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Posted to commits@hawq.apache.org by yo...@apache.org on 2017/01/06 17:32:59 UTC

[44/51] [partial] incubator-hawq-docs git commit: HAWQ-1254 Fix/remove book branching on incubator-hawq-docs

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-external-tables.html.md.erb
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----
-title: Accessing File-Based External Tables
----
-
-External tables enable accessing external files as if they are regular database tables. They are often used to move data into and out of a HAWQ database.
-
-To create an external table definition, you specify the format of your input files and the location of your external data sources. For information input file formats, see [Formatting Data Files](g-formatting-data-files.html#topic95).
-
-Use one of the following protocols to access external table data sources. You cannot mix protocols in `CREATE EXTERNAL TABLE` statements:
-
--   `gpfdist://` points to a directory on the file host and serves external data files to all HAWQ segments in parallel. See [gpfdist Protocol](g-gpfdist-protocol.html#topic_sny_yph_kr).
--   `gpfdists://` is the secure version of `gpfdist`. See [gpfdists Protocol](g-gpfdists-protocol.html#topic_sny_yph_kr).
--   `pxf://` specifies data accessed through the HAWQ Extensions Framework (PXF). PXF is a service that uses plug-in Java classes to read and write data in external data sources. PXF includes plug-ins to access data in HDFS, HBase, and Hive. Custom plug-ins can be written to access other external data sources.
-
-External tables allow you to access external files from within the database as if they are regular database tables. Used with `gpfdist`, the HAWQ parallel file distribution program, or HAWQ Extensions Framework (PXF), external tables provide full parallelism by using the resources of all HAWQ segments to load or unload data.
-
-You can query external table data directly and in parallel using SQL commands such as `SELECT`, `JOIN`, or `SORT EXTERNAL TABLE             DATA`, and you can create views for external tables.
-
-The steps for using external tables are:
-
-1.  Define the external table.
-2.  Start the gpfdist file server(s) if you plan to use the `gpfdist` or `gpdists` protocols.
-3.  Place the data files in the correct locations.
-4.  Query the external table with SQL commands.
-
-HAWQ provides readable and writable external tables:
-
--   Readable external tables for data loading. Readable external tables support basic extraction, transformation, and loading (ETL) tasks common in data warehousing. HAWQ segment instances read external table data in parallel to optimize large load operations. You cannot modify readable external tables.
--   Writable external tables for data unloading. Writable external tables support:
-
-    -   Selecting data from database tables to insert into the writable external table.
-    -   Sending data to an application as a stream of data. For example, unload data from HAWQ and send it to an application that connects to another database or ETL tool to load the data elsewhere.
-    -   Receiving output from HAWQ parallel MapReduce calculations.
-
-    Writable external tables allow only `INSERT` operations.
-
-External tables can be file-based or web-based.
-
--   Regular (file-based) external tables access static flat files. Regular external tables are rescannable: the data is static while the query runs.
--   Web (web-based) external tables access dynamic data sources, either on a web server with the `http://` protocol or by executing OS commands or scripts. Web external tables are not rescannable: the data can change while the query runs.
-
-Dump and restore operate only on external and web external table *definitions*, not on the data sources.
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-formatting-columns.html.md.erb
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----
-title: Formatting Columns
----
-
-The default column or field delimiter is the horizontal `TAB` character (`0x09`) for text files and the comma character (`0x2C`) for CSV files. You can declare a single character delimiter using the `DELIMITER` clause of `COPY`, `CREATE                 EXTERNAL TABLE` or the `hawq load` configuration table when you define your data format. The delimiter character must appear between any two data value fields. Do not place a delimiter at the beginning or end of a row. For example, if the pipe character ( | ) is your delimiter:
-
-``` pre
-data value 1|data value 2|data value 3
-```
-
-The following command shows the use of the pipe character as a column delimiter:
-
-``` sql
-=# CREATE EXTERNAL TABLE ext_table (name text, date date)
-LOCATION ('gpfdist://host:port/filename.txt)
-FORMAT 'TEXT' (DELIMITER '|');
-```
-
-

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----
-title: Formatting Data Files
----
-
-When you use the HAWQ tools for loading and unloading data, you must specify how your data is formatted. `COPY`, `CREATE             EXTERNAL TABLE, `and `hawq load` have clauses that allow you to specify how your data is formatted. Data can be delimited text (`TEXT`) or comma separated values (`CSV`) format. External data must be formatted correctly to be read by HAWQ. This topic explains the format of data files expected by HAWQ.
-
--   **[Formatting Rows](../../datamgmt/load/g-formatting-rows.html)**
-
--   **[Formatting Columns](../../datamgmt/load/g-formatting-columns.html)**
-
--   **[Representing NULL Values](../../datamgmt/load/g-representing-null-values.html)**
-
--   **[Escaping](../../datamgmt/load/g-escaping.html)**
-
--   **[Character Encoding](../../datamgmt/load/g-character-encoding.html)**
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-formatting-rows.html.md.erb
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----
-title: Formatting Rows
----
-
-HAWQ expects rows of data to be separated by the `LF` character (Line feed, `0x0A`), `CR` (Carriage return, `0x0D`), or `CR` followed by `LF` (`CR+LF`, `0x0D 0x0A`). `LF` is the standard newline representation on UNIX or UNIX-like operating systems. Operating systems such as Windows or Mac OS X use `CR` or `CR+LF`. All of these representations of a newline are supported by HAWQ as a row delimiter. For more information, see [Importing and Exporting Fixed Width Data](g-importing-and-exporting-fixed-width-data.html#topic37).
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-gpfdist-protocol.html.md.erb
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----
-title: gpfdist Protocol
----
-
-The `gpfdist://` protocol is used in a URI to reference a running `gpfdist` instance. The `gpfdist` utility serves external data files from a directory on a file host to all HAWQ segments in parallel.
-
-`gpfdist` is located in the `$GPHOME/bin` directory on your HAWQ master host and on each segment host.
-
-Run `gpfdist` on the host where the external data files reside. `gpfdist` uncompresses `gzip` (`.gz`) and `bzip2` (.`bz2`) files automatically. You can use the wildcard character (\*) or other C-style pattern matching to denote multiple files to read. The files specified are assumed to be relative to the directory that you specified when you started the `gpfdist` instance.
-
-All virtual segments access the external file(s) in parallel, subject to the number of segments set in the `gp_external_max_segments` parameter, the length of the `gpfdist` location list, and the limits specified by the `hawq_rm_nvseg_perquery_limit` and `hawq_rm_nvseg_perquery_perseg_limit` parameters. Use multiple `gpfdist` data sources in a `CREATE EXTERNAL TABLE` statement to scale the external table's scan performance. For more information about configuring `gpfdist`, see [Using the HAWQ File Server (gpfdist)](g-using-the-hawq-file-server--gpfdist-.html#topic13).
-
-See the `gpfdist` reference documentation for more information about using `gpfdist` with external tables.
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-gpfdists-protocol.html.md.erb
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----
-title: gpfdists Protocol
----
-
-The `gpfdists://` protocol is a secure version of the `gpfdist://         protocol`. To use it, you run the `gpfdist` utility with the `--ssl` option. When specified in a URI, the `gpfdists://` protocol enables encrypted communication and secure identification of the file server and the HAWQ to protect against attacks such as eavesdropping and man-in-the-middle attacks.
-
-`gpfdists` implements SSL security in a client/server scheme with the following attributes and limitations:
-
--   Client certificates are required.
--   Multilingual certificates are not supported.
--   A Certificate Revocation List (CRL) is not supported.
--   The `TLSv1` protocol is used with the `TLS_RSA_WITH_AES_128_CBC_SHA` encryption algorithm.
--   SSL parameters cannot be changed.
--   SSL renegotiation is supported.
--   The SSL ignore host mismatch parameter is set to `false`.
--   Private keys containing a passphrase are not supported for the `gpfdist` file server (server.key) and for the HAWQ (client.key).
--   Issuing certificates that are appropriate for the operating system in use is the user's responsibility. Generally, converting certificates as shown in [https://www.sslshopper.com/ssl-converter.html](https://www.sslshopper.com/ssl-converter.html) is supported.
-
-    **Note:** A server started with the `gpfdist --ssl` option can only communicate with the `gpfdists` protocol. A server that was started with `gpfdist` without the `--ssl` option can only communicate with the `gpfdist` protocol.
-
--   The client certificate file, client.crt
--   The client private key file, client.key
-
-Use one of the following methods to invoke the `gpfdists` protocol.
-
--   Run `gpfdist` with the `--ssl` option and then use the `gpfdists` protocol in the `LOCATION` clause of a `CREATE EXTERNAL TABLE` statement.
--   Use a `hawq load` YAML control file with the `SSL` option set to true.
-
-Using `gpfdists` requires that the following client certificates reside in the `$PGDATA/gpfdists` directory on each segment.
-
--   The client certificate file, `client.crt`
--   The client private key file, `client.key`
--   The trusted certificate authorities, `root.crt`
-
-For an example of loading data into an external table security, see [Example 3 - Multiple gpfdists instances](creating-external-tables-examples.html#topic47).
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-handling-errors-ext-table-data.html.md.erb
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----
-title: Handling Errors in External Table Data
----
-
-By default, if external table data contains an error, the command fails and no data loads into the target database table. Define the external table with single row error handling to enable loading correctly formatted rows and to isolate data errors in external table data. See [Handling Load Errors](g-handling-load-errors.html#topic55).
-
-The `gpfdist` file server uses the `HTTP` protocol. External table queries that use `LIMIT` end the connection after retrieving the rows, causing an HTTP socket error. If you use `LIMIT` in queries of external tables that use the `gpfdist://` or `http:// protocols`, ignore these errors \u2013 data is returned to the database as expected.
-
-

