Modified: zeppelin/site/docs/0.9.0/search_data.json URL: http://svn.apache.org/viewvc/zeppelin/site/docs/0.9.0/search_data.json?rev=1890433&r1=1890432&r2=1890433&view=diff ============================================================================== --- zeppelin/site/docs/0.9.0/search_data.json (original) +++ zeppelin/site/docs/0.9.0/search_data.json Thu Jun 3 15:43:41 2021 @@ -25,7 +25,7 @@ "/interpreter/pig.html": { "title": "Pig Interpreter for Apache Zeppelin", - "content" : "Pig Interpreter for Apache ZeppelinOverviewApache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.Supported interpreter type%pig.script (default Pig interpreter, so you can use %pig)%pig.script is like the Pig grunt shell. Anything you can run in Pig grunt shell can be run in %pig.script interpreter, it is used for running Pig script where you donât need to visualize the data, it is suitable for data munging. %pig.query%pig.query is a little different compared with %pig.script. It is used for exploratory data analysis via Pig latin where you can leverage Zeppelinâs visualization ability. There&#39;re 2 minor differences in the last statement between %pig .script and %pig.queryNo pig alias in the last statement in %pig.query (read the examples below).The last statement must be in single line in %pig.queryHow to useHow to setup Pig execution modes.Local ModeSet zeppelin.pig.execType as local.MapReduce ModeSet zeppelin.pig.execType as mapreduce. HADOOP_CONF_DIR needs to be specified in ZEPPELIN_HOME/conf/zeppelin-env.sh.Tez Local ModeOnly Tez 0.7 is supported. Set zeppelin.pig.execType as tez_local.Tez ModeOnly Tez 0.7 is supported. Set zeppelin.pig.execType as tez. HADOOP_CONF_DIR and TEZ_CONF_DIR needs to be specified in ZEPPELIN_HOME/conf/zeppelin-env.sh.Spark Local ModeOnly Spark 1.6.x is supported, by default it is Spark 1.6.3. Set zeppelin.pig.execType as spark_local.Spark ModeOnly Spark 1.6.x is supported, by default it is Spark 1.6.3. Set zeppelin.pig.execType as spark. For now, only yarn-client mode is supported. To enable it, you need to set property SPARK_MASTER to yarn-client and set SPARK_JAR to the spark assembly jar.How to choose custom Spark VersionBy default, Pig Interpreter would use Spark 1.6.3 built with scala 2.10, if you want to use another spark version or scala version, you need to rebuild Zeppelin by specifying the custom Spark version via -Dpig.spark.version= and scala version via -Dpig.scala.version= in the maven build command.How to configure interpreterAt the Interpreters menu, you have to create a new Pig interpreter. Pig interpreter has below properties by default.And you can set any Pig properties here which will be passed to Pig engine. (like tez.queue.name &amp; mapred.job.queue.name).Besides, we use paragraph title as job name if it exists, else use the last line of Pig script. So you can use that to find app running in YARN RM UI. Property Default Description zeppelin.pig.execType mapreduce Execution mode for pig runtime. local | mapreduce | tez_local | tez | spark_local | spark zeppelin.pig.includeJobSta ts false whether display jobStats info in %pig.script zeppelin.pig.maxResult 1000 max row number displayed in %pig.query tez.queue.name default queue name for tez engine mapred.job.queue.name default queue name for mapreduce engine SPARK_MASTER local local | yarn-client SPARK_JAR The spark assembly jar, both jar in local or hdfs is supported. Put it on hdfs could have performance benefit Examplepig%pigbankText = load &#39;bank.csv&#39; using PigStorage(&#39;;&#39;);bank = foreach bankText generate $0 as age, $1 as job, $2 as marital, $3 as education, $5 as balance; bank = filter bank by age != &#39;&quot;age&quot;&#39;;bank = foreach bank generate (int)age, REPLACE(job,&#39;&quot;&#39;,&#39;&#39;) as job, REPLACE(marital, &#39;&quot;&#39;, &#39;&a mp;#39;) as marital, (int)(REPLACE(balance, &#39;&quot;&#39;, &#39;&#39;)) as balance;store bank into &#39;clean_bank.csv&#39; using PigStorage(&#39;;&#39;); -- this statement is optional, it just show you that most of time %pig.script is used for data munging before querying the data. pig.queryGet the number of each age where age is less than 30%pig.querybank_data = filter bank by age &lt; 30;b = group bank_data by age;foreach b generate group, COUNT($1);The same as above, but use dynamic text form so that use can specify the variable maxAge in textbox. (See screenshot below). Dynamic form is a very cool feature of Zeppelin, you can refer this link) for details.%pig.querybank_data = filter bank by age &lt; ${maxAge=40};b = group bank_data by age;foreach b generate group, COUNT($1) as count;Get the number of each age for specific marital type, also use dynamic form here. User can choose the marital type in the dropdown list (see screenshot below).%pig.querybank_data = filter bank by marital==&#39;${marital=single,single|divorced|married}&#39;;b = group bank_data by age;foreach b generate group, COUNT($1) as count;The above examples are in the Pig tutorial note in Zeppelin, you can check that for details. Here&#39;s the screenshot.Data is shared between %pig and %pig.query, so that you can do some common work in %pig, and do different kinds of query based on the data of %pig. Besides, we recommend you to specify alias explicitly so that the visualization can display the column name correctly. In the above example 2 and 3 of %pig.query, we name COUNT($1) as count. If you don&#39;t do this, then we will name it using position. E.g. in the above first example of %pig.query, we will use col_1 in chart to represent COUNT($1).", + "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Pig Interpreter for Apache ZeppelinOverviewApache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.Supported interpreter type%pig.scrip t (default Pig interpreter, so you can use %pig)%pig.script is like the Pig grunt shell. Anything you can run in Pig grunt shell can be run in %pig.script interpreter, it is used for running Pig script where you donât need to visualize the data, it is suitable for data munging. %pig.query%pig.query is a little different compared with %pig.script. It is used for exploratory data analysis via Pig latin where you can leverage Zeppelinâs visualization ability. There&#39;re 2 minor differences in the last statement between %pig.script and %pig.queryNo pig alias in the last statement in %pig.query (read the examples below).The last statement must be in single line in %pig.queryHow to useHow to setup Pig execution modes.Local ModeSet zeppelin.pig.execType as local.MapReduce ModeSet zeppelin.pig.execType as mapreduce. HADOOP_CONF_DIR needs to be specified in ZEPPELIN_HOME/conf/zeppelin-env.sh.Tez Local ModeOnly Tez 0.7 is supported. Set zeppelin.pig.execType as tez_local.Tez M odeOnly Tez 0.7 is supported. Set zeppelin.pig.execType as tez. HADOOP_CONF_DIR and TEZ_CONF_DIR needs to be specified in ZEPPELIN_HOME/conf/zeppelin-env.sh.Spark Local ModeOnly Spark 1.6.x is supported, by default it is Spark 1.6.3. Set zeppelin.pig.execType as spark_local.Spark ModeOnly Spark 1.6.x is supported, by default it is Spark 1.6.3. Set zeppelin.pig.execType as spark. For now, only yarn-client mode is supported. To enable it, you need to set property SPARK_MASTER to yarn-client and set SPARK_JAR to the spark assembly jar.How to choose custom Spark VersionBy default, Pig Interpreter would use Spark 1.6.3 built with scala 2.10, if you want to use another spark version or scala version, you need to rebuild Zeppelin by specifying the custom Spark version via -Dpig.spark.version= and scala version via -Dpig.scala.version= in the maven build command.How to configure interpreterAt the Interpreters menu, you have to create a new Pig interpreter. Pig interpreter has below properti es by default.And you can set any Pig properties here which will be passed to Pig engine. (like tez.queue.name &amp; mapred.job.queue.name).Besides, we use paragraph title as job name if it exists, else use the last line of Pig script. So you can use that to find app running in YARN RM UI. Property Default Description zeppelin.pig.execType mapreduce Execution mode for pig runtime. local | mapreduce | tez_local | tez | spark_local | spark zeppelin.pig.includeJobStats false whether display jobStats info in %pig.script zeppelin.pig.maxResult 1000 max row number displayed in %pig.query tez.queue.name default queue name for tez engine mapred.job.queue.name default queue name for mapreduce engine SPARK_MASTER local local | yarn-client SPARK_JAR The spark asse mbly jar, both jar in local or hdfs is supported. Put it on hdfs could have performance benefit Examplepig%pigbankText = load &#39;bank.csv&#39; using PigStorage(&#39;;&#39;);bank = foreach bankText generate $0 as age, $1 as job, $2 as marital, $3 as education, $5 as balance; bank = filter bank by age != &#39;&quot;age&quot;&#39;;bank = foreach bank generate (int)age, REPLACE(job,&#39;&quot;&#39;,&#39;&#39;) as job, REPLACE(marital, &#39;&quot;&#39;, &#39;&#39;) as marital, (int)(REPLACE(balance, &#39;&quot;&#39;, &#39;&#39;)) as balance;store bank into &#39;clean_bank.csv&#39; using PigStorage(&#39;;&#39;); -- this statement is optional, it just show you that most of time %pig.script is used for data munging before querying the data. pig.queryGet the number of each age where age is less than 30%pig.querybank_data = filter bank by age &lt; 30;b = group bank_dat a by age;foreach b generate group, COUNT($1);The same as above, but use dynamic text form so that use can specify the variable maxAge in textbox. (See screenshot below). Dynamic form is a very cool feature of Zeppelin, you can refer this link) for details.