Bigquery Export Table Schema

Running the Code. Data Catalog. Hence we will have export our data to a CSV(comma separated. If a dataset has 50,000 or more tables, it will become slower to enumerate them, whether through an API call, the web UI,. Talend Data Fabric offers a single suite of cloud apps for data integration and data integrity to help enterprises collect, govern, transform, and share data. importing and exporting tabular data to and from Tabular Storage objects based on JSON Table Schema descriptors. Theoretically, you could use BigQuery’s streaming API to insert rows into a table, but this hasn’t been implemented. Order is important when structuring queries to export results from Treasure Data to Big Query, so make a note of the order of the fields in the schema. Dataset - Group tables and control access to tables. Choose to share it publicly and copy the public link for later use. While within one session may occur multiple hits, visited pages, etc. Specify the table schema: two necessary (column name and data type) and two optional (column mode and description). How to replace SAP BW with Google BigQuery? Included in this challenge was the BigQuery data schema design. bq load [--source_format=NEWLINE_DELIMITED_JSON|CSV] destination_table data_source_uri table_schema destination_table The fully-qualified table name of the table to create. This client provides an API for retrieving and inserting BigQuery data by wrapping Google's low-level API client library. Next, you'd see a Configure Flat File Destination window, select the table from the source table to export the data to the CSV file you specified earlier. Google BigQuery. The new Google BigQuery connector allows you to manipulate tables and views in BigQuery. Simply ensure that any new schema versions have been uploaded your Iglu registry, then start sending events with the new schema: the BigQuery Loader will create the corresponding additional column inside your BigQuery events table automatically. Google BigQuery logs are collected with Stackdriver and sent to a Cloud pub/sub with an HTTP push forwarder. this is either caused by the export from appengine. Double-click the table and choose Export table. Finally, create Athena tables by combining the extracted AVRO schema and Hive table definition. You will learn how to take data from the relational system and to the graph by translating the schema and using import tools. ENV variables are stored in the same directory in the file. This new offering is SAS/ACCESS engine for Google BigQuery. With these table formats, you can now use Dataproc for workloads that need: ACID transaction. In GCP a project is a way to organize cloud resources. Supermetrics for BigQuery is the first ever native BigQuery Data Transfer Service app for non-Google marketing platforms. See Understa. - ottogroup/schedoscope. employment_hours_earnings). BigQuery Page in google console Check table in BigQuery. Using the BigQuery Export schema, which of the following fields are available in BigQuery? Custom dimensions, landing page, hit number, client ID. For example, in Redshift, when you bulk load data into a table, if the user didn’t specify a compression scheme in the table definition, Redshift will analyze the data and find a scheme that works best, and automatically apply it to the table for you. Google Cloud’s AutoML Tables lets you automatically build and deploy state-of-the-art machine learning models using your own structured data. Depending on your workload the $500 credit might cover all your costs. These tables have the format "events_YYYYMMDD". Use the Schema Browser to create or remove objects, or view object properties. When you create a clustered table in BigQuery, the table data is automatically organized based on the contents of one or more columns in the table's schema. Next, you’d see a Configure Flat File Destination window, select the table from the source table to export the data to the CSV file you specified earlier. This page describes how to export or extract data from BigQuery tables. With an unfilled table in BigQuery, you need to set the schema manually:. If you select the single table schema, Mixpanel creates a mp_master_event table. Google BigQuery. In the BigQuery export, each row represents a session. Enter activity_email_send as the table name. Step 2: Setting up a Google BigQuery table. In this post, Kristoffer Olofsson walks us through how the BigQuery Export feature for Google Analytics Premium is put together, what it looks like, and some important things to be aware of when considering BigQuery Export as part of your Analytics solution. This client provides an API for retrieving and inserting BigQuery data by wrapping Google's low-level API client library. (bigquery-public-data:bls. Double-click the table and choose Export table. The generator has a number of options for customizing generated schemas. Unfortunately, the data hasn't been federated into a single table nor combined with weather data. Data Catalog. You can define your own schema manually, but BigQuery can autodetect the schema of CSV files based on the header row and a random sample of rows. Hence we will have export our data to a CSV(comma separated. You may then use transformations to enrich and manage