Hive Struct To Json String

I want to avoid creating struct for every json string , so I define json string in here. The syntax for specifying ARRAY, STRUCT, and MAP types in a CREATE TABLE statement is compatible between Impala and Hive. We need to use Hive SerDe's to load the JSON data to Hive tables. CREATE TABLE IF NOT EXISTS bookStat ( statTime STRING, bizCode STRING, saleInfo STRUCT < bookName:STRING, saleCount:INT > )ROW FORMAT SERDE 'org. For the nested JSON example I will use the example define in this JSON SerDe page here. Here is a thread from the community explaining the process of creating. How to determine if a JSON key has been set to null or not provided I was recently skimming my Twitter feed for new Go articles, libraries, etc and I stumbled across a tweet with this message:. A workaround was to add set hive. Note: hive-third-functions support hive-0. String and a JSON Payload¶ Sometimes the producer would find it easier to just send a message with Schema. When using that JSON Serde, you define your Hive schema based on the contents of the JSON. Storing JSON data can be more flexible than declaring all of your individual fields in your table schema, but can lead to higher costs. Currently it expects an integer but it should be relatively easy to change this to string / text for your purpose. Below is a list of Hive features that we don’t support yet. In this post, I'd like to expand upon that and show how to load these files into Hive in Azure HDInsight. This tutorial covers using Spark SQL with a JSON file input data source in Scala. hive 테이블 생성. Generally, in Hive and other databases, we have more experience on working with primitive data types like: Numeric Types. Do I need to use struct?How do I define struct in HIVE side (the structure of JSON is not known while mapping is created). The addressed value is returned and if there is no such value None is returned. Loading JSON Files with Nested Arrays from Azure Blob Storage into Hive Tables in HDInsight In my previous post I wrote about how to upload JSON files into Azure blob storage. The external table definition is below, I have defined this in Hive and reverse engineered into ODI just like the previous post. Re: How to load json data with nested arrays into hive? Date: Sun, 22 Jun 2014 04:57:41 GMT: Hi, Chris, I like the Json serde solution better, but there's another alternative to achieve what you're trying to do. Storing JSON data can be more flexible than declaring all of your individual fields in your table schema, but can lead to higher costs. A JsonConverter is used to override how a type is serialized. I downloaded json-serde-1. The aim of this post is to help you getting started with creating a data pipeline using flume, kafka and spark streaming that will enable you to fetch twitter data and analyze it in hive. Available in Hive 0. Apache Kylin Home. Python on HDInsight. Since both sources of input data is in JSON format, I will spend most of this post demonstrating different ways to read JSON files using Hive. However I have one element which is array of structs. The marshal and Unmarshal method returned in Bytes format, but we can change these data to strings/JSON in Go. Creating JSON Structure (Part-2): In our previous tutorial, we discussed creating a simple JSON file using sample data sets. I know there exists get_json_object(), but the things is I want to multiple JSON operations in a single select statement and don't want to incur the cost of parsing the JSON over and over again, because our json structures are quite large. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. get_json_object(string json_string, string path) Extracts json object from a json string based on json path specified, and returns json string of the extracted json object. Hive String and Binary columns are restricted to a maximum 1GB in size. For consistency, other human-readable formats are encouraged to develop analogous conventions where possible. We will show examples of JSON as input source to Spark SQL’s SQLContext. Let's have a look at some ObjectInspectors:. Hive supports a couple of ways to read JSON data, however, I think the easiest way is to use custom JsonSerDe library. 0, decimal type support added in Hive 0. mode: string [Optional] The field mode. With the prevalence of web and mobile applications, JSON has become the de-facto interchange format for web service API's as well as long-term. Let us look at those string functions in detail to. Now, jdo2-api-2. The marshal and Unmarshal method returned in Bytes format, but we can change these data to strings/JSON in Go. 2, and MEP 3. I know there exists get_json_object(), but the things is I want to multiple JSON operations in a single select statement and don't want to incur the cost of parsing the JSON over and over again, because our json structures are quite large. 