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----
-title: Handling Load Errors
----
-
-Readable external tables are most commonly used to select data to load into regular database tables. You use the `CREATE TABLE AS SELECT` or `INSERT                 INTO `commands to query the external table data. By default, if the data contains an error, the entire command fails and the data is not loaded into the target database table.
-
-The `SEGMENT REJECT LIMIT` clause allows you to isolate format errors in external table data and to continue loading correctly formatted rows. Use `SEGMENT REJECT LIMIT `to set an error threshold, specifying the reject limit `count` as number of `ROWS` (the default) or as a `PERCENT` of total rows (1-100).
-
-The entire external table operation is aborted, and no rows are processed, if the number of error rows reaches the `SEGMENT REJECT LIMIT`. The limit of error rows is per-segment, not per entire operation. The operation processes all good rows, and it discards and optionally logs formatting errors for erroneous rows, if the number of error rows does not reach the `SEGMENT REJECT                 LIMIT`.
-
-The `LOG ERRORS` clause allows you to keep error rows for further examination. For information about the `LOG ERRORS` clause, see the `CREATE EXTERNAL TABLE` command.
-
-When you set `SEGMENT REJECT LIMIT`, HAWQ scans the external data in single row error isolation mode. Single row error isolation mode applies to external data rows with format errors such as extra or missing attributes, attributes of a wrong data type, or invalid client encoding sequences. HAWQ does not check constraint errors, but you can filter constraint errors by limiting the `SELECT` from an external table at runtime. For example, to eliminate duplicate key errors:
-
-``` sql
-=# INSERT INTO table_with_pkeys 
-SELECT DISTINCT * FROM external_table;
-```
-
--   **[Define an External Table with Single Row Error Isolation](../../datamgmt/load/g-define-an-external-table-with-single-row-error-isolation.html)**
-
--   **[Capture Row Formatting Errors and Declare a Reject Limit](../../datamgmt/load/g-create-an-error-table-and-declare-a-reject-limit.html)**
-
--   **[Identifying Invalid CSV Files in Error Table Data](../../datamgmt/load/g-identifying-invalid-csv-files-in-error-table-data.html)**
-
--   **[Moving Data between Tables](../../datamgmt/load/g-moving-data-between-tables.html)**
-
-

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----
-title: Identifying Invalid CSV Files in Error Table Data
----
-
-If a CSV file contains invalid formatting, the *rawdata* field in the error table can contain several combined rows. For example, if a closing quote for a specific field is missing, all the following newlines are treated as embedded newlines. When this happens, HAWQ stops parsing a row when it reaches 64K, puts that 64K of data into the error table as a single row, resets the quote flag, and continues. If this happens three times during load processing, the load file is considered invalid and the entire load fails with the message "`rejected ` `N` ` or more rows`". See [Escaping in CSV Formatted Files](g-escaping-in-csv-formatted-files.html#topic101) for more information on the correct use of quotes in CSV files.
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-importing-and-exporting-fixed-width-data.html.md.erb
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----
-title: Importing and Exporting Fixed Width Data
----
-
-Specify custom formats for fixed-width data with the HAWQ functions `fixedwith_in` and `fixedwidth_out`. These functions already exist in the file `$GPHOME/share/postgresql/cdb_external_extensions.sql`. The following example declares a custom format, then calls the `fixedwidth_in` function to format the data.
-
-``` sql
-CREATE READABLE EXTERNAL TABLE students (
-  name varchar(20), address varchar(30), age int)
-LOCATION ('gpfdist://mdw:8081/students.txt')
-FORMAT 'CUSTOM' (formatter=fixedwidth_in, name='20', address='30', age='4');
-```
-
-The following options specify how to import fixed width data.
-
--   Read all the data.
-
-    To load all the fields on a line of fixed with data, you must load them in their physical order. You must specify the field length, but cannot specify a starting and ending position. The fields names in the fixed width arguments must match the order in the field list at the beginning of the `CREATE TABLE` command.
-
--   Set options for blank and null characters.
-
-    Trailing blanks are trimmed by default. To keep trailing blanks, use the `preserve_blanks=on` option.You can reset the trailing blanks option to the default with the `preserve_blanks=off` option.
-
-    Use the null=`'null_string_value'` option to specify a value for null characters.
-
--   If you specify `preserve_blanks=on`, you must also define a value for null characters.
--   If you specify `preserve_blanks=off`, null is not defined, and the field contains only blanks, HAWQ writes a null to the table. If null is defined, HAWQ writes an empty string to the table.
-
-    Use the `line_delim='line_ending'` parameter to specify the line ending character. The following examples cover most cases. The `E` specifies an escape string constant.
-
-    ``` pre
-    line_delim=E'\n'
-    line_delim=E'\r'
-    line_delim=E'\r\n'
-    line_delim='abc'
-    ```
-
-

http://git-wip-us.apache.org/repos/asf/incubator-hawq-docs/blob/de1e2e07/datamgmt/load/g-installing-gpfdist.html.md.erb
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----
-title: Installing gpfdist
----
-
-You may choose to run `gpfdist` from a machine other than the HAWQ master, such as on a machine devoted to ETL processing. To install `gpfdist` on your ETL server, refer to [Client-Based HAWQ Load Tools](client-loadtools.html) for information related to Linux and Windows load tools installation and configuration.
-
-

