad369d/content/docs/use_cases.md ---------------------------------------------------------------------- diff --git a/content/docs/use_cases.md b/content/docs/use_cases.md new file mode 100644 index 0000000..87c2381 --- /dev/null +++ b/content/docs/use_cases.md @@ -0,0 +1,82 @@ +<!-- + 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. +--> + +# CarbonData Use Cases +This tutorial will discuss about the problems that CarbonData address.It shall take you through the identified top use cases of Carbon. + +## Introduction +For big data interactive analysis scenarios, many customers expect sub-second response to query TB-PB level data on general hardware clusters with just a few nodes. + +In the current big data ecosystem, there are few columnar storage formats such as ORC and Parquet that are designed for SQL on Big Data. Apache Hiveâs ORC format is +a columnar storage format with basic indexing capability. However, ORC cannot meet the sub-second query response expectation on TB level data, because ORC format +performs only stride level dictionary encoding and all analytical operations such as filtering and aggregation is done on the actual data. Apache Parquet is columnar +storage can improve performance in comparison to ORC, because of more efficient storage organization. Though Parquet can provide query response on TB level data in a +few seconds, it is still far from the sub-second expectation of interactive analysis users. Cloudera Kudu can effectively solve some query performance issues, but kudu +is not hadoop native, canât seamlessly integrate historic HDFS data into new kudu system. + +However, CarbonData uses specially engineered optimizations targeted to improve performance of analytical queries which can include filters, aggregation and distinct counts, +the required data to be stored in an indexed, well organized, read-optimized format, CarbonDataâs query performance can achieve sub-second response. + +## Motivation: Single Format to provide low latency response for all use cases +The main motivation behind CarbonData is to provide a single storage format for all the usecases of querying big data on Hadoop. Thus CarbonData is able to cover all use-cases +into a single storage format. + +  + +## Use Cases +* ### Sequential Access + - Supports queries that select only a few columns with a group by clause but do not contain any filters. + This results in full scan over the complete store for the selected columns. + +  + + **Scenario** + + - ETL jobs + - Log Analysis + +* ### Random Access + - Supports Point Query. These are queries used from operational applications and usually select all or most of the columns but do involve a large number of + filters which reduce the result to a small size. Such queries generally do not involve any aggregation or group by clause. + - Row-key query(like HBase) + - Narrow Scan + - Requires second/sub-second level low latency + +  + + **Scenario** + + - Operational Query + - User Profiling + +* ### Olap Style Query + - Supports Interactive data analysis for any dimensions. These are queries which are typically fired from Interactive Analysis tools. + Such queries often select a few columns but involve filters and group by on a column or a grouping expression. + It also supports queries that : + - involves aggregation/join + - Roll-up,Drill-down,Slicing and Dicing + - Low-latency ad-hoc query + +  + + **Scenario** + + - Dash-board reporting + - Fraud & Ad-hoc Analysis + http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/a1ad369d/content/docs/user_guide.md ---------------------------------------------------------------------- diff --git a/content/docs/user_guide.md b/content/docs/user_guide.md new file mode 100644 index 0000000..6db4534 --- /dev/null +++ b/content/docs/user_guide.md @@ -0,0 +1,47 @@ +<!