0; bug with float types fixed in Hive 0. Data-Width Handling Differences Between Hive and Vertica The HCatalog Connector relies on Hive SerDe classes to extract data from files on HDFS. The best tool for using JSON docs with Hive is rcongui's openx Hive-JSON-Serde. The Hive UNION type is not currently supported in Impala. The Hive JSON SerDe is used to process JSON data, most commonly events. By continuing to use Pastebin, you agree to our use of cookies as described in the Cookies Policy. This does not work when a struct<> data type is in the schema, and the Hive schema contains just a portion of the struct elements. It will convert String into an array, and desired value can be fetched using the right index of an array. In my previous post I wrote about how to upload JSON files into Azure blob storage. Hive has UDF/UDTF to support extracting data from JSON/XML (json_object, json_tuple, xpath_string, xpath_int ). Hive String and Binary Types Considerations. (11 replies) hi, I'm very, very new to Hadoop, Hive, etc. It resides on top of Hadoop to summarize Big Data, and makes querying and analyzing easy. 本文提供一种用SCALA把JSON串转换为HIVE表的方法,由于比较简单,只贴代码,不做解释。有问题可以留言探讨 以下是测试结果 create table example ( people_type bigint,people_num double,people struct CREATE EXTERNAL TABLE tweets (id BIGINT, id_str STRING, user STRUCT, a string, and an integer. Hive is used to load data from HDFS into hive table. JSON_EXTRACT or JSON_EXTRACT_SCALAR. Accessing hierarchical JSON data in Hive from Denodo 20180306 4 of 7 employee view This query works as follows: the json_tuple function extracts the attributes passed as parameter from the json string and then, the LATERAL VIEW clause appends this information to the results of the query acting as a join. LATERAL VIEW explode (column_name_with_array) AdTable as column_name_View Maybe the simplest way is to create JSON files from XML files and then to import JSON files into Hive. STRUCT a) Explodes an array to multiple rows. json_tools should be able to map any valid Json to a type hierarchy. Hive is used to load data from HDFS into hive table. I'm using SqlBulkCopy to import CSV data to a database, but I'd like to be able to combine columns. anything else. Starting with MEP 6. Hive has a rich and complex data model that supports maps, arrays and structs, that could be mixed and matched, leading to arbitrarily nested structures, like in JSON. Note that the file that is offered as a json file is not a typical JSON file. 0 but should be portable to lower Hive versions. Arrays and maps are supported. A new json_tuple() UDTF is introduced in hive 0. The values should correspond to certain field names in MongoDB. string get_json_object(string Extract json object from a json string based on json path specified, and json_string, string path) return json string of the extracted json object. This is much more efficient than calling GET_JSON_OBJECT to retrieve more than one key from a single JSON string. Avro's Json encoding uses a Json object to tag each union value with the intended type. String to Json. I'm trying to import a JSON file into a hive table, and trying to execute the. Nothing to do with your enum but with your switch statement, which needs constants in its case clauses. I'm very satisfied, but I want to check out the json tuple and see how it performs versus the "get_json_object" class share | improve this answer answered Jul 10 '17 at 22:05. 057 seconds, Fetched: 10 row(s). Handling JSON using SerDe's Converting JSON schema to Hive table Create Schema Step 1: ( Product string, ID string, Address struct). Querying JSON records via Hive /* ---[ Opacity: A brief rant ]--- */ Despite the popularity of Hadoop and its ecosystem, I've found that much of it is frustratingly underdocumented or at best opaquely documented. JSON data comes with a key-value pair. get_json_object(string json_string, string path) Extracts json object from a json string based on json path specified, and returns json string of the extracted json object. It is important to understand that when using Hive to query data in an Oracle NoSQL Database table, the schema of the Hive external table you create is dependent on the schema of the corresponding Oracle NoSQL