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----
-title: Load the Data
----
-
-Create the tables with SQL statements based on the appropriate schema.
-
-There are no special requirements for the HAWQ tables that hold loaded data. In the prices example, the following command creates the appropriate table.
-
-``` sql
-CREATE TABLE prices (
-  itemnumber integer,       
-  price       decimal        
-) 
-DISTRIBUTED BY (itemnumber);
-```
-
-

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----
-title: Loading and Unloading Data
----
-
-The topics in this section describe methods for loading and writing data into and out of HAWQ, and how to format data files. It also covers registering HDFS files and folders directly into HAWQ internal tables.
-
-HAWQ supports high-performance parallel data loading and unloading, and for smaller amounts of data, single file, non-parallel data import and export.
-
-HAWQ can read from and write to several types of external data sources, including text files, Hadoop file systems, and web servers.
-
--   The `COPY` SQL command transfers data between an external text file on the master host and a HAWQ database table.
--   External tables allow you to query data outside of the database directly and in parallel using SQL commands such as `SELECT`, `JOIN`, or `SORT           EXTERNAL TABLE DATA`, and you can create views for external tables. External tables are often used to load external data into a regular database table using a command such as `CREATE TABLE table AS SELECT * FROM ext_table`.
--   External web tables provide access to dynamic data. They can be backed with data from URLs accessed using the HTTP protocol or by the output of an OS script running on one or more segments.
--   The `gpfdist` utility is the HAWQ parallel file distribution program. It is an HTTP server that is used with external tables to allow HAWQ segments to load external data in parallel, from multiple file systems. You can run multiple instances of `gpfdist` on different hosts and network interfaces and access them in parallel.
--   The `hawq load` utility automates the steps of a load task using a YAML-formatted control file.
-
-The method you choose to load data depends on the characteristics of the source data\u2014its location, size, format, and any transformations required.
-
-In the simplest case, the `COPY` SQL command loads data into a table from a text file that is accessible to the HAWQ master instance. This requires no setup and provides good performance for smaller amounts of data. With the `COPY` command, the data copied into or out of the database passes between a single file on the master host and the database. This limits the total size of the dataset to the capacity of the file system where the external file resides and limits the data transfer to a single file write stream.
-
-More efficient data loading options for large datasets take advantage of the HAWQ MPP architecture, using the HAWQ segments to load data in parallel. These methods allow data to load simultaneously from multiple file systems, through multiple NICs, on multiple hosts, achieving very high data transfer rates. External tables allow you to access external files from within the database as if they are regular database tables. When used with `gpfdist`, the HAWQ parallel file distribution program, external tables provide full parallelism by using the resources of all HAWQ segments to load or unload data.
-
-HAWQ leverages the parallel architecture of the Hadoop Distributed File System to access files on that system.
-
--   **[Working with File-Based External Tables](../../datamgmt/load/g-working-with-file-based-ext-tables.html)**
-
--   **[Using the HAWQ File Server (gpfdist)](../../datamgmt/load/g-using-the-hawq-file-server--gpfdist-.html)**
-
--   **[Creating and Using Web External Tables](../../datamgmt/load/g-creating-and-using-web-external-tables.html)**
-
--   **[Loading Data Using an External Table](../../datamgmt/load/g-loading-data-using-an-external-table.html)**
-
--   **[Registering Files into HAWQ Internal Tables](../../datamgmt/load/g-register_files.html)**
-
--   **[Loading and Writing Non-HDFS Custom Data](../../datamgmt/load/g-loading-and-writing-non-hdfs-custom-data.html)**
-
--   **[Creating External Tables - Examples](../../datamgmt/load/creating-external-tables-examples.html#topic44)**
-
--   **[Handling Load Errors](../../datamgmt/load/g-handling-load-errors.html)**
-
--   **[Loading Data with hawq load](../../datamgmt/load/g-loading-data-with-hawqload.html)**
-
--   **[Loading Data with COPY](../../datamgmt/load/g-loading-data-with-copy.html)**
-
--   **[Running COPY in Single Row Error Isolation Mode](../../datamgmt/load/g-running-copy-in-single-row-error-isolation-mode.html)**
-
--   **[Optimizing Data Load and Query Performance](../../datamgmt/load/g-optimizing-data-load-and-query-performance.html)**
-
--   **[Unloading Data from HAWQ](../../datamgmt/load/g-unloading-data-from-hawq-database.html)**
-
--   **[Transforming XML Data](../../datamgmt/load/g-transforming-xml-data.html)**
-
--   **[Formatting Data Files](../../datamgmt/load/g-formatting-data-files.html)**
-
-

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----
-title: Loading and Writing Non-HDFS Custom Data
----
-
-HAWQ supports `TEXT` and `CSV` formats for importing and exporting data. You can load and write the data in other formats by defining and using a custom format or custom protocol.
-
--   **[Using a Custom Format](../../datamgmt/load/g-using-a-custom-format.html)**
-
-

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----
-title: Loading Data Using an External Table
----
-
-Use SQL commands such as `INSERT` and `SELECT` to query a readable external table, the same way that you query a regular database table. For example, to load travel expense data from an external table, `ext_expenses`, into a database table,` expenses_travel`:
-
-``` sql
-=# INSERT INTO expenses_travel 
-SELECT * FROM ext_expenses WHERE category='travel';
-```
-
-To load all data into a new database table:
-
-``` sql
-=# CREATE TABLE expenses AS SELECT * FROM ext_expenses;
-```
-
-

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----
-title: Loading Data with COPY
----
-
-`COPY FROM` copies data from a file or standard input into a table and appends the data to the table contents. `COPY` is non-parallel: data is loaded in a single process using the HAWQ master instance. Using `COPY` is only recommended for very small data files.
-
-The `COPY` source file must be accessible to the master host. Specify the `COPY` source file name relative to the master host location.
-
-HAWQ copies data from `STDIN` or `STDOUT` using the connection between the client and the master server.
-
-

