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| <div class="section" id="module-airflow.contrib.operators.spark_jdbc_operator"> |
| <span id="airflow-contrib-operators-spark-jdbc-operator"></span><h1><a class="reference internal" href="#module-airflow.contrib.operators.spark_jdbc_operator" title="airflow.contrib.operators.spark_jdbc_operator"><code class="xref py py-mod docutils literal notranslate"><span class="pre">airflow.contrib.operators.spark_jdbc_operator</span></code></a><a class="headerlink" href="#module-airflow.contrib.operators.spark_jdbc_operator" title="Permalink to this headline">¶</a></h1> |
| <div class="section" id="module-contents"> |
| <h2>Module Contents<a class="headerlink" href="#module-contents" title="Permalink to this headline">¶</a></h2> |
| <dl class="class"> |
| <dt id="airflow.contrib.operators.spark_jdbc_operator.SparkJDBCOperator"> |
| <em class="property">class </em><code class="sig-prename descclassname">airflow.contrib.operators.spark_jdbc_operator.</code><code class="sig-name descname">SparkJDBCOperator</code><span class="sig-paren">(</span><em class="sig-param">spark_app_name='airflow-spark-jdbc'</em>, <em class="sig-param">spark_conn_id='spark-default'</em>, <em class="sig-param">spark_conf=None</em>, <em class="sig-param">spark_py_files=None</em>, <em class="sig-param">spark_files=None</em>, <em class="sig-param">spark_jars=None</em>, <em class="sig-param">num_executors=None</em>, <em class="sig-param">executor_cores=None</em>, <em class="sig-param">executor_memory=None</em>, <em class="sig-param">driver_memory=None</em>, <em class="sig-param">verbose=False</em>, <em class="sig-param">keytab=None</em>, <em class="sig-param">principal=None</em>, <em class="sig-param">cmd_type='spark_to_jdbc'</em>, <em class="sig-param">jdbc_table=None</em>, <em class="sig-param">jdbc_conn_id='jdbc-default'</em>, <em class="sig-param">jdbc_driver=None</em>, <em class="sig-param">metastore_table=None</em>, <em class="sig-param">jdbc_truncate=False</em>, <em class="sig-param">save_mode=None</em>, <em class="sig-param">save_format=None</em>, <em class="sig-param">batch_size=None</em>, <em class="sig-param">fetch_size=None</em>, <em class="sig-param">num_partitions=None</em>, <em class="sig-param">partition_column=None</em>, <em class="sig-param">lower_bound=None</em>, <em class="sig-param">upper_bound=None</em>, <em class="sig-param">create_table_column_types=None</em>, <em class="sig-param">*args</em>, <em class="sig-param">**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../_modules/airflow/contrib/operators/spark_jdbc_operator.html#SparkJDBCOperator"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#airflow.contrib.operators.spark_jdbc_operator.SparkJDBCOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="../spark_submit_operator/index.html#airflow.contrib.operators.spark_submit_operator.SparkSubmitOperator" title="airflow.contrib.operators.spark_submit_operator.SparkSubmitOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">airflow.contrib.operators.spark_submit_operator.SparkSubmitOperator</span></code></a></p> |
| <p>This operator extends the SparkSubmitOperator specifically for performing data |
| transfers to/from JDBC-based databases with Apache Spark. As with the |
| SparkSubmitOperator, it assumes that the “spark-submit” binary is available on the |
| PATH.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>spark_app_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Name of the job (default airflow-spark-jdbc)</p></li> |
| <li><p><strong>spark_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Connection id as configured in Airflow administration</p></li> |
| <li><p><strong>spark_conf</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.7)"><em>dict</em></a>) – Any additional Spark configuration properties</p></li> |
| <li><p><strong>spark_py_files</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Additional python files used (.zip, .egg, or .py)</p></li> |
| <li><p><strong>spark_files</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Additional files to upload to the container running the job</p></li> |
| <li><p><strong>spark_jars</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Additional jars to upload and add to the driver and |
| executor classpath</p></li> |
| <li><p><strong>num_executors</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – number of executor to run. This should be set so as to manage |
| the number of connections made with the JDBC database</p></li> |
| <li><p><strong>executor_cores</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – Number of cores per executor</p></li> |
| <li><p><strong>executor_memory</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Memory per executor (e.g. 1000M, 2G)</p></li> |
| <li><p><strong>driver_memory</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Memory allocated to the driver (e.g. 1000M, 2G)</p></li> |