Database table you wish to query. Environment: Amazon EMR, S3, etc. I am using get_json_object to fetch each element of json. The UDF pasted below I think is close to your needs. Yes, Hive supports file formats like Avro which we can use to save the json data process. An example using complex data types is provided later in this topic. A Serde Serializer is responsible for selecting the convention by which Rust structs and enums are represented in that format. I am able to create table successfully. encoding/json already knows how to check JSON against Go types. , create a second (temporary) table with one record for each struct in the array "features". This tutorial covers using Spark SQL with a JSON file input data source in Scala. For instance, lets say I have a firstname and lastname column in my CSV. On this table i've edited a complete column and now i wish to put it back onto hive. Writers like os. While HAWQ does not natively support these types, you can create HAWQ functions or application code to extract subcomponents of these complex data types. It will return null if the input json string is invalid. Here is a thread from the community explaining the process of creating. The syntax for specifying ARRAY, STRUCT, and MAP types in a CREATE TABLE statement is compatible between Impala and Hive. This is to make adding fields to objects in code more compact. This method is available since Spark 2. Structs and enums in JSON. 위 형식과 같은 json 파일의 샘플 파일 (sampledata. I want to unmarshal an array of json object into a struct. Thats not practical because every sender has other sensors/data. Thankfully this is very easy to do in Spark using Spark SQL DataFrames. java,enums,core. Here are a few examples of parsing nested data structures in JSON using Spark DataFrames (examples here done with Spark 1. Creating JSON Structure (Part-2): In our previous tutorial, we discussed creating a simple JSON file using sample data sets. It takes a set of names (keys) and a JSON string, and returns a tuple of values using one function. Amazon Athena is a serverless interactive query service that allows analytics using standard SQL for data residing in S3. boolean: in_file(string str, string filename) Returns true if the string str appears as an entire line. The declaration starts with the keyword type, then a name for the new struct, and finally the keyword struct. Load Data. 以下の記述がありましたが、具体的な手順等はなかったのでやってみました。 hive-json-schema を使うことで,入れ子になった JSON DDL を記述することができます。. , no upper-case or special characters. Good Post! Thank you so much for sharing this pretty post, it was so good to read and useful to improve my knowledge as updated one, keep blogging. i'm using the function get_json_object to extract each element of the json an insert in a table field. Operator is only supported on struct or list of struct types 'int_value' in definition of VIEW minimal_sample_viewb [ SELECT null. 2, and MEP 3. I dont know right way to do, because I couldn't find type conversion for JSON array like this in documentation. In order to be complaint with some object oriented systems an explicit 'null' json value is required in the serialized string. * CREATE TABLE foo (a INT, b ARRAY, c STRUCT); * JSON objects can also interpreted as a Hive MAP type, so long as the keys * and values in the JSON object are all of the appropriate types. This issue is known for at least 7 years, and seems like it will never be fixed for legacy reason (JSONEncoder uses NSJSONSerialization, and that is very old). We use cookies for various purposes including analytics. The following code does the job correctly, but I don't know if t. The Hive technology in ODI also has the ARRAY, STRUCT and MAP types seeded. Below is a list of Hive features that we don't support yet. traffic_json_tab( id string, clientid string, source string, destination string, priority string, reliability string, eventtime bigint, eventtimeasstring string, sender string, type string, properties string, direction string, receivedtime bigint, receivedtimeasstring string, payload struct<. The JSON Schema discovery tool processes a set of JSON documents and produces a schema that encompasses all of the records in all of the documents. Event Sample:. string: get_json_object(string json_string, string path) It extracts json object from a json string based on json path specified, and returns json string of the extracted json object. Before we move ahead you can go through the below link blogs to gain more knowledge on Hive and its working. Hive has UDF/UDTF to support extracting data from JSON/XML (json_object, json_tuple, xpath_string, xpath_int ). 