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----
-title: Loading Data with hawq load
----
-
-The HAWQ `hawq load` utility loads data using readable external tables and the HAWQ parallel file server ( `gpfdist` or `gpfdists`). It handles parallel file-based external table setup and allows users to configure their data format, external table definition, and `gpfdist` or `gpfdists` setup in a single configuration file.
-
-## <a id="topic62__du168147"></a>To use hawq load
-
-1.  Ensure that your environment is set up to run `hawq                         load`. Some dependent files from your HAWQ /&gt; installation are required, such as `gpfdist` and Python, as well as network access to the HAWQ segment hosts.
-2.  Create your load control file. This is a YAML-formatted file that specifies the HAWQ connection information, `gpfdist` configuration information, external table options, and data format.
-
-    For example:
-
-    ``` pre
-    ---
-    VERSION: 1.0.0.1
-    DATABASE: ops
-    USER: gpadmin
-    HOST: mdw-1
-    PORT: 5432
-    GPLOAD:
-       INPUT:
-        - SOURCE:
-             LOCAL_HOSTNAME:
-               - etl1-1
-               - etl1-2
-               - etl1-3
-               - etl1-4
-             PORT: 8081
-             FILE: 
-               - /var/load/data/*
-        - COLUMNS:
-               - name: text
-               - amount: float4
-               - category: text
-               - description: text
-               - date: date
-        - FORMAT: text
-        - DELIMITER: '|'
-        - ERROR_LIMIT: 25
-        - ERROR_TABLE: payables.err_expenses
-       OUTPUT:
-        - TABLE: payables.expenses
-        - MODE: INSERT
-    SQL:
-       - BEFORE: "INSERT INTO audit VALUES('start', current_timestamp)"
-       - AFTER: "INSERT INTO audit VALUES('end', current_timestamp)"
-    ```
-
-3.  Run `hawq load`, passing in the load control file. For example:
-
-    ``` shell
-    $ hawq load -f my_load.yml
-    ```
-
-

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----
-title: Moving Data between Tables
----
-
-You can use `CREATE TABLE AS` or `INSERT...SELECT` to load external and web external table data into another (non-external) database table, and the data will be loaded in parallel according to the external or web external table definition.
-
-If an external table file or web external table data source has an error, one of the following will happen, depending on the isolation mode used:
-
--   **Tables without error isolation mode**: any operation that reads from that table fails. Loading from external and web external tables without error isolation mode is an all or nothing operation.
--   **Tables with error isolation mode**: the entire file will be loaded, except for the problematic rows (subject to the configured REJECT\_LIMIT)
-
-

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----
-title: Optimizing Data Load and Query Performance
----
-
-Use the following tip to help optimize your data load and subsequent query performance.
-
--   Run `ANALYZE` after loading data. If you significantly altered the data in a table, run `ANALYZE` or `VACUUM                     ANALYZE` (system catalog tables only) to update table statistics for the query optimizer. Current statistics ensure that the optimizer makes the best decisions during query planning and avoids poor performance due to inaccurate or nonexistent statistics.
-
-
-

