OpenOpened commented on a change in pull request #1200: [HUDI-514] A schema
provider to get metadata through Jdbc
URL: https://github.com/apache/incubator-hudi/pull/1200#discussion_r378055288
##########
File path:
hudi-utilities/src/main/java/org/apache/hudi/utilities/UtilHelpers.java
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@@ -235,4 +248,57 @@ public static TypedProperties readConfig(InputStream in)
throws IOException {
defaults.load(in);
return defaults;
}
+
+ /***
+ * call spark function get the schema through jdbc.
+ * The code logic implementation refers to spark 2.4.x and spark 3.x.
+ * @param options
+ * @return
+ * @throws Exception
+ */
+ public static Schema getJDBCSchema(Map<String, String> options) throws
Exception {
+ scala.collection.immutable.Map<String, String> ioptions =
toScalaImmutableMap(options);
+ JDBCOptions jdbcOptions = new JDBCOptions(ioptions);
+ Connection conn = JdbcUtils.createConnectionFactory(jdbcOptions).apply();
+ String url = jdbcOptions.url();
+ String table = jdbcOptions.tableOrQuery();
+ JdbcOptionsInWrite jdbcOptionsInWrite = new JdbcOptionsInWrite(ioptions);
+ boolean tableExists = JdbcUtils.tableExists(conn, jdbcOptionsInWrite);
+
+ if (tableExists) {
+ JdbcDialect dialect = JdbcDialects.get(url);
+ try (PreparedStatement statement =
conn.prepareStatement(dialect.getSchemaQuery(table))) {
+ statement.setQueryTimeout(Integer.parseInt(options.get("timeout")));
+ try (ResultSet rs = statement.executeQuery()) {
+ StructType structType;
+ if (Boolean.parseBoolean(ioptions.get("nullable").get())) {
+ structType = JdbcUtils.getSchema(rs, dialect, true);
+ } else {
+ structType = JdbcUtils.getSchema(rs, dialect, false);
+ }
+ return AvroConversionUtils.convertStructTypeToAvroSchema(structType,
table, "hoodie." + table);
+ }
+ }
+ } else {
+ throw new HoodieException(String.format("%s table does not exists!",
table));
+ }
+ }
+
+ /**
+ * Replace java map with scala immutable map.
+ * refers:
https://stackoverflow.com/questions/11903167/convert-java-util-hashmap-to-scala-collection-immutable-map-in-java/11903737#11903737
Review comment:
Do you guys have a better way? I checked the relevant information. If you
want to achieve conversion elegantly, there are only two methods. First, using
scala code to do the conversion, you need to implement a scala conversion
class. Second, rewrite the related spark method with java. The disadvantage is
that it may cause compatibility problems in the future.
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