0 and later. It takes array, a string, and an integer. 0-jar-with-dependencies. 本記事では前回のBinaryテーブルに続いてMapR-DBのJSONテーブルにHiveからアクセスする方法について紹介します。 Hiveの各型とJSONテーブルの型の対応についてはこちらのドキュメントに記載さ. The automatic JSON schema discovery is equivalent to the json-schema tool below. That's why I want to convert it to array> Thanks for help. JSON Column-izer. This conversion can be done using SQLContext. My ultimate goal is to get the single value of each field within the JSON string. JSON_EXTRACT(json_string_expr, json_path_string_literal), which returns JSON values as STRINGs. Re: How to load json data with nested arrays into hive? Date: Sun, 22 Jun 2014 04:57:41 GMT: Hi, Chris, I like the Json serde solution better, but there's another alternative to achieve what you're trying to do. JSONLab is a free and open-source implementation of a JSON/UBJSON encoder and a decoder in the native MATLAB language. 语法: get_json_object(string json_string, string path) 返回值: string 说明:解析json的字符串json_string,返回path指定的内容。如果输入的json字符串无效,那么返回NULL。. Load Data. Hive MAPJOIN + LATERAL VIEW. For primitives, we can use the standard Hive object inspectors. 우선 HDFS에 샘플데이터 put. 0 or higher. reason') from test where game_id='xxx'; I get following exception. It returns NULL if the input json string is invalid. Hive is used to load data from HDFS into hive table. Hi! I just switch to CDH 5. The UDF pasted below I think is close to your needs. CREATE TABLE struct_demo ( id BIGINT, name STRING, -- A STRUCT as a top-level column. One is using native Hive JSON function such as get_json_object and the other is to use a JSON Serde to parse JSON objects containing nested elements with lesser code. This document describes how to access to hierarchical data represented in JSON format in Hive from Denodo Virtual DataPort. Example 2 3. It contains two data types: VARCHAR and CHAR. json is one of the most wildly used Go packages. You can browse for and follow blogs, read recent entries, see what others are viewing or recommending, and request your own blog. 在这篇文章中,我将介绍一下Spark SQL对Json的支持,这个特性是Databricks的开发者们的努力结果,它的目的就是在Spark中使得查询和创建JSON数据变得非常地简单。. This issue is known for at least 7 years, and seems like it will never be fixed for legacy reason (JSONEncoder uses NSJSONSerialization, and that is very old). HIVE Table/Data 생성. reason') from test where game_id='xxx'; I get following exception. The automatic JSON schema discovery is equivalent to the json-schema tool below. Need the syntax of. Demonstrates how the table ID column -- and the ID field within the STRUCT can coexist without a name conflict. We can encode and decode struct data using marshal and unmarshal. DataFrames and SQL support a common way to access a variety of data sources, like Hive, Avro, Parquet, ORC, JSON, and JDBC. This section describes the Hive connector for MapR Database JSON table. Best How To : I found a solution for this: Use the Hive explode UDTF to explode the struct array, i. The Hive connector supports the creation of MapR-DB based Hive tables. For instance, lets say I have a firstname and lastname column in my CSV. It can be used to convert a MATLAB data structure (array, struct, cell, struct array and cell array) into JSON/UBJSON formatted strings, or to decode a JSON/UBJSON file into MATLAB data structure. JSON file into Hive table using SerDe. boolean: in_file(string str, string filename) Returns true if the string str appears as an entire line. getValue() maybe returns a value that never changes, but it is not a constant expression to the compiler. v2/bson" I try to handle a nested struct and put this into mongodb. json() on either an RDD of String, or a JSON file. hive> show functions; and hive> desc will give you more info about these UDFs. 7; Convert JSON array to Hive array; Does Struct inside Struct works? array become struct<> when doing select; Question on converting an array of structs into a map; get_json_object for nested field returning a String instead of an Array; additional hive functions; Bug in Hive Split function. Now that I am more familiar with the API, I can describe an easier way to access such data, using the explode() function. For example, an Avro union of a string and an int which has an int value of 1 would be encoded in Json as {"int":1}. CREATE TABLE struct_demo ( id BIGINT, name STRING, -- A STRUCT as a top-level column. (as of Hive 0. Step-by-step guide of how to proceed with twitter analytics tasks using Elastic MapReduce, DynamoDB and Amazon Data