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----
-title: Registering Files into HAWQ Internal Tables
----
-
-The `hawq register` utility loads and registers HDFS data files or folders into HAWQ internal tables. Files can be read directly, rather than having to be copied or loaded, resulting in higher performance and more efficient transaction processing.
-
-Data from the file or directory specified by \<hdfsfilepath\> is loaded into the appropriate HAWQ table directory in HDFS and the utility updates the corresponding HAWQ metadata for the files. Either AO or Parquet-formatted tables in HDFS can be loaded into a corresponding table in HAWQ.
-
-You can use `hawq register` either to:
-
--  Load and register external Parquet-formatted file data generated by an external system such as Hive or Spark.
--  Recover cluster data from a backup cluster for disaster recovery. 
-
-Requirements for running `hawq register` on the  server are:
-
--   All hosts in your HAWQ cluster (master and segments) must have network access between them and the hosts containing the data to be loaded.
--   The Hadoop client must be configured and the hdfs filepath specified.
--   The files to be registered and the HAWQ table must be located in the same HDFS cluster.
--   The target table DDL is configured with the correct data type mapping.
-
-##<a id="topic1__section2"></a>Registering Externally Generated HDFS File Data to an Existing Table
-
-Files or folders in HDFS can be registered into an existing table, allowing them to be managed as a HAWQ internal table. When registering files, you can optionally specify the maximum amount of data to be loaded, in bytes, using the `--eof` option. If registering a folder, the actual file sizes are used. 
-
-Only HAWQ or Hive-generated Parquet tables are supported. Partitioned tables are not supported. Attempting to register these tables will result in an error. 
-
-Metadata for the Parquet file(s) and the destination table must be consistent. Different data types are used by HAWQ tables and Parquet files, so data must be mapped. You must verify that the structure of the Parquet files and the HAWQ table are compatible before running `hawq register`. Not all HIVE data types can be mapped to HAWQ equivalents. The currently-supported HIVE data types are: boolean, int, smallint, tinyint, bigint, float, double, string, binary, char, and varchar.
-
-As a best practice, create a copy of the Parquet file to be registered before running ```hawq register```
-You can then then run ```hawq register``` on the copy,  leaving the original file available for additional Hive queries or if a data mapping error is encountered.
-
-###Limitations for Registering Hive Tables to HAWQ 
-
-The following HIVE data types cannot be converted to HAWQ equivalents: timestamp, decimal, array, struct, map, and union.   
-
-###Example: Registering a Hive-Generated Parquet File
-
-This example shows how to register a HIVE-generated parquet file in HDFS into the table `parquet_table` in HAWQ, which is in the database named `postgres`. The file path of the HIVE-generated file is `hdfs://localhost:8020/temp/hive.paq`.
-
-In this example, the location of the database is `hdfs://localhost:8020/hawq_default`, the tablespace id is 16385, the database id is 16387, the table filenode id is 77160, and the last file under the filenode is numbered 7.
-
-Run the `hawq register` command for the file location  `hdfs://localhost:8020/temp/hive.paq`:
-
-``` pre
-$ hawq register -d postgres -f hdfs://localhost:8020/temp/hive.paq parquet_table
-```
-
-After running the `hawq register` command, the corresponding new location of the file in HDFS is:  `hdfs://localhost:8020/hawq_default/16385/16387/77160/8`. 
-
-The command updates the metadata of the table `parquet_table` in HAWQ, which is contained in the table `pg_aoseg.pg_paqseg_77160`. The pg\_aoseg table is a fixed schema for row-oriented and Parquet AO tables. For row-oriented tables, the table name prefix is pg\_aoseg. For Parquet tables, the table name prefix is pg\_paqseg. 77160 is the relation id of the table.
-
-You can locate the table by one of two methods, either  by relation ID or by table name. 
-
-To find the relation ID, run the following command on the catalog table pg\_class: 
-
-```
-SELECT oid FROM pg_class WHERE relname=$relname
-```
-To find the table name, run the command: 
-
-```
-SELECT segrelid FROM pg_appendonly WHERE relid = $relid
-```
-then run: 
-
-```
-SELECT relname FROM pg_class WHERE oid = segrelid
-```
-
-## <a id="topic1__section3"></a>Registering Data Using Information from a YAML Configuration File
- 
-The `hawq register` command can register HDFS files  by using metadata loaded from a YAML configuration file by using the `--config <yaml_config\>` option. Both AO and Parquet tables can be registered. Tables need not exist in HAWQ before being registered. In disaster recovery, information in a YAML-format file created by the `hawq extract` command can re-create HAWQ tables by using metadata from a backup checkpoint.
-
-You can also use a YAML confguration file to append HDFS files to an existing HAWQ table or create a table and register it into HAWQ.
-
-For disaster recovery, tables can be re-registered using the HDFS files and a YAML file. The clusters are assumed to have data periodically imported from Cluster A to Cluster B. 
-
-Data is registered according to the following conditions: 
-
--  Existing tables have files appended to the existing HAWQ table.
--  If a table does not exist, it is created and registered into HAWQ. The catalog table will be updated with the file size specified by the YAML file.
--  If the -\\\-force option is used, the data in existing catalog tables is erased and re-registered. All HDFS-related catalog contents in `pg_aoseg.pg_paqseg_$relid ` are cleared. The original files on HDFS are retained.
-
-Tables using random distribution are preferred for registering into HAWQ.
-
-There are additional restrictions when registering hash tables. When registering hash-distributed tables using a YAML file, the distribution policy in the YAML file must match that of the table being registered into and the order of the files in the YAML file should reflect the hash distribution. The size of the registered file should be identical to or a multiple of the hash table bucket number. 
-
-Only single-level partitioned tables can be registered into HAWQ.
-
-
-###Example: Registration using a YAML Configuration File
-
-This example shows how to use `hawq register` to register HDFS data using a YAML configuration file generated by hawq extract. 
-
-First, create a table in SQL and insert some data into it.  
-
-```
-=> CREATE TABLE paq1(a int, b varchar(10))with(appendonly=true, orientation=parquet);
-=> INSERT INTO paq1 VALUES(generate_series(1,1000), 'abcde');
-```
-
-Extract the table metadata by using the `hawq extract` utility.
-
-```
-hawq extract -o paq1.yml paq1
-```
-
-Register the data into new table paq2, using the -\\\-config option to identify the YAML file.
-
-```
-hawq register --config paq1.yml paq2
-```
-Select the new table and check to verify that  the content has been registered.
-
-```
-=> SELECT count(*) FROM paq2;
-```
-
-
-## <a id="topic1__section4"></a>Data Type Mapping<a id="topic1__section4"></a>
-
-HIVE and Parquet tables use different data types than HAWQ tables and must be mapped for metadata compatibility. You are responsible for making sure your implementation is mapped to the appropriate data type before running `hawq register`. The tables below show equivalent data types, if available.
-
-<span class="tablecap">Table 1. HAWQ to Parquet Mapping</span>
-
-|HAWQ Data Type   | Parquet Data Type  |
-| :------------| :---------------|
-| bool        | boolean       |
-| int2/int4/date        | int32       |
-| int8/money       | int64      |
-| time/timestamptz/timestamp       | int64      |
-| float4        | float       |
-|float8        | double       |
-|bit/varbit/bytea/numeric       | Byte array       |
-|char/bpchar/varchar/name| Byte array |
-| text/xml/interval/timetz  | Byte array  |
-| macaddr/inet/cidr  | Byte array  |
-
-**Additional HAWQ-to-Parquet Mapping**
-
-**point**:  
-
-``` 
-group {
-    required int x;
-    required int y;
-}
-```
-
-**circle:** 
-
-```
-group {
-    required int x;
-    required int y;
-    required int r;
-}
-```
-
-**box:**  
-
-```
-group {
-    required int x1;
-    required int y1;
-    required int x2;
-    required int y2;
-}
-```
-
-**iseg:** 
-
-
-```
-group {
-    required int x1;
-    required int y1;
-    required int x2;
-    required int y2;
-}
-``` 
-
-**path**:
-  
-```
-group {
-    repeated group {
-        required int x;
-        required int y;
-    }
-}
-```
-
-
-<span class="tablecap">Table 2. HIVE to HAWQ Mapping</span>
-
-|HIVE Data Type   | HAWQ Data Type  |
-| :------------| :---------------|
-| boolean        | bool       |
-| tinyint        | int2       |
-| smallint       | int2/smallint      |
-| int            | int4 / int |
-| bigint         | int8 / bigint      |
-| float        | float4       |
-| double	| float8 |
-| string        | varchar       |
-| binary      | bytea       |
-| char | char |
-| varchar  | varchar  |
-
-
-### Extracting Metadata
-
-For more information on extracting metadata to a YAML file and the output content of the YAML file, refer to the reference page for [hawq extract](../../reference/cli/admin_utilities/hawqextract.html#topic1).
-
-
-

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----
-title: Representing NULL Values
----
-
-`NULL` represents an unknown piece of data in a column or field. Within your data files you can designate a string to represent null values. The default string is `\N` (backslash-N) in `TEXT` mode, or an empty value with no quotations in `CSV` mode. You can also declare a different string using the `NULL` clause of `COPY`, `CREATE EXTERNAL                 TABLE `or the `hawq load` control file when defining your data format. For example, you can use an empty string if you do not want to distinguish nulls from empty strings. When using the HAWQ loading tools, any data item that matches the designated null string is considered a null value.
-
-

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----
-title: Running COPY in Single Row Error Isolation Mode
----
-
-By default, `COPY` stops an operation at the first error: if the data contains an error, the operation fails and no data loads. If you run `COPY                 FROM` in *single row error isolation mode*, HAWQ skips rows that contain format errors and loads properly formatted rows. Single row error isolation mode applies only to rows in the input file that contain format errors. If the data contains a contraint error such as violation of a `NOT NULL` or `CHECK` constraint, the operation fails and no data loads.
-
-Specifying `SEGMENT REJECT LIMIT` runs the `COPY` operation in single row error isolation mode. Specify the acceptable number of error rows on each segment, after which the entire `COPY FROM` operation fails and no rows load. The error row count is for each HAWQ segment, not for the entire load operation.
-
-If the `COPY` operation does not reach the error limit, HAWQ loads all correctly-formatted rows and discards the error rows. The `LOG ERRORS INTO` clause allows you to keep error rows for further examination. Use `LOG ERRORS` to capture data formatting errors internally in HAWQ. For example:
-
-``` sql
-=> COPY country FROM '/data/gpdb/country_data'
-   WITH DELIMITER '|' LOG ERRORS INTO errtable
-   SEGMENT REJECT LIMIT 10 ROWS;
-```
-
-

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----
-title: Starting and Stopping gpfdist
----
-
-You can start `gpfdist` in your current directory location or in any directory that you specify. The default port is `8080`.
-
-From your current directory, type:
-
-``` shell
-$ gpfdist &
-```
-
-From a different directory, specify the directory from which to serve files, and optionally, the HTTP port to run on.
-
-To start `gpfdist` in the background and log output messages and errors to a log file:
-
-``` shell
-$ gpfdist -d /var/load_files -p 8081 -l /home/gpadmin/log &
-```
-
-For multiple `gpfdist` instances on the same ETL host (see [External Tables Using Multiple gpfdist Instances with Multiple NICs](g-about-gpfdist-setup-and-performance.html#topic14__du165882)), use a different base directory and port for each instance. For example:
-
-``` shell
-$ gpfdist -d /var/load_files1 -p 8081 -l /home/gpadmin/log1 &
-$ gpfdist -d /var/load_files2 -p 8082 -l /home/gpadmin/log2 &
-```
-
-To stop `gpfdist` when it is running in the background:
-
-First find its process id:
-
-``` shell
-$ ps -ef | grep gpfdist
-```
-
-Then kill the process, for example (where 3456 is the process ID in this example):
-
-``` shell
-$ kill 3456
-```
-
-