%pig.querybank_data = filter bank by age &lt; ${maxAge=40};b = group bank_data by age;foreach b generate group, COUNT($1) as count;Get the number of each age for specific marital type, also use dynamic form here. User can choose the marital type in the dropdown list (see screenshot below).%pig.querybank_data = filter bank by marital==&#39;${marital=single,single|divorced|married}&#39;;b = group bank_data by age;foreach b generate group, COUNT($1) as count;The above examples are in the Pig tutorial note in Zeppelin, you can check that for details. Here&#39;s the screenshot.Data is shared between %pig and %pig.query, so that you can do some common work in %pig, and do different kinds of query based on the data of %pig . Besides, we recommend you to specify alias explicitly so that the visualization can display the column name correctly. In the above example 2 and 3 of %pig.query, we name COUNT($1) as count. If you don&#39;t do this, then we will name it using position. E.g. in the above first example of %pig.query, we will use col_1 in chart to represent COUNT($1).", "url": " /interpreter/pig.html", "group": "manual", "excerpt": "Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs." @@ -157,7 +157,7 @@ "/interpreter/sap.html": { "title": "SAP BusinessObjects Interpreter for Apache Zeppelin", - "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->SAP BusinessObjects (Universe) Interpreter for Apache ZeppelinOverviewSAP BusinessObjects BI platform (universes) can simplify the lives of business users and IT staff. SAP BusinessObjects is based on universes. The universe contains dual-semantic layer model. The users make queries upon universes. This interpreter is new interface for universes.Disclaimer SAP interpreter is not official interpreter for SAP BusinessObjects BI platf orm. It uses BI Semantic Layer REST APIThis interpreter is not directly supported by SAP AG.Tested with versions 4.2SP3 (14.2.3.2220) and 4.2SP5. There is no support for filters in UNX-universes converted from old UNV format.The universe name must be unique.Configuring SAP Universe InterpreterAt the &quot;Interpreters&quot; menu, you can edit SAP interpreter or create new one. Zeppelin provides these properties for SAP. Property Name Value Description universe.api.url http://localhost:6405/biprws The base url for the SAP BusinessObjects BI platform. You have to edit "localhost" that you may use (ex. http://0.0.0.0:6405/biprws) universe.authType secEnterprise The type of authentication for API of Universe. Available values: secEnterprise, secLDAP, secWinAD, secSAPR3 universe.password The BI platform user password universe.user Administrator The BI platform user login How to use Choose the universe Choo se dimensions and measures in select statement Define conditions in where statementYou can compare two dimensions/measures or use Filter (without value). Dimesions/Measures can be compared with static values, may be is null or is not null, contains or not in list.Available the nested conditions (using braces &quot;()&quot;). &quot;and&quot; operator have more priority than &quot;or&quot;. If generated query contains promtps, then promtps will appear as dynamic form after paragraph submitting.Example query%sapuniverse [Universe Name];select [Folder1].[Dimension2], [Folder2].[Dimension3], [Measure1]where [Filter1] and [Date] &gt; &#39;2018-01-01 00:00:00&#39; and [Folder1].[Dimension4] is not null and [Folder1].[Dimension5] in (&#39;Value1&#39;, &#39;Value2&#39;);distinct keywordYou can write keyword distinct after keyword select to return only distinct (different) values.Example query```sql%sapuniverse [Universe Name];select distinct [Folder1].[Dimension2], [Measure1]where [Filter1];```limit keywordYou can write keyword limit and limit value in the end of query to limit the number of records returned based on a limit value.Example query```sql%sapuniverse [Universe Name];select [Folder1].[Dimension2], [Measure1]where [Filter1]limit 100;```Object InterpolationThe SAP interpreter also supports interpolation of ZeppelinContext objects into the paragraph text.To enable this feature set universe.interpolation to true. The following example shows one use of this facility:In Scala cell:z.put(&quot;curr_date&quot;, &quot;2018-01-01 00:00:00&quot;)In later SAP cell:where [Filter1] and [Date] &gt; &#39;{curr_date}&#39;", + "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->SAP BusinessObjects (Universe) Interpreter for Apache ZeppelinOverviewSAP BusinessObjects BI platform (universes) can simplify the lives of business users and IT staff. SAP BusinessObjects is based on universes. The universe contains dual-semantic layer model. The users make queries upon universes. This interpreter is new interface for universes.Disclaimer SAP interpreter is not official interpreter for SAP BusinessObjects BI platf orm. It uses BI Semantic Layer REST APIThis interpreter is not directly supported by SAP AG.Tested with versions 4.2SP3 (14.2.3.2220) and 4.2SP5. There is no support for filters in UNX-universes converted from old UNV format.The universe name must be unique.Configuring SAP Universe InterpreterAt the &quot;Interpreters&quot; menu, you can edit SAP interpreter or create new one. Zeppelin provides these properties for SAP. Property Name Value Description universe.api.url http://localhost:6405/biprws The base url for the SAP BusinessObjects BI platform. You have to edit "localhost" that you may use (ex. http://0.0.0.0:6405/biprws) universe.authType secEnterprise The type of authentication for API of Universe. Available values: secEnterprise, secLDAP, secWinAD, secSAPR3 universe.password The BI platform user password universe.user Administrator The BI platform user login How to use Choose the universe Choo se dimensions and measures in select statement Define conditions in where statementYou can compare two dimensions/measures or use Filter (without value). Dimesions/Measures can be compared with static values, may be is null or is not null, contains or not in list.Available the nested conditions (using braces &quot;()&quot;). &quot;and&quot; operator have more priority than &quot;or&quot;. If generated query contains promtps, then promtps will appear as dynamic form after paragraph submitting.Example query%sapuniverse [Universe Name];select [Folder1].[Dimension2], [Folder2].[Dimension3], [Measure1]where [Filter1] and [Date] &gt; &#39;2018-01-01 00:00:00&#39; and [Folder1].[Dimension4] is not null and [Folder1].[Dimension5] in (&#39;Value1&#39;, &#39;Value2&#39;);distinct keywordYou can write keyword distinct after keyword select to return only distinct (different) values.Example query%sapuniverse [Universe Name];select distin ct [Folder1].[Dimension2], [Measure1]where [Filter1];limit keywordYou can write keyword limit and limit value in the end of query to limit the number of records returned based on a limit value.Example query%sapuniverse [Universe Name];select [Folder1].[Dimension2], [Measure1]where [Filter1]limit 100;Object InterpolationThe SAP interpreter also supports interpolation of ZeppelinContext objects into the paragraph text.To enable this feature set universe.interpolation to true. The following example shows one use of this facility:In Scala cell:z.put(&quot;curr_date&quot;, &quot;2018-01-01 00:00:00&quot;)In later SAP cell:where [Filter1] and [Date] &gt; &#39;{curr_date}&#39;", "url": " /interpreter/sap.html", "group": "interpreter", "excerpt": "SAP BusinessObjects BI platform can simplify the lives of business users and IT staff. SAP BusinessObjects is based on universes. The universe contains dual-semantic layer model. The users make queries upon universes. This interpreter is new interface for universes." @@ -256,7 +256,7 @@ "/interpreter/flink.html": { "title": "Flink Interpreter for Apache Zeppelin", - "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Flink interpreter for Apache ZeppelinOverviewApache Flink is an open source platform for distributed stream and batch data processing. Flinkâs core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams. Flink also builds batch processing on top of the streaming engine, overlaying native iteration support, managed memory, and program opt imization.In Zeppelin 0.9, we refactor the Flink interpreter in Zeppelin to support the latest version of Flink. Only Flink 1.10+ is supported, old version of flink won&#39;t work.Apache Flink is supported in Zeppelin with Flink interpreter group which consists of below five interpreters. Name Class Description %flink FlinkInterpreter Creates ExecutionEnvironment/StreamExecutionEnvironment/BatchTableEnvironment/StreamTableEnvironment and provides a Scala environment %flink.pyflink PyFlinkInterpreter Provides a python environment %flink.ipyflink IPyFlinkInterpreter Provides an ipython environment %flink.ssql FlinkStreamSqlInterpreter Provides a stream sql environment %flink.bsql FlinkBatchSqlInterpreter Provides a batch sql environment PrerequisitesDownload Flink 1.10 for scala 2.11 (Only scala-2.11 is supported, scala-2.12 is not supported yet in Zeppelin)ConfigurationThe Flink interpreter can be config ured with properties provided by Zeppelin (as following table).You can also add and set other flink properties which are not listed in the table. For a list of additional properties, refer to Flink Available Properties. Property Default Description FLINK_HOME Location of flink installation. It is must be specified, otherwise you can not use