Pipeline. For the nested JSON example I will use the example define in this JSON SerDe page here. In this way, we will cover each. Matt Martin As currently implemented, the parameters passed to the reflect() UDF must be primitives (and I'm guessing that "collectedSet" is a list). It has some fields along with User struct with user as key. JsonSerDe) The OpenX SerDe (org. Complex type support applies to data stored in Avro, Parquet and JSON formats. This demo has been tested on HDP-3. java,enums,core. json 파일 형식. Nothing to do with your enum but with your switch statement, which needs constants in its case clauses. That means splitting that string up on the other side. Inside tokens / is replaced by ~1 and ~ is replaced by ~0. def fromInternal (self, obj): """ Converts an internal SQL object into a native Python object. String is the field name, in your case "name", and the third argument is the value to match on. With no standard for dates in JSON, the number of possible different formats when interoping with other systems is endless. To serialize a collection - a generic list, array, dictionary, or your own custom collection - simply call the serializer with the object you want to get JSON for. STRUCT a) Explodes an array to multiple rows. 057 seconds, Fetched: 10 row(s). hive json, load twitter data into hive. Since both sources of input data is in JSON format, I will spend most of this post demonstrating different ways to read JSON files using Hive. I use the following packages: "gopkg. mapping parameter should be set to a JSON string whose keys correspond to certain Hive columns or Hive table struct field names. I am able to create table successfully. 0-jar-with-dependencies. The JSON Schema discovery tool processes a set of JSON documents and produces a schema that encompasses all of the records in all of the documents. My json string has already $ in name of json key, how can I extract its value. How to convert Array to String in Hive0. Major Hive Features. Hive schemas understand arrays, maps and structs. i am able to query the data from hive using select, However when i do select * from JSON_EXTERNAL_TABLE limit 1, the output is an Invalid JSON though the message in HDFS is a valid JSON. JsonHiveSchema mandi-2016-03-27 mandi_commodity_raw The ouput of following commands will provide HQL create to create hive table with your povided table name. But even the Programming Hive book lacks good information on how to effectively use Hive with JSON records, so I'm cataloging my findings here. I want to show you the power of some built-in Hive functions to transform JSON data, which is 'normalized' (optimized for transport) into a denormalized format which is much more suitable for data analysis. get_json_object(string json_string, string path) Extracts json object from a json string based on json path specified, and returns json string of the extracted json object. But just like earlier, we can use interface{} smarter here too, by giving encoding/json the right types to work with. Generally, in Hive and other databases, we have more experience on working with primitive data types like: Numeric Types. I know there exists get_json_object(), but the things is I want to multiple JSON operations in a single select statement and don't want to incur the cost of parsing the JSON over and over again, because our json structures are quite large. Solution Step 1: JSON sample data. Reading JSON Nested Array in Spark DataFrames In a previous post on JSON data, I showed how to read nested JSON arrays with Spark DataFrames. Handling JSON using SerDe's Converting JSON schema to Hive table Create Schema Step 1: ( Product string, ID string, Address struct). The Hive technology in ODI also has the ARRAY, STRUCT and MAP types seeded. If the property is defined as a string, works. `int_value` FROM ` default `. (6 replies) Hi there, I want to create a new JSON Field/Column type. Each line must contain a separate, self-contained valid JSON object. Hive explode array to rows. Hive String and Binary Types Considerations. Starting with MEP 6. Spark SQL does not currently support inserting to tables using dynamic partitioning. Finally we print values on the Result struct. Amazon Athena is a serverless interactive query service that allows analytics using standard SQL for data residing in S3. Another option you have is to use JSON/XML to represent map. encoding/json already knows how to check JSON against Go types. I have hdfs json files, specifically the files are tweets messages in json format, i'm trying to read that files with hive into a table. 