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----
-title: Transfer and Store the Data
----
-
-Use one of the following approaches to transform the data with `gpfdist`.
-
--   `GPLOAD` supports only input transformations, but is easier to implement in many cases.
--   `INSERT INTO SELECT FROM` supports both input and output transformations, but exposes more details.
-
--   **[Transforming with GPLOAD](../../datamgmt/load/g-transforming-with-gpload.html)**
-
--   **[Transforming with INSERT INTO SELECT FROM](../../datamgmt/load/g-transforming-with-insert-into-select-from.html)**
-
--   **[Configuration File Format](../../datamgmt/load/g-configuration-file-format.html)**
-
-

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----
-title: Transforming with GPLOAD
----
-
-To transform data using the `GPLOAD ` control file, you must specify both the file name for the `TRANSFORM_CONFIG` file and the name of the `TRANSFORM` operation in the `INPUT` section of the `GPLOAD` control file.
-
--   `TRANSFORM_CONFIG `specifies the name of the `gpfdist` configuration file.
--   The `TRANSFORM` setting indicates the name of the transformation that is described in the file named in `TRANSFORM_CONFIG`.
-
-``` pre
----
-VERSION: 1.0.0.1
-DATABASE: ops
-USER: gpadmin
-GPLOAD:
-INPUT:
-- TRANSFORM_CONFIG: config.yaml
-- TRANSFORM: prices_input
-- SOURCE:
-FILE: prices.xml
-```
-
-The transformation operation name must appear in two places: in the `TRANSFORM` setting of the `gpfdist` configuration file and in the `TRANSFORMATIONS` section of the file named in the `TRANSFORM_CONFIG` section.
-
-In the `GPLOAD` control file, the optional parameter `MAX_LINE_LENGTH` specifies the maximum length of a line in the XML transformation data that is passed to hawq load.
-
-The following diagram shows the relationships between the `GPLOAD` control file, the `gpfdist` configuration file, and the XML data file.
-
-<img src="../../images/03-gpload-files.jpg" class="image" width="415" height="258" />
-

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----
-title: Transforming with INSERT INTO SELECT FROM
----
-
-Specify the transformation in the `CREATE EXTERNAL TABLE` definition's `LOCATION` clause. For example, the transform is shown in bold in the following command. (Run `gpfdist` first, using the command `gpfdist             -c config.yaml`).
-
-``` sql
-CREATE READABLE EXTERNAL TABLE prices_readable (LIKE prices)
-   LOCATION ('gpfdist://hostname:8081/prices.xml#transform=prices_input')
-   FORMAT 'TEXT' (DELIMITER '|')
-   LOG ERRORS INTO error_log SEGMENT REJECT LIMIT 10;
-```
-
-In the command above, change *hostname* to your hostname. `prices_input` comes from the configuration file.
-
-The following query loads data into the `prices` table.
-
-``` sql
-INSERT INTO prices SELECT * FROM prices_readable;
-```
-
-

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----
-title: Transforming XML Data
----
-
-The HAWQ data loader *gpfdist* provides transformation features to load XML data into a table and to write data from the HAWQ to XML files. The following diagram shows *gpfdist* performing an XML transform.
-
-<a id="topic75__du185408"></a>
-<span class="figtitleprefix">Figure: </span>External Tables using XML Transformations
-
-<img src="../../images/ext-tables-xml.png" class="image" />
-
-To load or extract XML data:
-
--   [Determine the Transformation Schema](g-determine-the-transformation-schema.html#topic76)
--   [Write a Transform](g-write-a-transform.html#topic77)
--   [Write the gpfdist Configuration](g-write-the-gpfdist-configuration.html#topic78)
--   [Load the Data](g-load-the-data.html#topic79)
--   [Transfer and Store the Data](g-transfer-and-store-the-data.html#topic80)
-
-The first three steps comprise most of the development effort. The last two steps are straightforward and repeatable, suitable for production.
-
--   **[Determine the Transformation Schema](../../datamgmt/load/g-determine-the-transformation-schema.html)**
-
--   **[Write a Transform](../../datamgmt/load/g-write-a-transform.html)**
-
--   **[Write the gpfdist Configuration](../../datamgmt/load/g-write-the-gpfdist-configuration.html)**
-
--   **[Load the Data](../../datamgmt/load/g-load-the-data.html)**
-
--   **[Transfer and Store the Data](../../datamgmt/load/g-transfer-and-store-the-data.html)**
-
--   **[XML Transformation Examples](../../datamgmt/load/g-xml-transformation-examples.html)**
-
-

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----
-title: Troubleshooting gpfdist
----
-
-The segments access `gpfdist` at runtime. Ensure that the HAWQ segment hosts have network access to `gpfdist`. `gpfdist` is a web server: test connectivity by running the following command from each host in the HAWQ array (segments and master):
-
-``` shell
-$ wget http://gpfdist_hostname:port/filename      
-```
-
-The `CREATE EXTERNAL TABLE` definition must have the correct host name, port, and file names for `gpfdist`. Specify file names and paths relative to the directory from which `gpfdist` serves files (the directory path specified when `gpfdist` started). See [Creating External Tables - Examples](creating-external-tables-examples.html#topic44).
-
-If you start `gpfdist` on your system and IPv6 networking is disabled, `gpfdist` displays this warning message when testing for an IPv6 port.
-
-``` pre
-[WRN gpfdist.c:2050] Creating the socket failed
-```
-
-If the corresponding IPv4 port is available, `gpfdist` uses that port and the warning for IPv6 port can be ignored. To see information about the ports that `gpfdist` tests, use the `-V` option.
-
-For information about IPv6 and IPv4 networking, see your operating system documentation.
-
-

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----
-title: Unloading Data from HAWQ
----
-
-A writable external table allows you to select rows from other database tables and output the rows to files, named pipes, to applications, or as output targets for parallel MapReduce calculations. You can define file-based and web-based writable external tables.
-
-This topic describes how to unload data from HAWQ using parallel unload (writable external tables) and non-parallel unload (`COPY`).
-
--   **[Defining a File-Based Writable External Table](../../datamgmt/load/g-defining-a-file-based-writable-external-table.html)**
-
--   **[Defining a Command-Based Writable External Web Table](../../datamgmt/load/g-defining-a-command-based-writable-external-web-table.html)**
-
--   **[Unloading Data Using a Writable External Table](../../datamgmt/load/g-unloading-data-using-a-writable-external-table.html)**
-
--   **[Unloading Data Using COPY](../../datamgmt/load/g-unloading-data-using-copy.html)**
-
-

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----
-title: Unloading Data Using a Writable External Table
----
-
-Writable external tables allow only `INSERT` operations. You must grant `INSERT` permission on a table to enable access to users who are not the table owner or a superuser. For example:
-
-``` sql
-GRANT INSERT ON writable_ext_table TO admin;
-```
-
-To unload data using a writable external table, select the data from the source table(s) and insert it into the writable external table. The resulting rows are output to the writable external table. For example:
-
-``` sql
-INSERT INTO writable_ext_table SELECT * FROM regular_table;
-```
-
-

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----
-title: Unloading Data Using COPY
----
-
-`COPY TO` copies data from a table to a file (or standard input) on the HAWQ master host using a single process on the HAWQ master instance. Use `COPY` to output a table's entire contents, or filter the output using a `SELECT` statement. For example:
-
-``` sql
-COPY (SELECT * FROM country WHERE country_name LIKE 'A%') 
-TO '/home/gpadmin/a_list_countries.out';
-```
-
-

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----
-title: URL-based Web External Tables
----
-
-A URL-based web table accesses data from a web server using the HTTP protocol. Web table data is dynamic; the data is not rescannable.
-
-Specify the `LOCATION` of files on a web server using `http://`. The web data file(s) must reside on a web server that HAWQ segment hosts can access. The number of URLs specified corresponds to the minimum number of virtual segments that work in parallel to access the web table.
-
-The following sample command defines a web table that gets data from several URLs.
-
-``` sql
-=# CREATE EXTERNAL WEB TABLE ext_expenses (
-    name text, date date, amount float4, category text, description text) 
-LOCATION ('http://intranet.company.com/expenses/sales/file.csv',
-          'http://intranet.company.com/expenses/exec/file.csv',
-          'http://intranet.company.com/expenses/finance/file.csv',
-          'http://intranet.company.com/expenses/ops/file.csv',
-          'http://intranet.company.com/expenses/marketing/file.csv',
-          'http://intranet.company.com/expenses/eng/file.csv' 
-      )
-FORMAT 'CSV' ( HEADER );
-```
-
-

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----
-title: Using a Custom Format
----
-
-You specify a custom data format in the `FORMAT` clause of `CREATE             EXTERNAL TABLE`.
-
-```
-FORMAT 'CUSTOM' (formatter=format_function, key1=val1,...keyn=valn)
-```
-
-Where the `'CUSTOM'` keyword indicates that the data has a custom format and `formatter` specifies the function to use to format the data, followed by comma-separated parameters to the formatter function.
-
-HAWQ provides functions for formatting fixed-width data, but you must author the formatter functions for variable-width data. The steps are as follows.
-
-1.  Author and compile input and output functions as a shared library.
-2.  Specify the shared library function with `CREATE FUNCTION` in HAWQ.
-3.  Use the `formatter` parameter of `CREATE EXTERNAL                TABLE`'s `FORMAT` clause to call the function.
-
--   **[Importing and Exporting Fixed Width Data](../../datamgmt/load/g-importing-and-exporting-fixed-width-data.html)**
-
--   **[Examples - Read Fixed-Width Data](../../datamgmt/load/g-examples-read-fixed-width-data.html)**
-
-

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----
-title: Using the HAWQ File Server (gpfdist)
----
-
-The `gpfdist` protocol provides the best performance and is the easiest to set up. `gpfdist` ensures optimum use of all segments in your HAWQ system for external table reads.
-
-This topic describes the setup and management tasks for using `gpfdist` with external tables.
-
--   **[About gpfdist Setup and Performance](../../datamgmt/load/g-about-gpfdist-setup-and-performance.html)**
-
--   **[Controlling Segment Parallelism](../../datamgmt/load/g-controlling-segment-parallelism.html)**
-
--   **[Installing gpfdist](../../datamgmt/load/g-installing-gpfdist.html)**
-
--   **[Starting and Stopping gpfdist](../../datamgmt/load/g-starting-and-stopping-gpfdist.html)**
-
--   **[Troubleshooting gpfdist](../../datamgmt/load/g-troubleshooting-gpfdist.html)**
-
-

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----
-title: Working with File-Based External Tables
----
-
-External tables provide access to data stored in data sources outside of HAWQ as if the data were stored in regular database tables. Data can be read from or written to external tables.
-
-An external table is a HAWQ database table backed with data that resides outside of the database. An external table is either readable or writable. It can be used like a regular database table in SQL commands such as `SELECT` and `INSERT` and joined with other tables. External tables are most often used to load and unload database data.
-
-Web-based external tables provide access to data served by an HTTP server or an operating system process. See [Creating and Using Web External Tables](g-creating-and-using-web-external-tables.html#topic31) for more about web-based tables.
-
--   **[Accessing File-Based External Tables](../../datamgmt/load/g-external-tables.html)**
-
-    External tables enable accessing external files as if they are regular database tables. They are often used to move data into and out of a HAWQ database.
-
--   **[gpfdist Protocol](../../datamgmt/load/g-gpfdist-protocol.html)**
-
--   **[gpfdists Protocol](../../datamgmt/load/g-gpfdists-protocol.html)**
-
--   **[Handling Errors in External Table Data](../../datamgmt/load/g-handling-errors-ext-table-data.html)**
-
-

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----
-title: Write a Transform
----
-
-The transform specifies what to extract from the data.You can use any authoring environment and language appropriate for your project. For XML transformations, choose a technology such as XSLT, Joost (STX), Java, Python, or Perl, based on the goals and scope of the project.
-
-In the price example, the next step is to transform the XML data into a simple two-column delimited format.
-
-``` pre
-708421|19.99
-708466|59.25
-711121|24.99
-```
-
-The following STX transform, called *input\_transform.stx*, completes the data transformation.
-
-``` xml
-<?xml version="1.0"?>
-<stx:transform version="1.0"
-   xmlns:stx="http://stx.sourceforge.net/2002/ns"
-   pass-through="none">
-  <!-- declare variables -->
-  <stx:variable name="itemnumber"/>
-  <stx:variable name="price"/>
-  <!-- match and output prices as columns delimited by | -->
-  <stx:template match="/prices/pricerecord">
-    <stx:process-children/>
-    <stx:value-of select="$itemnumber"/>    
-<stx:text>|</stx:text>
-    <stx:value-of select="$price"/>      <stx:text>
-</stx:text>
-  </stx:template>
-  <stx:template match="itemnumber">
-    <stx:assign name="itemnumber" select="."/>
-  </stx:template>
-  <stx:template match="price">
-    <stx:assign name="price" select="."/>
-  </stx:template>
-</stx:transform>
-```
-
-This STX transform declares two temporary variables, `itemnumber` and `price`, and the following rules.
-
-1.  When an element that satisfies the XPath expression `/prices/pricerecord` is found, examine the child elements and generate output that contains the value of the `itemnumber` variable, a `|` character, the value of the price variable, and a newline.
-2.  When an `<itemnumber>` element is found, store the content of that element in the variable `itemnumber`.
-3.  When a &lt;price&gt; element is found, store the content of that element in the variable `price`.
-
-