the data in permanent tables. Treasure Data query results are automatically imported into this newly created table. Although BigQuery provides a number of built-in functions, it does not have a built-in for decoding URL-encoded strings. Load MySQL data to Google BigQuery in minutes. One of the formats accepted by BigQuery, the other being JSON. Oracle SQL Query Builder. By default, if you do not explicitly specify the type of file, BigQuery expects a CSV file. Edit the dataset's schema. Select a GCP service to filter the logs. Create your Dataset and Table on BigQuery Console. --source_format BigQuery accepts both CSV and JSON files. Click the menu icon (menu) in the global navigation bar and click BigQuery Viewer (beta) to open the BigQuery Viewer. - Java program would export existing BigQuery table data into Cloud storage. BigQuery's views are logical views, not materialized views, which means that the query that defines the view is re-executed every time the view is queried. I would suggest you create a support ticket to get dedicated support. Nested fields get flattened with their full-qualified names. read_sql_table (table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None) [source] ¶ Read SQL database table into a DataFrame. Disable ”Temporary ” tables drop Known Issues with custom BQ Types. Solution Diagram for building the visualization of the Google Analytics 360 BigQuery Export Schema. Load MySQL data to Google BigQuery in minutes. In spite of that the fact table and the dimension table are clearly different in their functionalities and features but all of them are data containers. Mixpanel recommends a single table schema because it makes querying the data simpler. Use a BQ Dataset with default table expiration 3. // See the License for the specific language governing permissions and // limitations under the License. However, with the introduction of Oracle Database 12c and particularly with the Processing object type DATABASE_EXPORT/. This is a nice script. Step-By-Step: Google BigQuery data extract using SSIS. Loop over rows of data within a table or view and run another component for each row. In GCP a project is a way to organize cloud resources. Tables Columns Data type with. Google BigQuery hits the gym and beefs up! August 19, 2016 October 15, 2018 Shine Solutions Group 2 Comments At Shine we’re big fans of Google BigQuery, which is their flagship big data processing SaaS. It supports many data sources, including BigQuery. •Tables: Within each dataset, a table is imported for each day of export. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. Microsoft Azure Cosmos DB System Properties Comparison Amazon Redshift vs. importing and exporting tabular data to and from Tabular Storage objects based on JSON Table Schema descriptors. Each app for which BigQuery exporting is enabled will export its data to that single dataset. read_sql_table (table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None) [source] ¶ Read SQL database table into a DataFrame. Although BigQuery provides a number of built-in functions, it does not have a built-in for decoding URL-encoded strings. This post will contain a simple JS function helping you to export data from Bigquery to Sheets. pg2bq is made for one thing: export tables from PostgreSQL to Google BigQuery. For the demonstration, I have the following BigQuery tables that I would like to import to Athena. Supermetrics for BigQuery is the first ever native BigQuery Data Transfer Service app for non-Google marketing platforms. This page describes how to export or extract data from BigQuery tables. One good option is exporting to Cloud Memorystore (Redis) for serving end-user queries, we have described how to do this elsewhere. - From Cloud storage, we read exported files directly into spark using their service account credentials file. However, this functionality is available in JavaScript, so we can extend BigQuery with a simple User-Defined Function to decode this type of data:. To query a full table, you can query like this:. In our case, we are interested in a partition based on state field. BigQuery tornadoes reads from a BigQuery table that has the 'month' and 'tornado' fields as part of the table schema, computes the number of tornadoes in each month, and outputs the results to a BigQuery table. The following operations allow you to work with table data. As for why you might want to send it to Google Analytics and export from there… Google Analytics does a ton of value-adds on the data that flows in there. Using the drop-down at the top of the Filter Tab, quickly change your Schema or Folder View. It is also not the project that contains the selected dataset and table. BigQuery Export Schema - This article explains the format and schema of the Google Analytics Premium data that is imported into BigQuery. The dataset uses the Google Analytics view id as its name. For a list of data stores that are supported as sources or sinks by the copy activity, see the Supported data stores table. You can use the same BigQuery connection for both Data Connector (input) and Result Output (output), but, currently, cannot use connections authenticated by OAuth for output. If the table does exist, the specified columns must match the existing table. BigQuery allows you to specify a table's schema when you load data into a table, and when you create an empty table. As a valued partner and proud supporter of MetaCPAN, StickerYou is happy to offer a 10% discount on all Custom Stickers, Business Labels, Roll Labels, Vinyl Lettering or Custom Decals. Replicate your MySQL database to Google BigQuery to improve the performance of your SQL queries at scale and to generate custom real-time reports and dashboards. In this example, we deploy the Create Table component onto the Matillion ETL canvas to create a table that will hold airport data. The BigQuery Doesn't allow us to modify the table schema directly. Schema Inspector. First step is obvious - you need a Google Analytics: App + Web property to be able to export data out of it to Firebase. How do you choose between a view and a table? If working with static data, do a table (ie: data for January 2019) If working dynamic data, do a view (ie: previous week) BigQuery exports — how you get data out of BQ — can happen in three ways: Full daily export - This is the default. Connection objects. This information is made available via the tables. Username: Username of the target database. Uses Google command line tools. Then, as shown in the figure below, use aju-dev-demos as the BigQuery Project ID, london_bikes_weather as the dataset ID, and bikes_weather as the table name. Exporting Google Analytics Clickstream Data to Your Own Data Warehouse. You will learn how to take data from the relational system and to the graph by translating the schema and using import tools. Next you configure storage for the data in BigQuery. Service Account Auth Token. Next, you'd see a Configure Flat File Destination window, select the table from the source table to export the data to the CSV file you specified earlier. Hi @Joni Kämppä (Nordcloud) currently my only option is to try to export columns as datetimes in Big Query and then schedule a query in Big Query to convert it into timestamps. Posts about bigquery written by mim. The cons of BigQuery is that you have to move data into BigQuery's storage system. When copying a table, the destination datasets must reside in the same location. The problem was not just transferring the data or export/import, the issue was the very old Cassandra!. We're sorry but bigquery-schema-generator doesn't work properly without JavaScript enabled. For the demonstration, I have the following BigQuery tables that I would like to import to Athena. Additionally, a table is imported for events received throughout the current day. approx_max_file_size_bytes (long) – This operator supports the ability to split large table dumps into multiple files (see notes in the filename param docs above). The BigQuery project id, required unless json_key or json_key_file is provided. This post will help you to load your data stored in PostgreSQL to Google BigQuery. Want to export these results? It’s possible to download the results from small queries directly as a CSV, but for larger results you’ll need to save them as another table and then export the table to GCS and download from there. You will find the exported dataset in your bucket. A simple workaround is to normalize the table in BigQuery using UNNEST, export it, then denormalize it in q using command xgroup. It also provides facilities that make it convenient to access data that is tied to an App Engine appspot, such as request logs. They aggregate referral information into channels. Tables Columns Data type with. Google BigQuery processes every operation as an insert for each row. We use multiple projects to maintain our BigQuery datasets. If you execute the following query And then export the table from BigQuery in a. it used to be that way (for efficiency reasons, as +ryan boyd mentions), but the limitation is now lifted with the. To properly work with the data, please, pay attention with all these fields. It's good for analyzing large quantities of data quickly, but not for modifying it. I will discuss in detail in subsequent sections. BigQuery-Python. •Source_format •BigQuery accepts both CSV and JSON files. Clicks, impressions, hit number, client ID. This guide will teach you the process for exporting data from a relational database (PostgreSQL) and importing into a graph database (Neo4j). They aggregate referral information into channels. Export data from SQL Server to Hadoop or Azure Storage. BigQuery. , tables may have nested and repeated fields. bq_ddl> operator can be used to create, delete and clear Google BigQuery Datasets and Tables. Core Functionalities. env must …. the need to export and load them separately into. The first part of our app, the runQuery() function, issues a query to BigQuery from Apps Script then connects to Google Sheets to store the results into a new Sheet (note we left out. With a simple save command, you can export kdb+ table to CSV. Hence we will have export our data to a CSV(comma separated. One user_migrations table which lists all instances of merging and migrating users. They take one row of input and produce zero or more rows of output, potentially with a different schema. Partitioned tables allow you to query a subset of data, thus increasing query performance and decreasing costs. Database Export Schema Table Statistics Table Statistics This database had issue in gathering stats in the past and run for days without completion in the prompt -- generate SQL to export schema stat to stat table. schema: string, optional. In the BigQuery export, each row represents a session. Next you configure storage for the data in BigQuery. generate-schema - Convert JSON Objects to MySQL Schema, JSON Schema, Mongoose Schema, Google BigQuery, or a Generic template for Swagger files, documentation, code generation, and more Javascript Convert JSON Objects to MySQL Table Schema, JSON Schema, Mongoose Schema, ClickHouse Schema, Google BigQuery, or a Generic template for documentation, code generation, and more. A modern BigQuery client for your team. With these table formats, you can now use Dataproc for workloads that need: ACID transaction. Data for the current day is not final until the daily. filtering bigquery data with where - youtube. In the mabl web UI, Visit Settings > Integrations and click BigQuery Export. For each source_table in the source_tables_to_copy list, do: Create a new empty target_table in the target_dataset using the source_table. Also, counting like select counts star, how many records are in the table. The bq load command creates or updates a table and loads data in a single step. BigQuery requires all requests to be authenticated, supporting a number of Google-proprietary mechanisms as well as OAuth. Enter activity_email_send as the table name. Storage, as we mentioned is two cents per GB per month, after 90 days if your table has not had any edits to it, or additions drops down by half, and screening inserts when you're inputting in your real time, individual records to BigQuery is per cents per GB. Projects, Datasets and Tables in BigQuery. BigQuery almost certainly does something similar. /** * @name Export Data to BigQuery * * @overview The Export Data to BigQuery script sets up a BigQuery * dataset and tables, downloads a report from Google Ads and then * loads the report to BigQuery. a blog about the web, Go, and building things. sql' extension, select File -> Export -> SQL Forward Engineer Create Script. The pros of BigQuery is that you get superior performance out of the box: with Athena, not only do you have to worry about data formats, most likely you have to convert your data into one of the suitable data formats. Transfer data from Facebook, Instagram, LinkedIn, Twitter, Bing, and more into Google's marketing data warehouse with Supermetrics for BigQuery. Next, you’d see a Configure Flat File Destination window, select the table from the source table to export the data to the CSV file you specified earlier. Exporting from BigQuery in CSV format with. From Firestore to BigQuery with Firebase Functions ••• In building my sentiment analysis service, I needed a way to get data into BigQuery + Data Studio so I could analyze trends against pricing data. @google-cloud/bigquery. Predicting with model is quite straightforward. By default, if you do not explicitly specify the type of file, BigQuery expects a CSV file. In contrast, this script uses all. Query your data on Treasure Data and export results to BigQuery. google-cloud-dataflow My scenario is a variation on the one discussed here: How do I write to BigQuery using a schema computed during Dataflow execution? In this case, the goal is that same (read a schema during execution, then write a table with that schema to BigQuery), but I want to accomplish Making use of workers in Custom Sink. Example: Copy GA360 exports to a partitioned table. The user can define filters for each of the Tables, Views folders. To that table I added the fields OrderHistory, Status, and TotalAmount. Although BigQuery provides a number of built-in functions, it does not have a built-in for decoding URL-encoded strings. Export data. Order is important when structuring queries to export results from Treasure Data to Big Query, so make a note of the order of the fields in the schema. If you execute the following query And then export the table from BigQuery in a. This version is aimed at full compliance with the DBI specification. In this brief tutorial, we'll explore two different methods of examining your database tables in more detail to see just what the schema really looks like. For a one time process - you can manually do it via BigQuery UI - on the right of the table name -> click on the drop list - >export table. For example, we can pull some data from our BigQuery table and make sure that in our select, we name our columns depending on what the TensorFlow requires. Choose to share it publicly and copy the public link for later use. Each table has been curated to include detailed table and field descriptions as well as table labels allowing users to search for BigQuery tables of interest using a free-form text search or via available filters. •Source_format •BigQuery accepts both CSV and JSON files. Many businesses want to benefit from the Google BigQuery ability to quickly perform complex analytical queries over petabytes of data, and need to load their data from Mailchimp and other applications to the Google BigQuery service for centralized storing and data analysis. This param allows developers to specify the file size of the splits. You can export data from the editor by doing the following: Click Edit Table. See, no code necessary! Although knowing code certainly helps data scientists carve through huge data sets and analyze them more intensively, hopefully, this walkthrough with BigQuery and Google Data Studio demonstrates just how low the barriers to entry are in working with big data now. Export Crashlytics Data to BigQuery. You need a BigQuery project, so you can either select an existing project or create a new one. Once this is done, export your Google BigQuery logs from Stackdriver to the pub/sub: Go to the Stackdriver page and filter the Google BigQuery logs. BigQuery Page in google console Check table in BigQuery. More information about the BigQuery Storage API can be found here. In MySQL, the -- (double-dash) comment style requires the second dash to be followed by at least one whitespace or control character (such as a space, tab, newline, and so on). The Introduction to BigQuery training course initially provides high level overview of BigQuery. Changes PostgreSQL types to Bigquery types. Microsoft Azure Cosmos DB System Properties Comparison Amazon Redshift vs. — but there is no scheduler yet to schedule a query to run at a specific time or periodicity. Step 4: Script To Import Data Into BigQuery. Now — instead of using this small table, let’s use the whole table to compute k-means with BigQuery. The list of Aggregate functions includes Avg, Count, Max, Min and Sum which are very common. But it is the first project in the table returned by the DAX query Source = GoogleBigQuery. One _dropped_tables table. gz compression yields 141 MB of files. For exporting data into Google Cloud Storage. You get hit level data, which is collected at each individual user interaction. And that’s it. The following operations allow you to work with table data. You can export your Crashlytics data into BigQuery for further analysis. They filter out bots and spam. Specify the file location by URI. With these table formats, you can now use Dataproc for workloads that need: ACID transaction. (For example, the exports could be loaded into Spanner which require an Avro schema as a standalone file or could be read with Avro readers that require a schema at initialization time). Step 1: Export data from Oracle DB to CSV format using Oracle SQL Developer. • BigQuery was not built to be a transactional store. At first, the idea of moving data from Oracle into BigQuery may sound straight forward. BigQuery does not offer exporting to CSV if a table contains a REPEATED column. Upon running the first journey through the BigQuery export feed,. If you select the single table schema, Mixpanel creates a mp_master_event table. Step-By-Step: Google BigQuery data extract using SSIS. Go to Logging and click Exports. BigQuery can export up to 1 GB of data to a single file. Iterate through this process as many times as it takes to load all of your tables into BigQuery. Specify the table schema: two necessary (column name and data type) and two optional (column mode and description). They filter out bots and spam. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data as raw binary (default ','). // See the License for the specific language governing permissions and // limitations under the License. For a list of data stores that are supported as sources or sinks by the copy activity, see the Supported data stores table. First step is obvious - you need a Google Analytics: App + Web property to be able to export data out of it to Firebase. The streaming insert row by row is very slow: to insert 1000 rows the execution of the code below took about 10 minutes. But remember JSON Table Schema is designed to be extensible. As I mentioned in the previous post clickstream data empowers analysts to answer much more complex (and valuable) business questions, namely by integration with other data sources (e. Schema is required for CSV and JSON formats and is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats when using external tables. BigQuery Page in google console Check table in BigQuery. For reference, an export of 1B hits from Google Analytics 360 to. Partitioned tables should make the queries faster and cheaper. But remember JSON Table Schema is designed to be extensible. BigQuery allows you to scale to petabyte and is great enterprise data warehouse for analytics. BigQuery is a structured, table-based SQL database. Want to export these results? It’s possible to download the results from small queries directly as a CSV, but for larger results you’ll need to save them as another table and then export the table to GCS and download from there. Google BigQuery. A BigQuery table is a standard, two-dimensional table with individual records Every table is described by a schema that. For exporting data into Google Cloud Storage. SQL query recipes, with inputs and outputs in BigQuery; Sync query recipes, with output in BigQuery and input in either Google Cloud Storage or BigQuery. •Created and Queries HBase tables using HBase Shell and Apache Phoenix. When you load Avro, Parquet, ORC, Firestore export files, or Datastore export files, the schema is automatically retrieved from the self-describing source data. You will learn how to take data from the relational system and to the graph by translating the schema and using import tools. Let’s take a step by step look at each of the steps mentioned above. Benefits of table formats. - From Cloud storage, we read exported files directly into spark using their service account credentials file. Brief Recap of the BigQuery Schema. Load MySQL data to Google BigQuery in minutes. The table contains a single row. This component uses the Google BigQuery API to retrieve data and load it into a Redshift table. sh extracts a list of all tables from the MySQLschema and calls mysql_table_to_big_query. Final thoughts. Unlike BigTable, it targets data in big picture and can query huge volume of data in a short time. • BigQuery is a massively scalable distributed analytics engine. the schema of returned rows with. Super easy to set up, not even a BigQuery schema to set up; Useful metadata (such as latency, user ip, status codes) is built-into each record; Cons. Mixpanel recommends a single table schema because it makes querying the data simpler. If the table already exists in BigQuery, when you execute the job, the table is deleted and a new table is added with the schema as JSON. Final thoughts. During this ingestion, Streamsets is tried with Cloudera cluster. If you execute the following query And then export the table from BigQuery in a. ” Under “Schema,” click “Edit as Text” and paste the JSON file you copied earlier. Enterprise Cloud Bridge. You can access the dataset here. The other system works out really well in practice. Predicting with model. (For example, the exports could be loaded into Spanner which require an Avro schema as a standalone file or could be read with Avro readers that require a schema at initialization time). Using the BigQuery Export schema, which of the following fields are available in BigQuery? Custom dimensions, landing page, hit number, client ID. At first, the idea of moving data from Oracle into BigQuery may sound straight forward. priority - Specifies a priority for the query. bq_ddl>: Managing Google BigQuery Datasets and Tables¶. in PowerBI,you can export from R or Python visuals but there…. Datasets correspond to GA views. if the table does not exist, Beam creates the table specified in location when the first record is written. The table produced by the export has fairly simple and self-explanatory schema, here is the query we have used to extract the data to track egress traffic:. Click the Export BigQuery button to get started. Posts about bigquery written by mim. This method does not return the data in the table, it only returns the table resource, which describes the structure of this table. Schema Inspector. To query several tables and combine the result as if it were one table, BigQuery provides the table_date_range function. Exporting Cassandra 2. BigQuery Export. Data for the current day is not final until the daily. (For example, the exports could be loaded into Spanner which require an Avro schema as a standalone file or could be read with Avro readers that require a schema at initialization time). When you create a clustered table in BigQuery, the table data is automatically organized based on the contents of one or more columns in the table's schema. This means you can use it to interact with genomic data in an ad-hoc fashion: Queries that on traditional systems take hours to run (as batch jobs) can instead be processed in seconds. Step 3: Connecting Google Cloud Pub/Sub to BigQuery through Google Dataflow. Exporting from BigQuery in CSV format with. The course features interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. Import & Export Tools Enhanced in 18. The streaming insert row by row is very slow: to insert 1000 rows the execution of the code below took about 10 minutes. Because of how Mixpanel’s API is designed, two of the three tables in the Mixpanel integration - the mixpanel_export and mixpanel_funnels tables - can only be queried by day. SQL Server INFORMATION_SCHEMA Views | See if a Table Exists Data Tutorial Databases What is the Problem? When writing queries for a database you might be new to, or one that changes often, you might want to run a quick check to find all the tables in a specific database, or the columns in the database, or to search if table or column exists. bq load [--source_format=NEWLINE_DELIMITED_JSON|CSV] destination_table data_source_uri table_schema destination_table The fully-qualified table name of the table to create. These tables have the format "ga_sessions_YYYYMMDD". now this may scale differently (next project), but for 100,000 rows, non-extracted jet connection, and this display, string is faster. Following on from this, it would be really handy to export the schema from an existing table in the text/JSON format that is accepted by BigQuery, does anyone know if it's possible to export a schema, or does anyone know of a quick workaround to get a schema? Thanks in advance. R defines the following functions: bqWait bqInsertData bqInsertLargeData madedotcom/retl source: R/bigquery. Schema-related errors will cause the pipeline to crash. The Introduction to BigQuery training course initially provides high level overview of BigQuery. If you are exporting more than 1 GB of data, you must export your data to multiple files.