flink in Zeppelin HADOOP_CONF_DIR Location of hadoop conf, this is must be set if running in yarn mode HIVE_CONF_DIR Location of hive conf, this is must be set if you want to connect to hive metastore flink.execution.mode local Execution mode of flink, e.g. local | yarn | remote flink.execution.remote.host Host name of running JobManager. Only used for remote mode flink.execution.remote.port Port of running JobManager. Only used for remote mode flink.jm.memory 1024 Total number of memory(mb) of JobManager flink.tm.memory 1024 To tal number of memory(mb) of TaskManager flink.tm.slot 1 Number of slot per TaskManager local.number-taskmanager 4 Total number of TaskManagers in local mode flink.yarn.appName Zeppelin Flink Session Yarn app name flink.yarn.queue default queue name of yarn app flink.webui.yarn.useProxy false whether use yarn proxy url as flink weburl, e.g. http://resource-manager:8088/proxy/application15833965980680004 flink.webui.yarn.address Set this value only when your yarn address is mapped to some other address, e.g. some cloud vender will map http://resource-manager:8088 to https://xxx-yarn.yy.cn/gateway/kkk/yarn flink.udf.jars Flink udf jars (comma separated), zeppelin will register udf in this jar automatically for user. These udf jars could be either local files or hdfs files if you have hadoop installed. The udf name is the class name. flink.udf.jars.packages Packages (comma separate d) that would be searched for the udf defined in flink.udf.jars. flink.execution.jars Additional user jars (comma separated), these jars could be either local files or hdfs files if you have hadoop installed. flink.execution.packages Additional user packages (comma separated), e.g. org.apache.flink:flink-connector-kafka2.11:1.10,org.apache.flink:flink-connector-kafka-base2.11:1.10.0,org.apache.flink:flink-json:1.10.0 zeppelin.flink.concurrentBatchSql.max 10 Max concurrent sql of Batch Sql (%flink.bsql) zeppelin.flink.concurrentStreamSql.max 10 Max concurrent sql of Stream Sql (%flink.ssql) zeppelin.pyflink.python python Python binary executable for PyFlink table.exec.resource.default-parallelism 1 Default parallelism for flink sql job zeppelin.flink.scala.color true Whether display scala shell output in colorful format zeppelin.flink.enableHive false Whether enable hive zep pelin.flink.hive.version 2.3.4 Hive version that you would like to connect zeppelin.flink.module.enableHive false Whether enable hive module, hive udf take precedence over flink udf if hive module is enabled. zeppelin.flink.maxResult 1000 max number of row returned by sql interpreter flink.interpreter.close.shutdown_cluster true Whether shutdown application when closing interpreter zeppelin.interpreter.close.cancel_job true Whether cancel flink job when closing interpreter zeppelin.flink.job.check_interval 1000 Check interval (in milliseconds) to check flink job progress StreamExecutionEnvironment, ExecutionEnvironment, StreamTableEnvironment, BatchTableEnvironmentZeppelin will create 6 variables as flink scala (%flink) entry point:senv (StreamExecutionEnvironment), benv (ExecutionEnvironment)stenv (StreamTableEnvironment for blink planner) btenv (BatchTableEnvironment for blink planner)stenv_2 (Str eamTableEnvironment for flink planner) btenv_2 (BatchTableEnvironment for flink planner)And will create 6 variables as pyflink (%flink.pyflink or %flink.ipyflink) entry point:s_env (StreamExecutionEnvironment), b_env (ExecutionEnvironment)st_env (StreamTableEnvironment for blink planner) bt_env (BatchTableEnvironment for blink planner)st_env_2 (StreamTableEnvironment for flink planner) bt_env_2 (BatchTableEnvironment for flink planner)Blink/Flink PlannerThere&#39;re 2 planners supported by Flink&#39;s table api: flink &amp; blink.If you want to use DataSet api, and convert it to flink table then please use flink planner (btenv_2 and stenv_2).In other cases, we would always recommend you to use blink planner. This is also what flink batch/streaming sql interpreter use (%flink.bsql &amp; %flink.ssql)Check this page for the difference between flink planner and blink planner.Execution mode (Local/Remote/Yarn)Flink in Zeppelin supports 3 execution modes ( flink.execution.mode):LocalRemoteYarnRun Flink in Local ModeRunning Flink in Local mode will start a MiniCluster in local JVM. By default, the local MiniCluster will use port 8081, so make sure this port is available in your machine,otherwise you can configure rest.port to specify another port. You can also specify local.number-taskmanager and flink.tm.slot to customize the number of TM and number of slots per TM, because by default it is only 4 TM with 1 Slots which may not be enough for some cases.Run Flink in Remote ModeRunning Flink in remote mode will connect to a existing flink cluster which could be standalone cluster or yarn session cluster. Besides specifying flink.execution.mode to be remote. You also need to specifyflink.execution.remote.host and flink.execution.remote.port to point to flink job manager.Run Flink in Yarn ModeIn order to run flink in Yarn mode, you need to make the following settings:Set flink.execution.mode to yarnSet HADOOP_CONF_DIR in flink&#39;s in terpreter setting.Make sure hadoop command is on your PATH. Because internally flink will call command hadoop classpath and load all the hadoop related jars in the flink interpreter processHow to use HiveIn order to use Hive in Flink, you have to make the following setting.Set zeppelin.flink.enableHive to be trueSet zeppelin.flink.hive.version to be the hive version you are using.Set HIVE_CONF_DIR to be the location where hive-site.xml is located. Make sure hive metastore is started and you have configured hive.metastore.uris in hive-site.xmlCopy the following dependencies to the lib folder of flink installation. flink-connector-hive_2.11â1.10.0.jarflink-hadoop-compatibility_2.11â1.10.0.jarhive-exec-2.x.jar (for hive 1.x, you need to copy hive-exec-1.x.jar, hive-metastore-1.x.jar, libfb303â0.9.2.jar and libthrift-0.9.2.jar)Flink Batch SQL%flink.bsql is used for flink&#39;s batch sql. You can type help to get all the available commands. It supports all the flink sql, including DML/DDL/DQL.Use insert into statement for batch ETLUse select statement for batch data analytics Flink Streaming SQL%flink.ssql is used for flink&#39;s streaming sql. You just type help to get all the available commands. It supports all the flink sql, including DML/DDL/DQL.Use insert into statement for streaming ETLUse select statement for streaming data analyticsStreaming Data VisualizationZeppelin supports 3 types of streaming data analytics:* Single* Update* Appendtype=singleSingle mode is for the case when the result of sql statement is always one row, such as the following example. The output format is HTML, and you can specify paragraph local property template for the final output content template. And you can use {i} as placeholder for the ith column of result. type=updateUpdate mode is suitable for the case when the output is more than one rows, and always will be updated continuously. Hereâs one example where we use group by. type=appendAppend mode is suitable for the scenario where output data is always appended. E.g. the following example which use tumble window. Flink UDFYou can use Flink scala UDF or Python UDF in sql. UDF for batch and streaming sql is the same. Here&#39;re 2 examples.Scala UDF%flinkclass ScalaUpper extends ScalarFunction { def eval(str: String) = str.toUpperCase}btenv.registerFunction(&quot;scala_upper&quot;, new ScalaUpper())Python UDF%flink.pyflinkclass PythonUpper(ScalarFunction): def eval(self, s): return s.upper()bt_env.register_function(&quot;python_upper&quot;, udf(PythonUpper(), DataTypes.STRING(), DataTypes.STRING()))Zeppelin only supports scala and python for flink interpreter, if you want to write java udf or the udf is pretty complicated which make it not suitable to write in Zeppelin,then you can write the udf in IDE and build a udf jar.In Zeppelin you just need to specify flink.udf.jars to this jar, and flinkinterpreter will detect all the udfs in this jar and register all the udfs to TableEnvironment, the udf name is the class name.PyFlink(%flink.pyflink)In order to use PyFlink in Zeppelin, you just need to do the following configuration.* Install apache-flink (e.g. pip install apache-flink)* Set zeppelin.pyflink.python to the python executable where apache-flink is installed in case you have multiple python installed.* Copy flink-python_2.11â1.10.0.jar from flink opt folder to flink lib folderAnd PyFlink will create 6 variables for you:s_env (StreamExecutionEnvironment), b_env (ExecutionEnvironment)st_env (StreamTableEnvironment for blink planner) bt_env (BatchTableEnvironment for blink planner)st_env_2 (StreamTableEnvironment for flink planner) bt_env_2 (BatchTableEnvironment for flink planner)IPython Support(%flink.ipyflink)By default, zeppelin would use IPython in %flink.pyflink when IPython is available, Otherwise it would fall back to the original python implementation.For the IPython features, you can refer docPython InterpreterZeppelinContextZeppelin automatically injects ZeppelinContext as variable z in your Scala/Python environment. ZeppelinContext provides some additional functions and utilities.See Zeppelin-Context for more details. You can use z to display both flink DataSet and batch/stream table.Display DataSetDisplay Batch TableDisplay Stream TableParagraph local propertiesIn the section of Streaming Data Visualization, we demonstrate the different visualization type via paragraph local properties: type. In this section, we will list and explain all the supported local properties in flink interpreter. Property Default Description type Used in %flink.ssql to specify the streaming visualization type (single, update, append) refreshInterval 3000 Used in `%flink.ssql` to specify frontend refresh interval for streaming data visualization. template {0} Used in `%flink.ssql` to specify html template for `single` type of streaming da ta visualization, And you can use `{i}` as placeholder for the {i}th column of the result. parallelism Used in %flink.ssql & %flink.bsql to specify the flink sql job parallelism maxParallelism Used in %flink.ssql & %flink.bsql to specify the flink sql job max parallelism in case you want to change parallelism later. For more details, refer this [link](https://ci.apache.org/projects/flink/flink-docs-release-1.10/dev/parallel.html#setting-the-maximum-parallelism) savepointDir If you specify it, then when you cancel your flink job in Zeppelin, it would also do savepoint and store state in this directory. And when you resume your job, it would resume from this savepoint. execution.savepoint.path When you resume your job, it would resume from this savepoint path. resumeFromSavepoint Resume flink job from savepoint if you specify savepointDir. resumeFromLatestCheckpoint Resume flink job from lates t checkpoint if you enable checkpoint. runAsOne false All the insert into sql will run in a single flink job if this is true. Tutorial NotesZeppelin is shipped with several Flink tutorial notes which may be helpful for you. You check more features in the tutorial notes.", + "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Flink interpreter for Apache ZeppelinOverviewApache Flink is an open source platform for distributed stream and batch data processing. Flinkâs core is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations over data streams. Flink also builds batch processing on top of the streaming engine, overlaying native iteration support, managed memory, and program opt imization.In Zeppelin 0.9, we refactor the Flink interpreter in Zeppelin to support the latest version of Flink. Only Flink 1.10+ is supported, old versions of flink won&#39;t work.Apache Flink is supported in Zeppelin with the Flink interpreter group which consists of the five interpreters listed below. Name Class Description %flink FlinkInterpreter Creates ExecutionEnvironment/StreamExecutionEnvironment/BatchTableEnvironment/StreamTableEnvironment and provides a Scala environment %flink.pyflink PyFlinkInterpreter Provides a python environment %flink.ipyflink IPyFlinkInterpreter Provides an ipython environment %flink.ssql FlinkStreamSqlInterpreter Provides a stream sql environment %flink.bsql FlinkBatchSqlInterpreter Provides a batch sql environment PrerequisitesDownload Flink 1.10 for scala 2.11 (Only scala-2.11 is supported, scala-2.12 is not supported yet in Zeppelin)ConfigurationThe Flink interpret er can be configured with properties provided by Zeppelin (as following table).You can also add and set other flink properties which are not listed in the table. For a list of additional properties, refer to Flink Available Properties. Property Default Description FLINK_HOME Location of flink installation. It is must be specified, otherwise you can not use flink in Zeppelin HADOOP_CONF_DIR Location of hadoop conf, this is must be set if running in yarn mode HIVE_CONF_DIR Location of hive conf, this is must be set if you want to connect to hive metastore flink.execution.mode local Execution mode of flink, e.g. local | yarn | remote flink.execution.remote.host Host name of running JobManager. Only used for remote mode flink.execution.remote.port Port of running JobManager. Only used for remote mode flink.jm.memory 1024 Total number of memory(mb) of JobManager flink.tm.memo ry 1024 Total number of memory(mb) of TaskManager flink.tm.slot 1 Number of slot per TaskManager local.number-taskmanager 4 Total number of TaskManagers in local mode flink.yarn.appName Zeppelin Flink Session Yarn app name flink.yarn.queue default queue name of yarn app flink.webui.yarn.useProxy false whether use yarn proxy url as flink weburl, e.g. http://resource-manager:8088/proxy/application15833965980680004 flink.webui.yarn.address Set this value only when your yarn address is mapped to some other address, e.g. some cloud vender will map http://resource-manager:8088 to https://xxx-yarn.yy.cn/gateway/kkk/yarn flink.udf.jars Flink udf jars (comma separated), zeppelin will register udf in this jar automatically for user. These udf jars could be either local files or hdfs files if you have hadoop installed. The udf name is the class name. flink.udf.jars.packages Packages (comma separated) that would be searched for the udf defined in flink.udf.jars. flink.execution.jars Additional user jars (comma separated), these jars could be either local files or hdfs files if you have hadoop installed. flink.execution.packages Additional user packages (comma separated), e.g. org.apache.flink:flink-connector-kafka2.11:1.10,org.apache.flink:flink-connector-kafka-base2.11:1.10.0,org.apache.flink:flink-json:1.10.0 zeppelin.flink.concurrentBatchSql.max 10 Max concurrent sql of Batch Sql (%flink.bsql) zeppelin.flink.concurrentStreamSql.max 10 Max concurrent sql of Stream Sql (%flink.ssql) zeppelin.pyflink.python python Python binary executable for PyFlink table.exec.resource.default-parallelism 1 Default parallelism for flink sql job zeppelin.flink.scala.color true Whether display scala shell output in colorful format zeppelin.flink.enableHive false Whether enable hive zeppelin.flink.hive.version 2.3.4 Hive version that you would like to connect zeppelin.flink.module.enableHive false Whether enable hive module, hive udf take precedence over flink udf if hive module is enabled. zeppelin.flink.maxResult 1000 max number of row returned by sql interpreter flink.interpreter.close.shutdown_cluster true Whether shutdown application when closing interpreter zeppelin.interpreter.close.cancel_job true Whether cancel flink job when closing interpreter zeppelin.flink.job.check_interval 1000 Check interval (in milliseconds) to check flink job progress StreamExecutionEnvironment, ExecutionEnvironment, StreamTableEnvironment, BatchTableEnvironmentZeppelin will create 6 variables as flink scala (%flink) entry point:senv (StreamExecutionEnvironment), benv (ExecutionEnvironment)stenv (StreamTableEnvironment for blink planner) btenv (BatchTableEnvironment for blink planne r)stenv_2 (StreamTableEnvironment for flink planner) btenv_2 (BatchTableEnvironment for flink planner)And will create 6 variables as pyflink (%flink.pyflink or %flink.ipyflink) entry point:s_env (StreamExecutionEnvironment), b_env (ExecutionEnvironment)st_env (StreamTableEnvironment for blink planner) bt_env (BatchTableEnvironment for blink planner)st_env_2 (StreamTableEnvironment for flink planner) bt_env_2 (BatchTableEnvironment for flink planner)Blink/Flink PlannerThere are 2 planners supported by Flink&#39;s table api: flink &amp; blink.If you want to use DataSet api, and convert it to flink table then please use flink planner (btenv_2 and stenv_2).In other cases, we would always recommend you to use blink planner. This is also what flink batch/streaming sql interpreter use (%flink.bsql &amp; %flink.ssql)Check this page for the difference between flink planner and blink planner.Execution mode (Local/Remote/Yarn/Yarn Application)Flink in Zeppelin su pports 4 execution modes (flink.execution.mode):LocalRemoteYarnYarn ApplicationRun Flink in Local ModeRunning Flink in Local mode will start a MiniCluster in local JVM. By default, the local MiniCluster will use port 8081, so make sure this port is available in your machine,otherwise you can configure rest.port to specify another port. You can also specify local.number-taskmanager and flink.tm.slot to customize the number of TM and number of slots per TM, because by default it is only 4 TM with 1 Slots which may not be enough for some cases.Run Flink in Remote ModeRunning Flink in remote mode will connect to an existing flink cluster which could be standalone cluster or yarn session cluster. Besides specifying flink.execution.mode to be remote. You also need to specifyflink.execution.remote.host and flink.execution.remote.port to point to flink job manager.Run Flink in Yarn ModeIn order to run flink in Yarn mode, you need to make the following settings:Set flink.execution.mode to ya rnSet HADOOP_CONF_DIR in flink&#39;s interpreter setting or zeppelin-env.sh.Make sure hadoop command is on your PATH. Because internally flink will call command hadoop classpath and load all the hadoop related jars in the flink interpreter processRun Flink in Yarn Application ModeIn the above yarn mode, there will be a separated flink interpreter process. This may run out of resources when there&#39;re many interpreter processes.So it is recommended to use yarn application mode if you are using flink 1.11 or afterwards (yarn application mode is only supported after flink 1.11). In this mode flink interpreter runs in the JobManager which is in yarn container.In order to run flink in yarn application mode, you need to make the following settings:Set flink.execution.mode to yarn-applicationSet HADOOP_CONF_DIR in flink&#39;s interpreter setting or zeppelin-env.sh.Make sure hadoop command is on your PATH. Because internally flink will call command hadoop classpath and load al l the hadoop related jars in the flink interpreter processHow to use HiveIn order to use Hive in Flink, you have to make the following setting.Set zeppelin.flink.enableHive to be trueSet zeppelin.flink.hive.version to be the hive version you are using.Set HIVE_CONF_DIR to be the location where hive-site.xml is located. Make sure hive metastore is started and you have configured hive.metastore.uris in hive-site.xmlCopy the following dependencies to the lib folder of flink installation. flink-connector-hive_2.11â1.10.0.jarflink-hadoop-compatibility_2.11â1.10.0.jarhive-exec-2.x.jar (for hive 1.x, you need to copy hive-exec-1.x.jar, hive-metastore-1.x.jar, libfb303â0.9.2.jar and libthrift-0.9.2.jar)Flink Batch SQL%flink.bsql is used for flink&#39;s batch sql. You can type help to get all the available commands. It supports all the flink sql, including DML/DDL/DQL.Use insert into statement for batch ETLUse select statement for batch data analytics Flink Streaming SQ L%flink.ssql is used for flink&#39;s streaming sql. You just type help to get all the available commands. It supports all the flink sql, including DML/DDL/DQL.Use insert into statement for streaming ETLUse select statement for streaming data analyticsStreaming Data VisualizationZeppelin supports 3 types of streaming data analytics:* Single* Update* Appendtype=singleSingle mode is for the case when the result of sql statement is always one row, such as the following example. The output format is HTML, and you can specify paragraph local property template for the final output content template. And you can use {i} as placeholder for the ith column of result. type=updateUpdate mode is suitable for the case when the output is more than one rows, and always will be updated continuously. Hereâs one example where we use group by. type=appendAppend mode is suitable for the scenario where output data is always appended. E.g. the following example which use tumble window. Fli nk UDFYou can use Flink scala UDF or Python UDF in sql. UDF for batch and streaming sql is the same. Here&#39;re 2 examples.Scala UDF%flinkclass ScalaUpper extends ScalarFunction { def eval(str: String) = str.toUpperCase}btenv.registerFunction(&quot;scala_upper&quot;, new ScalaUpper())Python UDF%flink.pyflinkclass PythonUpper(ScalarFunction): def eval(self, s): return s.upper()bt_env.register_function(&quot;python_upper&quot;, udf(PythonUpper(), DataTypes.STRING(), DataTypes.STRING()))Zeppelin only supports scala and python for flink interpreter, if you want to write a java udf or the udf is pretty complicated which make it not suitable to write in Zeppelin,then you can write the udf in IDE and build an udf jar.In Zeppelin you just need to specify flink.udf.jars to this jar, and flinkinterpreter will detect all the udfs in this jar and register all the udfs to TableEnvironment, the udf name is the class name.PyFlink(%flink.pyflink)In order to use PyFlink in Zeppelin, you just need to do the following configuration.* Install apache-flink (e.g. pip install apache-flink)* Set zeppelin.pyflink.python to the python executable where apache-flink is installed in case you have multiple python installed.* Copy flink-python_2.11â1.10.0.jar from flink opt folder to flink lib folderAnd PyFlink will create 6 variables for you:s_env (StreamExecutionEnvironment), b_env (ExecutionEnvironment)st_env (StreamTableEnvironment for blink planner) bt_env (BatchTableEnvironment for blink planner)st_env_2 (StreamTableEnvironment for flink planner) bt_env_2 (BatchTableEnvironment for flink planner)IPython Support(%flink.ipyflink)By default, zeppelin would use IPython in %flink.pyflink when IPython is available, Otherwise it would fall back to the original python implementation.For the IPython features, you can refer docPython InterpreterZeppelinContextZeppelin automatically injects ZeppelinContext as variable z in your Scala/Python environme nt. ZeppelinContext provides some additional functions and utilities.See Zeppelin-Context for more details. You can use z to display both flink DataSet and batch/stream table.Display DataSetDisplay Batch TableDisplay Stream TableParagraph local propertiesIn the section of Streaming Data Visualization, we demonstrate the different visualization type via paragraph local properties: type. In this section, we will list and explain all the supported local properties in flink interpreter. Property Default Description type Used in %flink.ssql to specify the streaming visualization type (single, update, append) refreshInterval 3000 Used in `%flink.ssql` to specify frontend refresh interval for streaming data visualization. template {0} Used in `%flink.ssql` to specify html template for `single` type of streaming data visualization, And you can use `{i}` as placeholder for the {i}th column of the result. parallelism Used in %fl ink.ssql & %flink.bsql to specify the flink sql job parallelism maxParallelism Used in %flink.ssql & %flink.bsql to specify the flink sql job max parallelism in case you want to change parallelism later. For more details, refer this [link](https://ci.apache.org/projects/flink/flink-docs-release-1.10/dev/parallel.html#setting-the-maximum-parallelism) savepointDir If you specify it, then when you cancel your flink job in Zeppelin, it would also do savepoint and store state in this directory. And when you resume your job, it would resume from this savepoint. execution.savepoint.path When you resume your job, it would resume from this savepoint path. resumeFromSavepoint Resume flink job from savepoint if you specify savepointDir. resumeFromLatestCheckpoint Resume flink job from latest checkpoint if you enable checkpoint. runAsOne false All the insert into sql will run in a single flink job if thi s is true. Tutorial NotesZeppelin is shipped with several Flink tutorial notes which may be helpful for you. You can check for more features in the tutorial notes.", "url": " /interpreter/flink.html", "group": "interpreter", "excerpt": "Apache Flink is an open source platform for distributed stream and batch data processing." @@ -467,7 +467,7 @@ "/development/writing_zeppelin_interpreter.html": { "title": "Writing a New Interpreter", - "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Writing a New InterpreterWhat is Apache Zeppelin InterpreterApache Zeppelin Interpreter is a language backend. For example to use scala code in Zeppelin, you need a scala interpreter.Every Interpreters belongs to an InterpreterGroup.Interpreters in the same InterpreterGroup can reference each other. For example, SparkSqlInterpreter can reference SparkInterpreter to get SparkContext from it while they&#39;re in the same group.In terpreterSetting is configuration of a given InterpreterGroup and a unit of start/stop interpreter.All Interpreters in the same InterpreterSetting are launched in a single, separate JVM process. The Interpreter communicates with Zeppelin engine via Thrift.In &#39;Separate Interpreter(scoped / isolated) for each note&#39; mode which you can see at the Interpreter Setting menu when you create a new interpreter, new interpreter instance will be created per note. But it still runs on the same JVM while they&#39;re in the same InterpreterSettings.Make your own InterpreterCreating a new interpreter is quite simple. Just extend org.apache.zeppelin.interpreter abstract class and implement some methods.For your interpreter project, you need to make interpreter-parent as your parent project and use plugin maven-enforcer-plugin, maven-dependency-plugin and maven-resources-plugin. Here&#39;s one sample pom.xml &lt;project xmlns=&quot;http://maven.apache.org/POM/4.0.0& ;quot; xmlns:xsi=&quot;http://www.w3.org/2001/XMLSchema-instance&quot; xsi:schemaLocation=&quot;http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd&quot;&gt; &lt;modelVersion&gt;4.0.0&lt;/modelVersion&gt; &lt;parent&gt; &lt;artifactId&gt;interpreter-parent&lt;/artifactId&gt; &lt;groupId&gt;org.apache.zeppelin&lt;/groupId&gt; &lt;version&gt;0.9.0-SNAPSHOT&lt;/version&gt; &lt;relativePath&gt;../interpreter-parent&lt;/relativePath&gt; &lt;/parent&gt; ... &lt;dependencies&gt; &lt;dependency&gt; &lt;groupId&gt;org.apache.zeppelin&lt;/groupId&gt; &lt;artifactId&gt;zeppelin-interpreter&lt;/artifactId&gt; &lt;version&gt;${project.version}&lt;/version&gt; &lt;scope&gt;provided&lt;/scope&a mp;gt; &lt;/dependency&gt; &lt;/dependencies&gt; &lt;build&gt; &lt;plugins&gt; &lt;plugin&gt; &lt;artifactId&gt;maven-enforcer-plugin&lt;/artifactId&gt; &lt;/plugin&gt; &lt;plugin&gt; &lt;artifactId&gt;maven-dependency-plugin&lt;/artifactId&gt; &lt;/plugin&gt; &lt;plugin&gt; &lt;artifactId&gt;maven-resources-plugin&lt;/artifactId&gt; &lt;/plugin&gt; &lt;/plugins&gt; &lt;/build&gt;&lt;/project&gt;You should include org.apache.zeppelin:zeppelin-interpreter:[VERSION] as your interpreter&#39;s dependency in pom.xml. BesAnd you should put your jars under your interpreter directory with a specific directory name. Zeppelin server reads interpreter directories recursively and initializes interpreter s including your own interpreter.There are three locations where you can store your interpreter group, name and other information. Zeppelin server tries to find the location below. Next, Zeppelin tries to find interpreter-setting.json in your interpreter jar.{ZEPPELIN_INTERPRETER_DIR}/{YOUR_OWN_INTERPRETER_DIR}/interpreter-setting.jsonHere is an example of interpreter-setting.json on your own interpreter.