0-jar-with-dependencies. In this way, we will cover each. The 2 JSON files I'm going to load are up in my blob storage, acronym/abc. Is this an expected one ?. We can select the data just fine but writing it is the issue. About DNS-Lookup. reason') from test where game_id='xxx'; I get following exception. json() on either an RDD of String, or a JSON file. My ultimate goal is to get the single value of each field within the JSON string. ToString() ToString() ToString() ToString() Provides a string representation of the property for debugging purposes. Another UDF provided by Hive is called json_tuple, which performs better than get_ json _object. Now, let us know what is Struct and its working. Spark Structured Streaming is a stream processing engine built on Spark SQL. In this article, we will discuss on the various Hive string functions and usage. I wrote about a JSON SerDe in another post and if you use it, you know it can lead to pretty complicated nested tables. Since both sources of input data is in JSON format, I will spend most of this post demonstrating different ways to read JSON files using Hive. Hive JSON Schema Generator Overview. Nothing to do with your enum but with your switch statement, which needs constants in its case clauses. I prefer to map JSON objects to structs. In this case, your connector configuration should be set to value. Finally we print values on the Result struct. On this table i've edited a complete column and now i wish to put it back onto hive. PITFALL: Backslash escaped in JSON. Note that the file that is offered as a json file is not a typical JSON file. The automatic JSON schema discovery is equivalent to the json-schema tool below. DEFAULT is the name of the initial Hive database. 本記事では前回のBinaryテーブルに続いてMapR-DBのJSONテーブルにHiveからアクセスする方法について紹介します。 Hiveの各型とJSONテーブルの型の対応についてはこちらのドキュメントに記載さ. There are two other tools that generate Hive schemas from JSON:. HIVE Table/Data 생성. HiveQL is the Hive query language. The problem is that this table has some arrays and therefore I can't use OpenCSV wich converts all columns to string. The UDF pasted below I think is close to your needs. Step 5: Use Hive function. JsonHiveSchema mandi-2016-03-27 mandi_commodity_raw The ouput of following commands will provide HQL create to create hive table with your povided table name. Starting with MEP 6. by Abdul-Wahab April 25, 2019 Abdul-Wahab April 25, 2019. case needs constant expressions like "helloWorld", the expression Header. CREATE TABLE json_tab( DocId. 1) Create an HDFS directory: hadoop fs -mkdir -p //fitbit. 0) string: get_json_object(string json_string, string path) Extract json object from a json string based on json path specified, and return json string of the extracted json object. It will convert String into an array, and desired value can be fetched using the right index of an array. Here are some samples of parsing nested data structures in JSON Spark DataFrames (examples here finished Spark one. Twitter streaming converts tweets to Avro format and send Avro events to downsteam HDFS sinks, when Hive table backed by Avro load the data, I got. The external table definition is below, I have defined this in Hive and reverse engineered into ODI just like the previous post. Understanding the INSERT INTO Statement This section describes how to use the INSERT INTO statement to insert or overwrite rows in nested MapR Database JSON tables, using the Hive connector. BigQuery's JSON functions give you the ability to find values within your stored JSON data, by using JSONPath-like expressions. 0) string: get_json_object(string json_string, string path) Extract json object from a json string based on json path specified, and return json string of the extracted json object. The reducer fails with an exception like this:. Hive Maps also will work with JSONObjects. I am using get_json_object to fetch each element of json. Hive support yyyy-MM-dd date format. PXF maps each of these complex types to text. The marshal and Unmarshal method returned in Bytes format, but we can change these data to strings/JSON in Go. This is a good and handy tutorial to udnerstand mapper functions and use them. If you are interested in using Python instead, check out Spark SQL JSON in Python tutorial page. CREATE TABLE if not exists member ( name STRING, id INT, props STRUCT < departname:STRING, alias:STRING > ) ROW FORMAT SERDE 'org. GitHub Gist: instantly share code, notes, and snippets. Here are a few examples of parsing nested data