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----
-title: Write the gpfdist Configuration
----
-
-The `gpfdist` configuration is specified as a YAML 1.1 document. It specifies rules that `gpfdist` uses to select a Transform to apply when loading or extracting data.
-
-This example `gpfdist` configuration contains the following items:
-
--   the `config.yaml` file defining `TRANSFORMATIONS`
--   the `input_transform.sh` wrapper script, referenced in the `config.yaml` file
--   the `input_transform.stx` joost transformation, called from `input_transform.sh`
-
-Aside from the ordinary YAML rules, such as starting the document with three dashes (`---`), a `gpfdist` configuration must conform to the following restrictions:
-
-1.  a `VERSION` setting must be present with the value `1.0.0.1`.
-2.  a `TRANSFORMATIONS` setting must be present and contain one or more mappings.
-3.  Each mapping in the `TRANSFORMATION` must contain:
-    -   a `TYPE` with the value 'input' or 'output'
-    -   a `COMMAND` indicating how the transform is run.
-
-4.  Each mapping in the `TRANSFORMATION` can contain optional `CONTENT`, `SAFE`, and `STDERR` settings.
-
-The following `gpfdist` configuration called `config.YAML` applies to the prices example. The initial indentation on each line is significant and reflects the hierarchical nature of the specification. The name `prices_input` in the following example will be referenced later when creating the table in SQL.
-
-``` pre
----
-VERSION: 1.0.0.1
-TRANSFORMATIONS:
-  prices_input:
-    TYPE:     input
-    COMMAND:  /bin/bash input_transform.sh %filename%
-```
-
-The `COMMAND` setting uses a wrapper script called `input_transform.sh` with a `%filename%` placeholder. When `gpfdist` runs the `prices_input` transform, it invokes `input_transform.sh` with `/bin/bash` and replaces the `%filename%` placeholder with the path to the input file to transform. The wrapper script called `input_transform.sh` contains the logic to invoke the STX transformation and return the output.
-
-If Joost is used, the Joost STX engine must be installed.
-
-``` bash
-#!/bin/bash
-# input_transform.sh - sample input transformation, 
-# demonstrating use of Java and Joost STX to convert XML into
-# text to load into HAWQ.
-# java arguments:
-#   -jar joost.jar ��������joost STX engine
-#   -nodecl                  don't generate a <?xml?> declaration
-#   $1                        filename to process
-#   input_transform.stx    the STX transformation
-#
-# the AWK step eliminates a blank line joost emits at the end
-java \
-    -jar joost.jar \
-    -nodecl \
-    $1 \
-    input_transform.stx \
- | awk 'NF>0
-```
-
-The `input_transform.sh` file uses the Joost STX engine with the AWK interpreter. The following diagram shows the process flow as `gpfdist` runs the transformation.
-
-<img src="../../images/02-pipeline.png" class="image" width="462" height="190" />
-

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----
-title: XML Transformation Examples
----
-
-The following examples demonstrate the complete process for different types of XML data and STX transformations. Files and detailed instructions associated with these examples can be downloaded from the Apache site `gpfdist_transform` tools demo page. Read the README file before you run the examples.
-
--   **[Command-based Web External Tables](../../datamgmt/load/g-example-1-dblp-database-publications-in-demo-directory.html)**
-
--   **[Example using IRS MeF XML Files (In demo Directory)](../../datamgmt/load/g-example-irs-mef-xml-files-in-demo-directory.html)**
-
--   **[Example using WITSML\u2122 Files (In demo Directory)](../../datamgmt/load/g-example-witsml-files-in-demo-directory.html)**
-
-

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----
-title: Creating and Managing Databases
----
-
-A HAWQ system is a single instance of HAWQ. There can be several separate HAWQ systems installed, but usually just one is selected by environment variable settings. See your HAWQ administrator for details.
-
-There can be multiple databases in a HAWQ system. This is different from some database management systems \(such as Oracle\) where the database instance *is* the database. Although you can create many databases in a HAWQ system, client programs can connect to and access only one database at a time \u2014 you cannot cross-query between databases.
-
-## <a id="topic3"></a>About Template Databases 
-
-Each new database you create is based on a *template*. HAWQ provides a default database, *template1*. Use *template1* to connect to HAWQ for the first time. HAWQ uses *template1* to create databases unless you specify another template. Do not create any objects in *template1* unless you want those objects to be in every database you create.
-
-HAWQ uses two other database templates, *template0* and *postgres*, internally. Do not drop or modify *template0* or *postgres*. You can use *template0* to create a completely clean database containing only the standard objects predefined by HAWQ at initialization, especially if you modified *template1*.
-
-## <a id="topic4"></a>Creating a Database 
-
-The `CREATE DATABASE` command creates a new database. For example:
-
-``` sql
-=> CREATE DATABASE new_dbname;
-```
-
-To create a database, you must have privileges to create a database or be a HAWQ superuser. If you do not have the correct privileges, you cannot create a database. The HAWQ administrator must either give you the necessary privileges or to create a database for you.
-
-You can also use the client program `createdb` to create a database. For example, running the following command in a command line terminal connects to HAWQ using the provided host name and port and creates a database named *mydatabase*:
-
-``` shell
-$ createdb -h masterhost -p 5432 mydatabase
-```
-
-The host name and port must match the host name and port of the installed HAWQ system.
-
-Some objects, such as roles, are shared by all the databases in a HAWQ system. Other objects, such as tables that you create, are known only in the database in which you create them.
-
-### <a id="topic5"></a>Cloning a Database 
-
-By default, a new database is created by cloning the standard system database template, *template1*. Any database can be used as a template when creating a new database, thereby providing the capability to 'clone' or copy an existing database and all objects and data within that database. For example:
-
-``` sql
-=> CREATE DATABASE new_dbname TEMPLATE old_dbname
-```
-
-## <a id="topic6"></a>Viewing the List of Databases 
-
-If you are working in the `psql` client program, you can use the `\l` meta-command to show the list of databases and templates in your HAWQ system. If using another client program and you are a superuser, you can query the list of databases from the `pg_database` system catalog table. For example:
-
-``` sql
-=> SELECT datname FROM pg_database;
-```
-
-## <a id="topic7"></a>Altering a Database 
-
-The ALTER DATABASE command changes database attributes such as owner, name, or default configuration attributes. For example, the following command alters a database by setting its default schema search path \(the `search_path` configuration parameter\):
-
-``` sql
-=> ALTER DATABASE mydatabase SET search_path TO myschema, public, pg_catalog;
-```
-
-To alter a database, you must be the owner of the database or a superuser.
-
-## <a id="topic8"></a>Dropping a Database 
-
-The `DROP DATABASE` command drops \(or deletes\) a database. It removes the system catalog entries for the database and deletes the database directory on disk that contains the data. You must be the database owner or a superuser to drop a database, and you cannot drop a database while you or anyone else is connected to it. Connect to `template1` \(or another database\) before dropping a database. For example:
-
-``` shell
-=> \c template1
-```
-``` sql
-=> DROP DATABASE mydatabase;
-```
-
-You can also use the client program `dropdb` to drop a database. For example, the following command connects to HAWQ using the provided host name and port and drops the database *mydatabase*:
-
-``` shell
-$ dropdb -h masterhost -p 5432 mydatabase
-```
-
-**Warning:** Dropping a database cannot be undone.