| <li><p><strong>verbose</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.7)"><em>bool</em></a>) – Whether to pass the verbose flag to spark-submit for debugging</p></li> |
| <li><p><strong>keytab</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Full path to the file that contains the keytab</p></li> |
| <li><p><strong>principal</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – The name of the kerberos principal used for keytab</p></li> |
| <li><p><strong>cmd_type</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Which way the data should flow. 2 possible values: |
| spark_to_jdbc: data written by spark from metastore to jdbc |
| jdbc_to_spark: data written by spark from jdbc to metastore</p></li> |
| <li><p><strong>jdbc_table</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – The name of the JDBC table</p></li> |
| <li><p><strong>jdbc_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Connection id used for connection to JDBC database</p></li> |
| <li><p><strong>jdbc_driver</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – Name of the JDBC driver to use for the JDBC connection. This |
| driver (usually a jar) should be passed in the ‘jars’ parameter</p></li> |
| <li><p><strong>metastore_table</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – The name of the metastore table,</p></li> |
| <li><p><strong>jdbc_truncate</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.7)"><em>bool</em></a>) – (spark_to_jdbc only) Whether or not Spark should truncate or |
| drop and recreate the JDBC table. This only takes effect if |
| ‘save_mode’ is set to Overwrite. Also, if the schema is |
| different, Spark cannot truncate, and will drop and recreate</p></li> |
| <li><p><strong>save_mode</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – The Spark save-mode to use (e.g. overwrite, append, etc.)</p></li> |
| <li><p><strong>save_format</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – (jdbc_to_spark-only) The Spark save-format to use (e.g. parquet)</p></li> |
| <li><p><strong>batch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – (spark_to_jdbc only) The size of the batch to insert per round |
| trip to the JDBC database. Defaults to 1000</p></li> |
| <li><p><strong>fetch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – (jdbc_to_spark only) The size of the batch to fetch per round trip |
| from the JDBC database. Default depends on the JDBC driver</p></li> |
| <li><p><strong>num_partitions</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – The maximum number of partitions that can be used by Spark |
| simultaneously, both for spark_to_jdbc and jdbc_to_spark |
| operations. This will also cap the number of JDBC connections |
| that can be opened</p></li> |
| <li><p><strong>partition_column</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.7)"><em>str</em></a>) – (jdbc_to_spark-only) A numeric column to be used to |
| partition the metastore table by. If specified, you must |
| also specify: |
| num_partitions, lower_bound, upper_bound</p></li> |
| <li><p><strong>lower_bound</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – (jdbc_to_spark-only) Lower bound of the range of the numeric |
| partition column to fetch. If specified, you must also specify: |
| num_partitions, partition_column, upper_bound</p></li> |
| <li><p><strong>upper_bound</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.7)"><em>int</em></a>) – (jdbc_to_spark-only) Upper bound of the range of the numeric |
| partition column to fetch. If specified, you must also specify: |
| num_partitions, partition_column, lower_bound</p></li> |
| <li><p><strong>create_table_column_types</strong> – (spark_to_jdbc-only) The database column data types |
| to use instead of the defaults, when creating the |
| table. Data type information should be specified in |
| the same format as CREATE TABLE columns syntax |
| (e.g: “name CHAR(64), comments VARCHAR(1024)”). |
| The specified types should be valid spark sql data |
| types.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <dl class="method"> |
| <dt id="airflow.contrib.operators.spark_jdbc_operator.SparkJDBCOperator.execute"> |
| <code class="sig-name descname">execute</code><span class="sig-paren">(</span><em class="sig-param">self</em>, <em class="sig-param">context</em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../_modules/airflow/contrib/operators/spark_jdbc_operator.html#SparkJDBCOperator.execute"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#airflow.contrib.operators.spark_jdbc_operator.SparkJDBCOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Call the SparkSubmitHook to run the provided spark job</p> |
| </dd></dl> |
| |
| <dl class="method"> |
| <dt id="airflow.contrib.operators.spark_jdbc_operator.SparkJDBCOperator.on_kill"> |
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