structures in JSON using Spark DataFrames (examples here done with Spark 1. I am new to Hive, I am trying to use struct data type. One is using native Hive JSON function such as get_json_object and the other is to use a JSON Serde to parse JSON objects containing nested elements with lesser code. Spark SQL can automatically infer the schema of a JSON dataset, and use it to load data into a DataFrame object. serDes is serializer — Deserializer tool which help hive to understand the json format of tweet (which is loaded from. Prior to 0. It will return null if the input json string is invalid. The external table definition is below, I have defined this in Hive and reverse engineered into ODI just like the previous post. For primitives, we can use the standard Hive object inspectors. For instance, lets say I have a firstname and lastname column in my CSV. The best tool for using JSON docs with Hive is rcongui's openx Hive-JSON-Serde. json解析函数:get_json_object 语法: get_json_object(string json_string, string path) 返回值: string 说明:解析json的字符串json_string,返回path指定的内容。如果输入的json字符串无效,那么返回NULL。 举例: hive> select get_json_object(‘{“store”:. The JSON path can only have the characters [0-9a-z_], for example, no upper-case or special characters. Using the Navigator API and JSON formatted metadata definition files, entities can be assigned properties in bulk, prior to extraction. however JSON will get untidy and parsing it will get tough. I want to show you the power of some built-in Hive functions to transform JSON data, which is 'normalized' (optimized for transport) into a denormalized format which is much more suitable for data analysis. 0) string: get_json_object(string json_string, string path) Extract json object from a json string based on json path specified, and return json string of the extracted json object. Hive supporta strutture oltre che dati scali e questo si presta bene per accede a record i cui dati sono strutturati come ad esempio nei json. An example using complex data types is provided later in this topic. Note: hive-third-functions support hive-0. However, we will cover how to write own Hive SerDe. We are talking about parsing such values that are "JSON array", "escaped" and present in "string format". JSON supports fewer data types than MATLAB, which results in loss of type information. I think this is primarily due to the fact that Hive only supports a limited number of complex types (specifically: list, map, struct, union) and these types are abstracted in a way which makes it difficult to convert to concrete Java types and. $ is used as root object for get_json_object. Learn how to use Python user-defined functions (UDF) with Apache Hive and Apache Pig in Apache Hadoop on Azure HDInsight. CREATE TABLE struct_demo ( id BIGINT, name STRING, -- A STRUCT as a top-level column. 本文提供一种用SCALA把JSON串转换为HIVE表的方法,由于比较简单,只贴代码,不做解释。有问题可以留言探讨 以下是测试结果 create table example ( people_type bigint,people_num double,people struct CREATE EXTERNAL TABLE tweets (id BIGINT, id_str STRING, user STRUCT select * from iteblog limit 10; OK NULL NULL NULL NULL NULL NULL NULL NULL NULL NULL Time taken: 0. In this post, I'd like to expand upon that and show how to load these files into Hive in Azure HDInsight. net does for built in structs). An example using complex data types is provided later in this topic. Since then I have also learnt about and used the Hive-JSON-Serde. When using that JSON Serde, you define your Hive schema based on the contents of the JSON. Custom struct field tags in Golang Posted on 16 Jul 2016 Structs in Golang represent one of the most common variable types and used practically everywhere, from dealing with configuration options to marshaling of JSON or XML documents using encoding/json or encoding/xml packages. CREATE TABLE json_tab( DocId. Hive json file with example: Hive: Hive is a data warehouse infrastructure tool to process structured data in Hadoop. (As of Hive 0. One of my elasticsearch fields (ACTIVITIES) is an array of JSON objects with structure like this:. The default representation for this enum in Serde is called the externally tagged enum representation. streaming to HDFS from Flume) then you would probably want a Hive table over the HDFS file so that it is live when queried. hive_database_name: The Hive database where the source data resides. For example, an Avro union of a string and an int which has an int value of 1 would be encoded in Json as {"int":1}. STRUCT a) Explodes an array to multiple rows. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: