schema

问题 Can we put a default value in a field of dataframe while creating the dataframe? I am creating a spark dataframe from List<Object[]> rows as : List<org.apache.spark.sql.Row> sparkRows = rows.stream().map(RowFactory::create).collect(Collectors.toList()); Dataset<org.apache.spark.sql.Row> dataset = session.createDataFrame(sparkRows, schema); While looking for a way, I found that org.apache.spark.sql.types.DataTypes contains object of org.apache.spark.sql.types.Metadata class. The documentation

问题 Apologies for the lengthy post for a seemingly simple curiosity, but I wanted to give full context... In Databricks, I am creating a "row" of data based on a specific schema definition, and then inserting that row into an empty dataframe (also based on the same specific schema). The schema definition looks like this: myschema_xb = StructType( [ StructField("_xmlns", StringType(), True), StructField("_Version", DoubleType(), True), StructField("MyIds", ArrayType( StructType( [ StructField("_ID

问题 I am trying to use this library "react-jsonschema-form" to create forms using react and jsonschema. I am trying to use it in my project as described in the example from the website by including the .js file via cdn. It is not working. The exported component "Form" is undefined. I had a look at this similar question Using React component from js source maps but I could not understand the solution offered. I am supposed to alias the default export of JSONSchemaForm. But what is JSONSchemaForm?

问题 I have a set of avro files with slightly varying schemas which I'd like to load into one bq table. Is there a way to do that with one line? Every automatic way to handle schema difference would be fine for me. Here is what I tried so far. 0) If I try to do it in a straightforward way, bq fails with error: bq load --source_format=AVRO myproject:mydataset.logs gs://mybucket/logs/* Waiting on bqjob_r4e484dc546c68744_0000015bcaa30f59_1 ... (4s) Current status: DONE BigQuery error in load

问题 In my Mongoose Schema I'm trying to simulate a dictionary offersInCategory that looks like this: offersInCategory = { "Electronics": 2, "Furniture": 5 }; Mongoose doesn't support dictionaries so I'm forced to use object literals in an array instead, like so: offersInCategory: [{ category: { type: String, enum: ['Furniture', 'Household', 'Electronicts', 'Other'] }, val: { type: Number, min: 0 } }] My problem with this approach is it feels unintuitive. Furthermore it doesn't prevent my model

问题 With spark, import spark.implicits._ val data = Seq( (1, ("value11", "value12")), (2, ("value21", "value22")), (3, ("value31", "value32")) ) val df = data.toDF("id", "v1") df.printSchema() The result is the following: root |-- id: integer (nullable = false) |-- v1: struct (nullable = true) | |-- _1: string (nullable = true) | |-- _2: string (nullable = true) Now if I want to create the schema myself, how should I process? val schema = StructType(Array( StructField("id", IntegerType),

问题 I would like to write a validator for json files that conforms to the json schema paradigm. I've been looking for a grammar that describes json schema without any luck. Do you know if there is any formal description of the json schema specifications that I can use to write a parser? Thank you. f. 回答1: The meta-schema is at http://json-schema.org/schema The semantics are defined in http://json-schema.org/latest/json-schema-validation.html 来源： https://stackoverflow.com/questions/29435810

问题 We plan to add a column of type list to an existing cassandra table which data file size is about 350 GB. We can temporarily halt all the read/write for a few minutes while applying the schema change. Our understanding is that cassandra does not lock a table when applying schema changes, but to be sure our DBA wants to do an experiment on a table with datafile at 25 GB in size. However it will take 3-4 weeks to grow in such size on a small server where a non-production cassandra server is

问题 In order to insert same data to same set of tables in different schemas (data about the mobile application where app id is primary key but app is cross-platform and exists on different platforms. Schema per platfrom so pp id does not interfere for tables with it as fk). I already has some infrastructure for it and I wasn't expecting this requirement. For me I see the easiest way is having existing model class binded to some db+schema_1+table_name insert data to first schema then somehow

问题 In order to insert same data to same set of tables in different schemas (data about the mobile application where app id is primary key but app is cross-platform and exists on different platforms. Schema per platfrom so pp id does not interfere for tables with it as fk). I already has some infrastructure for it and I wasn't expecting this requirement. For me I see the easiest way is having existing model class binded to some db+schema_1+table_name insert data to first schema then somehow