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public class SqlSelect extends SqlCall {
  //~ Static fields/initializers ---------------------------------------------

  // constants representing operand positions
  public static final int FROM_OPERAND = 2;
  public static final int WHERE_OPERAND = 3;
  public static final int HAVING_OPERAND = 5;

  SqlNodeList keywordList;
  SqlNodeList selectList;

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LogicalProject(subset=[rel#28:Subset#3.ENUMERABLE.[]], EMPNO=[$0], GENDER=[$2], NAME=[$1]): rowcount = 15.0, cumulative cost = {15.0 rows, 45.0 cpu, 0.0 io}, id = 23
  LogicalFilter(subset=[rel#22:Subset#2.NONE.[]], condition=[=($1, 'John')]): rowcount = 15.0, cumulative cost = {15.0 rows, 100.0 cpu, 0.0 io}, id = 21
    LogicalProject(subset=[rel#20:Subset#1.NONE.[]], EMPNO=[$0], NAME=[$1], GENDER=[$3]): rowcount = 100.0, cumulative cost = {100.0 rows, 300.0 cpu, 0.0 io}, id = 19
      CsvTableScan(subset=[rel#18:Subset#0.ENUMERABLE.[]], table=[[SALES, EMPS]], fields=[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0 cpu, 0.0 io}, id = 0

masayuki038

2019-06-03 20:49:33,973 [main] DEBUG - Cheapest plan:
EnumerableProject(EMPNO=[$0], GENDER=[$2], NAME=[$1]): rowcount = 15.0, cumulative cost = {71.66666666666667 rows, 187.08333333333334 cpu, 0.0 io}, id = 59
  EnumerableFilter(condition=[=($1, 'John')]): rowcount = 15.0, cumulative cost = {56.66666666666667 rows, 142.08333333333334 cpu, 0.0 io}, id = 58
    CsvTableScan(table=[[SALES, EMPS]], fields=[[0, 1, 3]]): rowcount = 100.0, cumulative cost = {41.66666666666667 rows, 42.083333333333336 cpu, 0.0 io}, id = 57

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/*   1 */ org.apache.calcite.DataContext root;
/*   2 */ 
/*   3 */ public org.apache.calcite.linq4j.Enumerable bind(final org.apache.calcite.DataContext root0) {
/*   4 */   root = root0;
/*   5 */   final org.apache.calcite.linq4j.Enumerable _inputEnumerable = ((org.apache.calcite.adapter.csv.CsvTranslatableTable) root.getRootSchema().getSubSchema("SALES").getTable("EMPS")).project(root, new int[] {
/*   6 */     0,
/*   7 */     1,
/*   8 */     3});
/*   9 */   return new org.apache.calcite.linq4j.AbstractEnumerable(){
/*  10 */       public org.apache.calcite.linq4j.Enumerator enumerator() {

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import time

import pandas as pd
%matplotlib inline

import matplotlib.pyplot as plt

def load_data():
    return [{"a": "k1", "b": 2}, {"a": "k2", "b": 4}, {"a": "k3", "b": 5}, {"a": "k1", "b": 15}]

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const puppeteer = require('puppeteer');

(async () => {
          const browser = await puppeteer.launch();
          const page = await browser.newPage();
          await page.goto('https://www.google.com');
          await page.screenshot({path: 'screenshot.png'});

          await browser.close();
})();

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from time import sleep
import os
import json
import threading

from flask import Flask, jsonify

from uwsgidecorators import postfork
import pystuck
pystuck.run_server(unix_socket='/tmp/utd-master')

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package net.wrap_trap.calcite_avro_sample;

import org.apache.calcite.model.ModelHandler;
import org.apache.calcite.schema.Schema;
import org.apache.calcite.schema.SchemaFactory;
import org.apache.calcite.schema.SchemaPlus;

import java.io.File;
import java.util.Map;

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public class AvroSchema extends AbstractSchema {
  private Map<String, Table> tableMap;
  private File directory;

  public AvroSchema(File directory) {
    this.directory = directory;
  }

  @Override
  public Map<String, Table> getTableMap() {

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  @Override
  public RelDataType getRowType(RelDataTypeFactory relDataTypeFactory) {
    JavaTypeFactory typeFactory = (JavaTypeFactory) relDataTypeFactory;

    List<Pair<String, RelDataType>> ret = schema.getFields().stream().map(field -> {
      Schema.Type avroFieldType = field.schema().getType();
      if (avroFieldType == Schema.Type.UNION) {
        avroFieldType = getAvroNullableField(field);
      }
      RelDataType relDataType = AvroFieldType.of(avroFieldType).toType(typeFactory);