-- + 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. +--> + +# User Guide +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, in turn it will help speedup queries an order of magnitude faster over PetaBytes of data. +This user guide provides a detailed description about the CarbonData and its features. + +Let's get started ! + +* [Overview]() + * [Introduction]() + * [Features]() + * [Data Types]() + * [Compatibility]() + * [Packaging and Interfaces]() +* [Installing CarbonData]() + * [Standalone Spark Cluster]() + * [Spark on Yarn Cluster]() +* [Configuring CarbonData]() + * [System Configuration]() + * [Performance Configuration]() + * [Spark Configuration]() +* [Using CarbonData]() + * [Data Management]() + * [DDL Operations]() + * [DML Operations]() + + + + + http://git-wip-us.apache.org/repos/asf/incubator-carbondata-site/blob/a1ad369d/content/documents/configuration.html ---------------------------------------------------------------------- diff --git a/content/documents/configuration.html b/content/documents/configuration.html new file mode 100644 index 0000000..275efa8 --- /dev/null +++ b/content/documents/configuration.html @@ -0,0 +1,441 @@ + +<!DOCTYPE html><html><head><meta charset="utf-8"><title>Untitled Document.md</title><style></style></head><body id="preview"> +<p><!â<br> +Licensed to the Apache Software Foundation (ASF) under one<br> +or more contributor license agreements. See the NOTICE file<br> +distributed with this work for additional information<br> +regarding copyright ownership. The ASF licenses this file<br> +to you under the Apache License, Version 2.0 (the<br> +âLicenseâ); you may not use this file except in compliance<br> +with the License. You may obtain a copy of the License at</p> +<pre><code> 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. +</code></pre> +<p>â></p> +<h1><a id="Configuring_CarbonData_19"></a>Configuring CarbonData</h1> +<p>This tutorial will guide you through the advance configuration of CarbonData.</p> +<h2><a id="System_Configuration_22"></a>System Configuration</h2> +<p>This section provides the details of all the configurations required for Carbon System.<br> +<b><p align=âcenterâ>System Configuration in carbon.properties</p></b></p> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.storelocation</td> +<td>/user/hive/warehouse/carbon.store</td> +<td>Location where Carbon will create the store, and write the data in its own format.NOTE: Store location should be in HDFS.</td> +</tr> +<tr> +<td>carbon.ddl.base.hdfs.url</td> +<td>hdfs://hacluster/opt/data</td> +<td>This property is used to configure the HDFS relative path from the HDFS base path, configured in fs.defaultFS. The path configured in carbon.ddl.base.hdfs.url will be appended to the HDFS path configured in fs.defaultFS. If this path is configured, then user need not pass the complete path while dataload.For example: If absolute path of the csv file is hdfs://10.18.101.155:54310/data/cnbc/2016/xyz.csv,the path âhdfs://10.18.101.155:54310â will come from property fs.defaultFS and user can configure the /data/cnbc/ as carbon.ddl.base.hdfs.url.Now while dataload user can specify the csv path as/2016/xyz.csv.</td> +</tr> +<tr> +<td>carbon.badRecords.location</td> +<td>/opt/Carbon/Spark/badrecords</td> +<td>Path where the bad records are stored.</td> +</tr> +<tr> +<td>carbon.kettle.home</td> +<td>$SPARK_HOME/carbonlib/carbonplugins</td> +<td>Path used by Carbon internally to create graph for loading the data.</td> +</tr> +<tr> +<td>carbon.data.file.version</td> +<td>2</td> +<td>If this parameter value is set to1, then the Carbon supports the data load which is in old format. If the value is set to 2, then the Carbon supports the data load of new format only.NOTE: The file format created before DataSight Spark V100R002C30 is considered as old format.</td> +</tr> +</tbody> +</table> +<h2><a id="Performance_Configuration_34"></a>Performance Configuration</h2> +<p>This section provides the details of all the configurations required for Carbon Performance Optimization.<br> +<b><p align=âcenterâ>Performance Configuration in carbon.properties</p></b></p> +<ol> +<li><strong>Data Loading Configuration</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +<th>Range</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.sort.file.buffer.size</td> +<td>20</td> +<td>File read buffer size used during sorting.</td> +<td>The value is in MB.Min=1 and Max=100</td> +</tr> +<tr> +<td>carbon.graph.rowset.size</td> +<td>100000</td> +<td>Rowset size exchanged between data load graph steps.</td> +<td>Min=500 and Max=1000000</td> +</tr> +<tr> +<td>carbon.number.of.cores.while.loading</td> +<td>6</td> +<td>Number of cores to be used while data loading.</td> +<td></td> +</tr> +<tr> +<td>carbon.sort.size</td> +<td>500000</td> +<td>Record count to sort and write to temp intermediate files.</td> +<td></td> +</tr> +<tr> +<td>carbon.enableXXHash</td> +<td>true</td> +<td>Algorithm for hashmap for hashkey calculation.</td> +<td></td> +</tr> +<tr> +<td>carbon.number.of.cores.block.sort</td> +<td>7</td> +<td>Number of cores to be used for block sort while dataloading.</td> +<td></td> +</tr> +<tr> +<td>carbon.max.driver.lru.cache.size</td> +<td>-1</td> +<td>Max LRU cache size upto which data will be loaded at the driver side.</td> +<td>The value is in MB. The default value is -1, means there is no memory limit for caching. Only integer values greater than 0 are accepted.</td> +</tr> +<tr> +<td>carbon.max.executor.lru.cache.size</td> +<td>-1</td> +<td>Max LRU cache size upto which data will be loaded at the executor side.</td> +<td>The value is in MB. The default value is -1, means there is no memory limit for caching. Only integer values greater than 0 are accepted. If this parameter is not configured, then thecarbon.max.driver.lru.cache.size value will be considered.</td> +</tr> +<tr> +<td>carbon.merge.sort.prefetch</td> +<td>true</td> +<td>Enable prefetch of data during merge sort while reading data from sort temp files in data loading.</td> +<td></td> +</tr> +<tr> +<td>carbon.update.persist.enable</td> +<td>true</td> +<td>Enabling this parameter considers persistent data. Enabling this will reduce the execution time of UPDATE operation.</td> +<td></td> +</tr> +</tbody> +</table> +<ol start="2"> +<li><strong>Compaction Configuration</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +<th>Range</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.number.of.cores.while.compacting</td> +<td>2</td> +<td>Number of cores which is used to write data during compaction.</td> +<td></td> +</tr> +<tr> +<td>carbon.compaction.level.threshold</td> +<td>4,3</td> +<td>This property is for minor compaction which decides how many segments to be merged.Example: if it is set as 2,3 then minor compaction will be triggered for every 2 segments. 3 is the number of level 1 compacted segment which is further compacted to new segment.</td> +<td>Valid values are from 0-100.</td> +</tr> +<tr> +<td>carbon.major.compaction.size</td> +<td>1024</td> +<td>Major compaction size can be configured using this parameter. Sum of the segments which is below this threshold will be merged. The value is in MB.</td> +<td></td> +</tr> +<tr> +<td>carbon.horizontal.compaction.enable</td> +<td>true</td> +<td>This property is used to turn ON/OFF horizontal compaction. After every DELETE and UPDATE statement, horizontal compaction may occur in case the delta (DELETE/ UPDATE) files becomes more than specified threshold. By default the horizontal compaction is Turned ON but can turn OFF the horizontal compaction by setting the value to false.</td> +<td></td> +</tr> +<tr> +<td>carbon.horizontal.UPDATE.compaction.threshold</td> +<td>1</td> +<td>This property specifies the threshold limit on number of UPDATE delta files within a segment. In case the number of delta files goes beyond the threshold, the UPDATE delta files within the segment becomes eligible for horizontal compaction and compacted into single UPDATE delta file.</td> +<td>By default the value is set to 1 and can be altered to values between 1 to 10000.</td> +</tr> +<tr> +<td>carbon.horizontal.DELETE.compaction.threshold</td> +<td>1</td> +<td>This property specifies the threshold limit on number of DELETE delta files within a block of a segment. In case the number of delta files goes beyond the threshold, the DELETE delta files for the particular block of the segment becomes eligible for horizontal compaction and compacted into single DELETE delta file.