[ { &quot;group&quot;: &quot;your-group&quot;, &quot;name&quot;: &quot;your-name&quot;, &quot;className&quot;: &quot;your.own.interpreter.class&quot;, &quot;properties&quot;: { &quot;properties1&quot;: { &quot;envName&quot;: null, &quot;propertyName&quot;: &quot;property.1.name&quot;, &quot;defaultValue&quot;: &quot;propertyDefaultValue&quot;, &quot;description&quot;: &quot;Property description&quot;, &quot;t ype&quot;: &quot;textarea&quot; }, &quot;properties2&quot;: { &quot;envName&quot;: PROPERTIES_2, &quot;propertyName&quot;: null, &quot;defaultValue&quot;: &quot;property2DefaultValue&quot;, &quot;description&quot;: &quot;Property 2 description&quot;, &quot;type&quot;: &quot;textarea&quot; }, ... }, &quot;editor&quot;: { &quot;language&quot;: &quot;your-syntax-highlight-language&quot;, &quot;editOnDblClick&quot;: false, &quot;completionKey&quot;: &quot;TAB&quot; }, &quot;config&quot;: { &quot;runOnSelectionChange&quot;: true/false, &quot;title&quot;: true/false, &quot;checkEmpty&quot;: true/false } }, { ... }]Finally, Zeppelin uses static initialization with the following:static { Interpreter.register(&quot;MyInterpret erName&quot;, MyClassName.class.getName());}Static initialization is deprecated and will be supported until 0.6.0.The name will appear later in the interpreter name option box during the interpreter configuration process.The name of the interpreter is what you later write to identify a paragraph which should be interpreted using this interpreter.%MyInterpreterNamesome interpreter specific code...Editor setting for InterpreterYou can add editor object to interpreter-setting.json file to specify paragraph editor settings.LanguageIf the interpreter uses a specific programming language (like Scala, Python, SQL), it is generally recommended to add a syntax highlighting supported for that to the note paragraph editor.To check out the list of languages supported, see the mode-*.js files under zeppelin-web/bower_components/ace-builds/src-noconflict or from github.com/ajaxorg/ace-builds.If you want to add a new set of syntax highlighting, Add the mode-*.js file to zeppelin-web/bower.jso n (when built, zeppelin-web/src/index.html will be changed automatically).Add language field to editor object. Note that if you don&#39;t specify language field, your interpreter will use plain text mode for syntax highlighting. Let&#39;s say you want to set your language to java, then add:&quot;editor&quot;: { &quot;language&quot;: &quot;java&quot;}Edit on double clickIf your interpreter uses mark-up language such as markdown or HTML, set editOnDblClick to true so that text editor opens on pargraph double click and closes on paragraph run. Otherwise set it to false.&quot;editor&quot;: { &quot;editOnDblClick&quot;: false}Completion key (Optional)By default, Ctrl+dot(.) brings autocompletion list in the editor.Through completionKey, each interpreter can configure autocompletion key.Currently TAB is only available option.&quot;editor&quot;: { &quot;completionKey&quot;: &quot;TAB&quot;}Notebook paragraph display title (Optional)The notebook paragraph does not display the title by default.You can have the title of the notebook display the title by config.title=true.&quot;config&quot;: { &quot;title&quot;: true # default: false}Notebook run on selection change (Optional)The dynamic form in the notebook triggers execution when the selection is modified.You can make the dynamic form in the notebook not trigger execution after selecting the modification by setting config.runOnSelectionChange=false.&quot;config&quot;: { &quot;runOnSelectionChange&quot;: false # default: true}Check if the paragraph is empty before running (Optional)The notebook&#39;s paragraph default will not run if it is empty.You can set config.checkEmpty=false, to run even when the paragraph of the notebook is empty.&quot;config&quot;: { &quot;checkEmpty&quot;: false # default: true}Install your interpreter binaryOnce you have built your interpreter, you can place it und er the interpreter directory with all its dependencies.[ZEPPELIN_HOME]/interpreter/[INTERPRETER_NAME]/Configure your interpreterTo configure your interpreter you need to follow these steps:Start Zeppelin by running ./bin/zeppelin-daemon.sh start.In the interpreter page, click the +Create button and configure your interpreter properties.Now you are done and ready to use your interpreter.Note : Interpreters released with zeppelin have a default configuration which is used when there is no conf/zeppelin-site.xml.Use your interpreter0.5.0Inside of a note, %[INTERPRETER_NAME] directive will call your interpreter.Note that the first interpreter configuration in zeppelin.interpreters will be the default one.For example,%myintpval a = &quot;My interpreter&quot;println(a)0.6.0 and laterInside of a note, %[INTERPRETER_GROUP].[INTERPRETER_NAME] directive will call your interpreter.You can omit either [INTERPRETER_GROUP] or [INTERPRETER_NAME]. If you omit [INTERPRETER_NAME], then first available interpreter will be selected in the [INTERPRETER_GROUP].Likewise, if you skip [INTERPRETER_GROUP], then [INTERPRETER_NAME] will be chosen from default interpreter group.For example, if you have two interpreter myintp1 and myintp2 in group mygrp, you can call myintp1 like%mygrp.myintp1codes for myintp1and you can call myintp2 like%mygrp.myintp2codes for myintp2If you omit your interpreter name, it&#39;ll select first available interpreter in the group ( myintp1 ).%mygrpcodes for myintp1You can only omit your interpreter group when your interpreter group is selected as a default group.%myintp2codes for myintp2ExamplesCheckout some interpreters released with Zeppelin by default.sparkmarkdownshelljdbcContributing a new Interpreter to Zeppelin releasesWe welcome contribution to a new interpreter. Please follow these few steps:First, check out the general contribution guide here.Follow the steps in Make your own Interpreter section and Editor setting for Interpreter above.Ad d your interpreter as in the Configure your interpreter section above; also add it to the example template zeppelin-site.xml.template.Add tests! They are run by Travis for all changes and it is important that they are self-contained.Include your interpreter as a module in pom.xml.Add documentation on how to use your interpreter under docs/interpreter/. Follow the Markdown style as this example. Make sure you list config settings and provide working examples on using your interpreter in code boxes in Markdown. Link to images as appropriate (images should go to docs/assets/themes/zeppelin/img/docs-img/). And add a link to your documentation in the navigation menu (docs/_includes/themes/zeppelin/_navigation.html).Most importantly, ensure licenses of the transitive closure of all dependencies are list in license file.Commit your changes and open a Pull Request on the project Mirror on GitHub; check to make sure Travis CI build is passing.", + "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Writing a New InterpreterWhat is Apache Zeppelin InterpreterApache Zeppelin Interpreter is a language backend. For example to use scala code in Zeppelin, you need a scala interpreter.Every Interpreters belongs to an InterpreterGroup.Interpreters in the same InterpreterGroup can reference each other. For example, SparkSqlInterpreter can reference SparkInterpreter to get SparkContext from it while they&#39;re in the same group.In terpreterSetting is configuration of a given InterpreterGroup and a unit of start/stop interpreter.All Interpreters in the same InterpreterSetting are launched in a single, separate JVM process. The Interpreter communicates with Zeppelin engine via Thrift.In &#39;Separate Interpreter(scoped / isolated) for each note&#39; mode which you can see at the Interpreter Setting menu when you create a new interpreter, new interpreter instance will be created per note. But it still runs on the same JVM while they&#39;re in the same InterpreterSettings.Make your own InterpreterCreating a new interpreter is quite simple. Just extend org.apache.zeppelin.interpreter abstract class and implement some methods.For your interpreter project, you need to make interpreter-parent as your parent project and use plugin maven-enforcer-plugin, maven-dependency-plugin and maven-resources-plugin. Here&#39;s one sample pom.xml &lt;project xmlns=&quot;http://maven.apache.org/POM/4.0.0& ;quot; xmlns:xsi=&quot;http://www.w3.org/2001/XMLSchema-instance&quot; xsi:schemaLocation=&quot;http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd&quot;&gt; &lt;modelVersion&gt;4.0.0&lt;/modelVersion&gt; &lt;parent&gt; &lt;artifactId&gt;interpreter-parent&lt;/artifactId&gt; &lt;groupId&gt;org.apache.zeppelin&lt;/groupId&gt; &lt;version&gt;0.9.0-SNAPSHOT&lt;/version&gt; &lt;relativePath&gt;../interpreter-parent&lt;/relativePath&gt; &lt;/parent&gt; ... &lt;dependencies&gt; &lt;dependency&gt; &lt;groupId&gt;org.apache.zeppelin&lt;/groupId&gt; &lt;artifactId&gt;zeppelin-interpreter&lt;/artifactId&gt; &lt;version&gt;${project.version}&lt;/version&gt; &lt;scope&gt;provided&lt;/scope&a mp;gt; &lt;/dependency&gt; &lt;/dependencies&gt; &lt;build&gt; &lt;plugins&gt; &lt;plugin&gt; &lt;artifactId&gt;maven-enforcer-plugin&lt;/artifactId&gt; &lt;/plugin&gt; &lt;plugin&gt; &lt;artifactId&gt;maven-dependency-plugin&lt;/artifactId&gt; &lt;/plugin&gt; &lt;plugin&gt; &lt;artifactId&gt;maven-resources-plugin&lt;/artifactId&gt; &lt;/plugin&gt; &lt;/plugins&gt; &lt;/build&gt;&lt;/project&gt;You should include org.apache.zeppelin:zeppelin-interpreter:[VERSION] as your interpreter&#39;s dependency in pom.xml. BesAnd you should put your jars under your interpreter directory with a specific directory name. Zeppelin server reads interpreter directories recursively and initializes interpreter s including your own interpreter.There are three locations where you can store your interpreter group, name and other information. Zeppelin server tries to find the location below. Next, Zeppelin tries to find interpreter-setting.json in your interpreter jar.{ZEPPELIN_INTERPRETER_DIR}/{YOUR_OWN_INTERPRETER_DIR}/interpreter-setting.jsonHere is an example of interpreter-setting.json on your own interpreter.[ { &quot;group&quot;: &quot;your-group&quot;, &quot;name&quot;: &quot;your-name&quot;, &quot;className&quot;: &quot;your.own.interpreter.class&quot;, &quot;properties&quot;: { &quot;properties1&quot;: { &quot;envName&quot;: null, &quot;propertyName&quot;: &quot;property.1.name&quot;, &quot;defaultValue&quot;: &quot;propertyDefaultValue&quot;, &quot;description&quot;: &quot;Property description&quot;, &quot;t ype&quot;: &quot;textarea&quot; }, &quot;properties2&quot;: { &quot;envName&quot;: PROPERTIES_2, &quot;propertyName&quot;: null, &quot;defaultValue&quot;: &quot;property2DefaultValue&quot;, &quot;description&quot;: &quot;Property 2 description&quot;, &quot;type&quot;: &quot;textarea&quot; }, ... }, &quot;editor&quot;: { &quot;language&quot;: &quot;your-syntax-highlight-language&quot;, &quot;editOnDblClick&quot;: false, &quot;completionKey&quot;: &quot;TAB&quot; }, &quot;config&quot;: { &quot;runOnSelectionChange&quot;: true/false, &quot;title&quot;: true/false, &quot;checkEmpty&quot;: true/false } }, { ... }]Finally, Zeppelin uses static initialization with the following:static { Interpreter.register(&quot;MyInterpret erName&quot;, MyClassName.class.getName());}Static initialization is deprecated and will be supported until 0.6.0.The name will appear later in the interpreter name option box during the interpreter configuration process.The name of the interpreter is what you later write to identify a paragraph which should be interpreted using this interpreter.%MyInterpreterNamesome interpreter specific code...Editor setting for InterpreterYou can add editor object to interpreter-setting.json file to specify paragraph editor settings.LanguageIf the interpreter uses a specific programming language (like Scala, Python, SQL), it is generally recommended to add a syntax highlighting supported for that to the note paragraph editor.To check out the list of languages supported, see the mode-*.js files under zeppelin-web/bower_components/ace-builds/src-noconflict or from github.com/ajaxorg/ace-builds.If you want to add a new set of syntax highlighting, Add the mode-*.js file to zeppelin-web/bower.jso n (when built, zeppelin-web/src/index.html will be changed automatically).Add language field to editor object. Note that if you don&#39;t specify language field, your interpreter will use plain text mode for syntax highlighting. Let&#39;s say you want to set your language to java, then add:&quot;editor&quot;: { &quot;language&quot;: &quot;java&quot;}Edit on double clickIf your interpreter uses mark-up language such as markdown or HTML, set editOnDblClick to true so that text editor opens on pargraph double click and closes on paragraph run. Otherwise set it to false.&quot;editor&quot;: { &quot;editOnDblClick&quot;: false}Completion key (Optional)By default, Ctrl+dot(.) brings autocompletion list in the editor.Through completionKey, each interpreter can configure autocompletion key.Currently TAB is only available option.&quot;editor&quot;: { &quot;completionKey&quot;: &quot;TAB&quot;}Notebook paragraph display title (Optional)The notebook paragraph does not display the title by default.You can have the title of the notebook display the title by config.title=true.&quot;config&quot;: { &quot;title&quot;: true # default: false}Notebook run on selection change (Optional)The dynamic form in the notebook triggers execution when the selection is modified.You can make the dynamic form in the notebook not trigger execution after selecting the modification by setting config.runOnSelectionChange=false.&quot;config&quot;: { &quot;runOnSelectionChange&quot;: false # default: true}Check if the paragraph is empty before running (Optional)The notebook&#39;s paragraph default will not run if it is empty.You can set config.checkEmpty=false, to run even when the paragraph of the notebook is empty.&quot;config&quot;: { &quot;checkEmpty&quot;: false # default: true}Install your interpreter binaryOnce you have built your interpreter, you can place it und er the interpreter directory with all its dependencies.[ZEPPELIN_HOME]/interpreter/[INTERPRETER_NAME]/Configure your interpreterTo configure your interpreter you need to follow these steps:Start Zeppelin by running ./bin/zeppelin-daemon.sh start.In the interpreter page, click the +Create button and configure your interpreter properties.Now you are done and ready to use your interpreter.Note : Interpreters released with zeppelin have a default configuration which is used when there is no conf/zeppelin-site.xml.Use your interpreter0.5.0Inside of a note, %[INTERPRETER_NAME] directive will call your interpreter.Note that the first interpreter configuration in zeppelin.interpreters will be the default one.For example,%myintpval a = &quot;My interpreter&quot;println(a)0.6.0 and laterInside of a note, %[INTERPRETER_GROUP].[INTERPRETER_NAME] directive will call your interpreter.You can omit either [INTERPRETER_GROUP] or [INTERPRETER_NAME]. If you omit [INTERPRETER_NAME], then first available interpreter will be selected in the [INTERPRETER_GROUP].Likewise, if you skip [INTERPRETER_GROUP], then [INTERPRETER_NAME] will be chosen from default interpreter group.For example, if you have two interpreter myintp1 and myintp2 in group mygrp, you can call myintp1 like%mygrp.myintp1codes for myintp1and you can call myintp2 like%mygrp.myintp2codes for myintp2If you omit your interpreter name, it&#39;ll select first available interpreter in the group ( myintp1 ).%mygrpcodes for myintp1You can only omit your interpreter group when your interpreter group is selected as a default group.%myintp2codes for myintp2ExamplesCheckout some interpreters released with Zeppelin by default.sparkmarkdownshelljdbcContributing a new Interpreter to Zeppelin releasesWe welcome contribution to a new interpreter. Please follow these few steps:First, check out the general contribution guide here.Follow the steps in Make your own Interpreter section and Editor setting for Interpreter above.Ad d your interpreter as in the Configure your interpreter section above; also add it to the example template zeppelin-site.xml.template.Add tests! They are run for all changes and it is important that they are self-contained.Include your interpreter as a module in pom.xml.Add documentation on how to use your interpreter under docs/interpreter/. Follow the Markdown style as this example. Make sure you list config settings and provide working examples on using your interpreter in code boxes in Markdown. Link to images as appropriate (images should go to docs/assets/themes/zeppelin/img/docs-img/). And add a link to your documentation in the navigation menu (docs/_includes/themes/zeppelin/_navigation.html).Most importantly, ensure licenses of the transitive closure of all dependencies are list in license file.Commit your changes and open a Pull Request on the project Mirror on GitHub; check to make sure Travis CI build is passing.", "url": " /development/writing_zeppelin_interpreter.html", "group": "development", "excerpt": "Apache Zeppelin Interpreter is a language backend. Every Interpreters belongs to an InterpreterGroup. Interpreters in the same InterpreterGroup can reference each other." @@ -489,7 +489,7 @@ "/development/contribution/how_to_contribute_code.html": { "title": "Contributing to Apache Zeppelin (Code)", - "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Contributing to Apache Zeppelin ( Code )NOTE : Apache Zeppelin is an Apache2 License Software.Any contributions to Zeppelin (Source code, Documents, Image, Website) means you agree with license all your contributions as Apache2 License.Setting upHere are some tools you will need to build and test Zeppelin.Software Configuration Management ( SCM )Since Zeppelin uses Git for it&#39;s SCM system, you need git client installed in y our development machine.Integrated Development Environment ( IDE )You are free to use whatever IDE you prefer, or your favorite command line editor.Build ToolsTo build the code, installOracle Java 8Apache MavenGetting the source codeFirst of all, you need Zeppelin source code. The official location of Zeppelin is https://gitbox.apache.org/repos/asf/zeppelin.git.git accessGet the source code on your development machine using git.git clone git://gitbox.apache.org/repos/asf/zeppelin.git zeppelinYou may also want to develop against a specific branch. For example, for branch-0.5.6git clone -b branch-0.5.6 git://gitbox.apache.org/repos/asf/zeppelin.git zeppelinApache Zeppelin follows Fork &amp; Pull as a source control workflow.If you want to not only build Zeppelin but also make any changes, then you need to fork Zeppelin github mirror repository and make a pull request.Before making a pull request, please take a look Contribution Guidelines.Buildmvn installTo skip testmvn install -D skipTestsTo build with specific spark / hadoop versionmvn install -Dspark.version=x.x.x -Dhadoop.version=x.x.xFor the further Run Zeppelin server in development modeOption 1 - Command LineCopy the conf/zeppelin-site.xml.template to zeppelin-server/src/main/resources/zeppelin-site.xml and change the configurations in this file if requiredRun the following commandcd zeppelin-serverHADOOP_HOME=YOUR_HADOOP_HOME JAVA_HOME=YOUR_JAVA_HOME mvn exec:java -Dexec.mainClass=&quot;org.apache.zeppelin.server.ZeppelinServer&quot; -Dexec.args=&quot;&quot;Option 2 - Daemon ScriptNote: Make sure you first run mvn clean install -DskipTestsin your zeppelin root directory, otherwise your server build will fail to find the required dependencies in the local repro.or use daemon scriptbin/zeppelin-daemon startServer will be run on http://localhost:8080.Option 3 - IDECopy the conf/zeppelin-site.xml.template to zeppelin-server/src/main/resources/zeppelin-site.xml and change the configurations in this file if requiredZeppelinServer.java Main classGenerating Thrift CodeSome portions of the Zeppelin code are generated by Thrift. For most Zeppelin changes, you don&#39;t need to worry about this. But if you modify any of the Thrift IDL files (e.g. zeppelin-interpreter/src/main/thrift/*.thrift), then you also need to regenerate these files and submit their updated version as part of your patch.To regenerate the code, install thrift-0.9.2 and then run the following command to generate thrift code.cd &lt;zeppelin_home&gt;/zeppelin-interpreter/src/main/thrift./genthrift.shRun Selenium testZeppelin has set of integration tests using Selenium. To run these test, first build and run Zeppelin and make sure Zeppelin is running on port 8080. Then you can run test using following commandTEST_SELENIUM=true mvn test -Dtest=[TEST_NAME] -DfailIfNoTests=false -pl &#39;zeppelin-interpreter,zeppelin-zengine,zeppelin-server&#39;For example, to run ParagraphActionIT,TEST_SEL ENIUM=true mvn test -Dtest=ParagraphActionsIT -DfailIfNoTests=false -pl &#39;zeppelin-interpreter,zeppelin-zengine,zeppelin-server&#39;You&#39;ll need Firefox web browser installed in your development environment. While CI server uses Firefox 31.0 to run selenium test, it is good idea to install the same version (disable auto update to keep the version).Where to StartYou can find issues for beginner &amp; newbieStay involvedContributors should join the Zeppelin mailing lists....@zeppelin.apache.org is for people who want to contribute code to Zeppelin. subscribe, unsubscribe, archivesIf you have any issues, create a ticket in JIRA.", + "content" : "<!--Licensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.-->Contributing to Apache Zeppelin ( Code )NOTE : Apache Zeppelin is an Apache2 License Software.Any contributions to Zeppelin (Source code, Documents, Image, Website) means you agree with license all your contributions as Apache2 License.Setting upHere are some tools you will need to build and test Zeppelin.Software Configuration Management ( SCM )Since Zeppelin uses Git for it&#39;s SCM system, you need git client installed in y our development machine.Integrated Development Environment ( IDE )You are free to use whatever IDE you prefer, or your favorite command line editor.Build ToolsTo build the code, installOracle Java 8Apache MavenGetting the source codeFirst of all, you need Zeppelin source code. The official location of Zeppelin is https://gitbox.apache.org/repos/asf/zeppelin.git.git accessGet the source code on your development machine using git.git clone git://gitbox.apache.org/repos/asf/zeppelin.git zeppelinYou may also want to develop against a specific branch. For example, for branch-0.5.6git clone -b branch-0.5.6 git://gitbox.apache.org/repos/asf/zeppelin.git zeppelinApache Zeppelin follows Fork &amp; Pull as a source control workflow.If you want to not only build Zeppelin but also make any changes, then you need to fork Zeppelin github mirror repository and make a pull request.Before making a pull request, please take a look Contribution Guidelines.Buildmvn installTo skip testmvn install -D skipTestsTo build with specific spark / hadoop versionmvn install -Dspark.version=x.x.x -Dhadoop.version=x.x.xFor the further Run Zeppelin server in development modeOption 1 - Command LineCopy the conf/zeppelin-site.xml.template to zeppelin-server/src/main/resources/zeppelin-site.xml and change the configurations in this file if requiredRun the following commandcd zeppelin-serverHADOOP_HOME=YOUR_HADOOP_HOME JAVA_HOME=YOUR_JAVA_HOME mvn exec:java -Dexec.mainClass=&quot;org.apache.zeppelin.server.ZeppelinServer&quot; -Dexec.args=&quot;&quot;Option 2 - Daemon ScriptNote: Make sure you first run mvn clean install -DskipTestsin your zeppelin root directory, otherwise your server build will fail to find the required dependencies in the local repro.or use daemon scriptbin/zeppelin-daemon startServer will be run on http://localhost:8080.Option 3 - IDECopy the conf/zeppelin-site.xml.template to zeppelin-server/src/main/resources/zeppelin-site.xml and change the configurations in this file if requiredZeppelinServer.java Main classGenerating Thrift CodeSome portions of the Zeppelin code are generated by Thrift. For most Zeppelin changes, you don&#39;t need to worry about this. But if you modify any of the Thrift IDL files (e.g. zeppelin-interpreter/src/main/thrift/*.thrift), then you also need to regenerate these files and submit their updated version as part of your patch.To regenerate the code, install thrift-0.9.2 and then run the following command to generate thrift code.cd &lt;zeppelin_home&gt;/zeppelin-interpreter/src/main/thrift./genthrift.shRun Selenium testZeppelin has set of integration tests using Selenium. To run these test, first build and run Zeppelin and make sure Zeppelin is running on port 8080. Then you can run test using following commandTEST_SELENIUM=true mvn test -Dtest=[TEST_NAME] -DfailIfNoTests=false -pl &#39;zeppelin-interpreter,zeppelin-zengine,zeppelin-server&#39;For example, to run ParagraphActionIT,TEST_SEL ENIUM=true mvn test -Dtest=ParagraphActionsIT -DfailIfNoTests=false -pl &#39;zeppelin-interpreter,zeppelin-zengine,zeppelin-server&#39;You&#39;ll need Firefox web browser installed in your development environment.Where to StartYou can find issues for beginner &amp; newbieStay involvedContributors should join the Zeppelin mailing lists....@zeppelin.apache.org is for people who want to contribute code to Zeppelin. subscribe, unsubscribe, archivesIf you have any issues, create a ticket in JIRA.", "url": " /development/contribution/how_to_contribute_code.html", "group": "development/contribution", "excerpt": "How can you contribute to Apache Zeppelin project? This document covers from setting up your develop environment to making a pull request on Github." @@ -534,7 +534,7 @@ "/setup/operation/configuration.html": { "title": "Apache Zeppelin Configuration",
[... 197 lines stripped ...] Modified: zeppelin/site/docs/0.9.0/setup/basics/hadoop_integration.html URL: http://svn.apache.org/viewvc/zeppelin/site/docs/0.9.0/setup/basics/hadoop_integration.html?rev=1890433&r1=1890432&r2=1890433&view=diff ============================================================================== --- zeppelin/site/docs/0.9.0/setup/basics/hadoop_integration.html (original) +++ zeppelin/site/docs/0.9.0/setup/basics/hadoop_integration.html Thu Jun 3 15:43:41 2021 @@ -125,6 +125,9 @@ <li><a href="/docs/0.9.0/usage/rest_api/configuration.html">Configuration API</a></li> <li><a href="/docs/0.9.0/usage/rest_api/credential.html">Credential API</a></li> <li><a href="/docs/0.9.0/usage/rest_api/helium.html">Helium API</a></li> + <li class="title"><span>Zeppelin SDK</span></li> + <li><a href="/docs/0.9.0/usage/zeppelin_sdk/client_api.html">Client API</a></li> + <li><a href="/docs/0.9.0/usage/zeppelin_sdk/session_api.html">Session API</a></li> </ul> </li> @@ -192,17 +195,21 @@ <li><a href="/docs/0.9.0/interpreter/hdfs.html">HDFS</a></li> <li><a href="/docs/0.9.0/interpreter/hive.html">Hive</a></li> <li><a href="/docs/0.9.0/interpreter/ignite.html">Ignite</a></li> + <li><a href="/docs/0.9.0/interpreter/influxdb.html">influxDB</a></li> <li><a href="/docs/0.9.0/interpreter/java.html">Java</a></li> <li><a href="/docs/0.9.0/interpreter/jupyter.html">Jupyter</a></li> <li><a href="/docs/0.9.0/interpreter/kotlin.html">Kotlin</a></li> + <li><a href="/docs/0.9.0/interpreter/ksql.html">KSQL</a></li> <li><a href="/docs/0.9.0/interpreter/kylin.html">Kylin</a></li> <li><a href="/docs/0.9.0/interpreter/lens.html">Lens</a></li> <li><a href="/docs/0.9.0/interpreter/livy.html">Livy</a></li> + <li><a href="/docs/0.9.0/interpreter/mahout.html">Mahout</a></li> <li><a href="/docs/0.9.0/interpreter/markdown.html">Markdown</a></li> <li><a href="/docs/0.9.0/interpreter/mongodb.html">MongoDB</a></li> <li><a href="/docs/0.9.0/interpreter/neo4j.html">Neo4j</a></li> <li><a href="/docs/0.9.0/interpreter/pig.html">Pig</a></li> <li><a href="/docs/0.9.0/interpreter/postgresql.html">Postgresql, HAWQ</a></li> + <li><a href="/docs/0.9.0/interpreter/sap.html">SAP</a></li> <li><a href="/docs/0.9.0/interpreter/scalding.html">Scalding</a></li> <li><a href="/docs/0.9.0/interpreter/scio.html">Scio</a></li> <li><a href="/docs/0.9.0/interpreter/shell.html">Shell</a></li> @@ -285,7 +292,7 @@ limitations under the License. <h2>Requirements</h2> -<p>In Zeppelin 0.9 doesn't ship with hadoop dependencies, you need to include hadoop jars by yourself via the following steps</p> +<p>Zeppelin 0.9 doesn't ship with hadoop dependencies, you need to include hadoop jars by yourself via the following steps</p> <ul> <li>Hadoop client (both 2.x and 3.x are supported) is installed.</li> @@ -299,7 +306,7 @@ limitations under the License. <hr> <footer> - <!-- <p>© 2020 The Apache Software Foundation</p>--> + <!-- <p>© 2021 The Apache Software Foundation</p>--> </footer> </div>
