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2013-06-06T13:08:17.210
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Pig and Hive are both use <a href="http://www.antlr.org/" rel="nofollow">ANTLR</a> to build a compiler to parse their scripts. If you are not familar with the compiler theory, I suggest you read some related material. For Pig, the source codes for ANLTR are <code>src/org/apache/pig/parser/QueryLexer.g</code> and <code>src/org/apache/pig/parser/QueryParser.g</code>. They will be compiled to <code>org.apache.pig.parser.QueryLexer</code> and <code>org.apache.pig.parser.QueryParser</code>. However, these two classes are used to compile your Pig script to an abstract syntax tree. Then it will be transformed to <code>org.apache.pig.newplan.logical.relational.LogicalPlan</code>. After that, LogcialPlan will be transformed to <code>org.apache.pig.backend.hadoop.executionengine.physicalLayer.plans.PhysicalPlan</code>. Here I listed some related source files: <pre><code>org.apache.pig.newplan.logical.relational.LogicalPlan org.apache.pig.backend.hadoop.executionengine.physicalLayer.plans.PhysicalPlan org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.plans.MROperPlan org.apache.pig.parser.QueryParserDriver.parse(String) org.apache.pig.backend.hadoop.executionengine.HExecutionEngine.compile(LogicalPlan, Properties) org.apache.pig.PigServer.launchPlan(PhysicalPlan, String) org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher.compile(PhysicalPlan, PigContext) org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler.getJob(MROperPlan, MapReduceOper, Configuration, PigContext) org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.JobControlCompiler.compile(MROperPlan, String) org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.MapReduceLauncher.launchPig(PhysicalPlan, String, PigContext) org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperators.POLocalRearrange.constructLROutput(List<Result>, List<Result>, Tuple) org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigGenericMapReduce.Map.collect(Context, Tuple) </code></pre> For Hive, the source code for ANLTR is <code>ql/src/java/org/apache/hadoop/hive/ql/parse/Hive.g</code>. It will be compiled to <code>org.apache.hadoop.hive.ql.parse.HiveLexer</code> and <code>org.apache.hadoop.hive.ql.parse.HiveParser</code>. These two classes are used to compile your Hive script to an abstract syntax tree. Then it will be transformed to <code>org.apache.hadoop.hive.ql.QueryPlan</code>. The mapper and reducer in Hive are ExecMapper and ExecReducer. Here I listed some related source files: <pre><code>org.apache.hadoop.hive.cli.CliDriver org.apache.hadoop.hive.ql.Driver org.apache.hadoop.hive.ql.Driver.run(String) org.apache.hadoop.hive.ql.parse.ParseDriver.parse(String, Context) org.apache.hadoop.hive.ql.parse.ParseDriver.parse(String, Context) org.apache.hadoop.hive.ql.parse.ASTNode org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer org.apache.hadoop.hive.ql.QueryPlan org.apache.hadoop.hive.ql.Driver.compile(String, boolean) org.apache.hadoop.hive.ql.exec.TaskRunner org.apache.hadoop.hive.ql.Driver.execute() org.apache.hadoop.hive.ql.exec.ExecDriver org.apache.hadoop.hive.ql.exec.ExecMapper org.apache.hadoop.hive.ql.exec.ExecReducer org.apache.hadoop.hive.ql.exec.MapOperator </code></pre> At last, I suggest you download their source codes and browse them in the eclipse to find out any question you want to know by yourself.
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Querying!

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A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.