</td> +<td>By default the value is set to 1 and can be altered to values between 1 to 10000.</td> +</tr> +</tbody> +</table> +<ol start="3"> +<li><strong>Query Configuration</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +<th>Range</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.number.of.cores</td> +<td>4</td> +<td>Number of cores to be used while querying.</td> +<td></td> +</tr> +<tr> +<td>carbon.inmemory.record.size</td> +<td>120000</td> +<td>Number of records to be in memory while querying.</td> +<td>Min=100000 and Max=240000</td> +</tr> +<tr> +<td>carbon.enable.quick.filter</td> +<td>false</td> +<td>Improves the performance of filter query.</td> +<td></td> +</tr> +<tr> +<td>no.of.cores.to.load.blocks.in.driver</td> +<td>10</td> +<td>Number of core to load the blocks in driver.</td> +<td></td> +</tr> +</tbody> +</table> +<h2><a id="Miscellaneous_Configurations_74"></a>Miscellaneous Configurations</h2> +<p><b><p align=âcenterâ>Extra Configuration in carbon.properties</p></b></p> +<ol> +<li><strong>Time format for CarbonData</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Format</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.timestamp.format</td> +<td>yyyy-MM-dd HH:mm:ss</td> +<td>Timestamp format of input data used for timestamp data type.</td> +</tr> +</tbody> +</table> +<ol start="2"> +<li><strong>Dataload Configuration</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.sort.file.write.buffer.size</td> +<td>10485760</td> +<td>File write buffer size used during sorting.</td> +</tr> +<tr> +<td>carbon.lock.type</td> +<td>LOCALLOCK</td> +<td>This configuration specifies the type of lock to be acquired during concurrent operations on table.There are following types of lock implementation: - LOCALLOCK: 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 Carbon spark application is launched concurrently. - HDFSLOCK: Lock is created on HDFS file system as file. This lock is useful when multiple carbon spark applications are launched and no ZooKeeper is running on cluster and HDFS supports file based locking.</td> +</tr> +<tr> +<td>carbon.sort.intermediate.files.limit</td> +<td>20</td> +<td>Minimum no of intermediate files after which sort merged to be started.</td> +</tr> +<tr> +<td>carbon.block.meta.size.reserved.percentage</td> +<td>10</td> +<td>space reserved in percentage for writing block meta data in carbon data file.</td> +</tr> +<tr> +<td>carbon.csv.read.buffersize.byte</td> +<td>1048576</td> +<td>csv reading buffer size.</td> +</tr> +<tr> +<td>high.cardinality.value</td> +<td>100000</td> +<td>To identify and apply compression for non-high cardinality columns.</td> +</tr> +<tr> +<td>carbon.merge.sort.reader.thread</td> +<td>3</td> +<td>Maximum no of threads used for reading intermediate files for final merging.</td> +</tr> +<tr> +<td>carbon.load.metadata.lock.retries</td> +<td>3</td> +<td>Maximum number of retries to get the metadata lock for loading data to table.</td> +</tr> +<tr> +<td>carbon.load.metadata.lock.retry.timeout.sec</td> +<td>5</td> +<td>Interval between the retries to get the lock.</td> +</tr> +<tr> +<td>carbon.tempstore.location</td> +<td>/opt/Carbon/TempStoreLoc</td> +<td>Temporary store location. By default it takes System.getProperty(âjava.io.tmpdirâ).</td> +</tr> +<tr> +<td>carbon.load.log.counter</td> +<td>500000</td> +<td>Data loading records count logger.</td> +</tr> +</tbody> +</table> +<ol start="3"> +<li><strong>Compaction Configuration</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>carbon.numberof.preserve.segments</td> +<td>0</td> +<td>If the user wants to preserve some number of segments from being compacted then he can set this property.Example: carbon.numberof.preserve.segments=2 then 2 latest segments will always be excluded from the compaction. No segments will be preserved by default.</td> +</tr> +<tr> +<td>carbon.allowed.compaction.days</td> +<td>0</td> +<td>Compaction will merge the segments which are loaded with in the specific number of days configured.Example: if the configuration is 2, then the segments which are loaded in the time frame of 2 days only will get merged. Segments which are loaded 2 days apart will not be merged.This is disabled by default.</td> +</tr> +<tr> +<td>carbon.enable.auto.load.merge</td> +<td>false</td> +<td>To enable compaction while data loading.</td> +</tr> +</tbody> +</table> +<ol start="4"> +<li><strong>Query Configuration</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>max.query.execution.time</td> +<td>60</td> +<td>Maximum time allowed for one query to be executed. The value is in minutes.</td> +</tr> +<tr> +<td>carbon.enableMinMax</td> +<td>true</td> +<td>Min max is feature added to enhance query performance. To disable this feature, set it false.</td> +</tr> +</tbody> +</table> +<ol start="5"> +<li><strong>Global Dictionary Configurations</strong></li> +</ol> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>high.cardinality.identify.enable</td> +<td>true</td> +<td>If the parameter is true, the high cardinality columns of the dictionary code are automatically recognized and these columns will not be used as global dictionary encoding. If the parameter is false, all dictionary encoding columns are used as dictionary encoding.The high cardinality column must meet the following requirements:value of cardinality > configured value of high.cardinalityEqually, the value of cardinality is higher than the threshold.value of cardinality/ row number x 100 > configured value of high.cardinality.row.count.percentageEqually, the ratio of the cardinality value to data row number is higher than the configured percentage.</td> +</tr> +<tr> +<td>high.cardinality.threshold</td> +<td>1000000</td> +<td>Threshold to identify whether high cardinality column.Configuration value formula:Value of cardinality > configured value of high.cardinalityThe minimum value is 10000.</td> +</tr> +<tr> +<td>high.cardinality.row.count.percentage</td> +<td>80</td> +<td>Percentage to identify whether column cardinality is more than configured percent of total row count.Configuration value formula:Value of cardinality/ row number x 100 > configured value of high.cardinality.row.count.percentageThe value of the parameter must be larger than 0.</td> +</tr> +<tr> +<td>carbon.cutOffTimestamp</td> +<td>1970-01-01 05:30:00</td> +<td>Sets the start date for calculating the timestamp. Java counts the number of milliseconds from start of â1970-01-01 00:00:00â. This property is used to customize the start of position. For example â2000-01-01 00:00:00â.The date must be in the form âcarbon.timestamp.formatâ.NOTE: The Carbon supports data store up to 68 years from the cut-off time defined. For example, if the cut-off time is 1970-01-01 05:30:00, then the data can be stored up to 2038-01-01 05:30:00.</td> +</tr> +<tr> +<td>carbon.timegranularity</td> +<td>SECOND</td> +<td>The property used to set the data granularity level DAY, HOUR, MINUTE, or SECOND.</td> +</tr> +</tbody> +</table> +<h2><a id="Spark_Configuration_125"></a>Spark Configuration</h2> +<p><b><p align=âcenterâ>Spark Configuration Reference in spark-defaults.conf</p></b></p> +<table class="table table-striped table-bordered"> +<thead> +<tr> +<th>Parameter</th> +<th>Default Value</th> +<th>Description</th> +</tr> +</thead> +<tbody> +<tr> +<td>spark.driver.memory</td> +<td>1g</td> +<td>Amount of memory to use for the driver process, i.e. where SparkContext is initialized.NOTE: In client mode, this config must not be set through the SparkConf directly in your application, because the driver JVM has already started at that point. Instead, please set this through the --driver-memory command line option or in your default properties file.</td> +</tr> +<tr> +<td>spark.executor.memory</td> +<td>1g</td> +<td>Amount of memory to use per executor process.</td> +</tr> +<tr> +<td>spark.sql.bigdata.register.analyseRule</td> +<td>org.apache.spark.sql.hive.acl.CarbonAccessControlRules</td> +<td>CarbonAccessControlRules need to be set for enabling Access Control.</td> +</tr> +</tbody> +</table> + +</body></html>
